Measuring economic growth from outer space


Globalization, structural change and productivity growth


Taking the pulse of the economy: measuring GDP


Institutions, Institutional Change and Economic Performance


Data reuse and the open data citation advantage


The citation advantage of linking publications to research data

Colavizza G
Hrynaszkiewicz I
Staden I
Whitaker K
McGillivray B


Citation advantage of open access articles


Self-selected or mandated, open access increases citation impact for higher quality research

Gargouri Y
Hajjem C
Lariviere V
Gingras Y
Carr L
Brody T
Harnad S


Is the open access citation advantage real? A systematic review


How open science helps researchers succeed

McKiernan EC
Bourne PE
Brown CT
Buck S
Kenall A
Lin J


Current status of Landsat program, science, and applications

Wulder MA
Loveland TR
Roy DP
Crawford CJ
Masek JG
Woodcock CE


Benefits of the free and open Landsat data policy

Zhu Z
Wulder MA
Roy DP
Woodcock CE
Hansen MC
Radeloff VC


The FAIR Guiding Principles for scientific data management and stewardship

Wilkinson MD
Dumontier M
Aalbersberg IJ
Appleton G
Axton M
Baak A


Joint declaration of data citation principles


A data citation roadmap for scholarly data repositories

Fenner M
Crosas M
Grethe JS
Kennedy D
Hermjakob H
Rocca-Serra P


The NASA Astrophysics Data System: Overview

Kurtz MJ
Eichhorn G
Accomazzi A
Grant CS
Murray SS
Watson JM

Astronomy and Astrophysics Supplement Series


Difference-in-differences with multiple time periods


Difference-in-differences with variation in treatment timing


Estimating dynamic treatment effects in event studies with heterogeneous treatment effects


Two-way fixed effects estimators with heterogeneous treatment effects


The central role of the propensity score in observational studies for causal effects


Matching methods for causal inference: a review and a look forward


Revisiting event-study designs: robust and efficient estimation


Pre-test with caution: event-study estimates after testing for parallel trends


A more credible approach to parallel trends


Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples


NASA'S Earth Science Data Stewardship Activities

Abstract: NASA has been collecting Earth observation data for over 50 years using instruments on board satellites, aircraft and ground-based systems. With the inception of the Earth Observing System (EOS) Program in 1990, NASA established the Earth Science Data and Information System (ESDIS) Project and initiated development of the Earth Observing System Data and Information System (EOSDIS). A set of Distributed Active Archive Centers (DAACs) was established at locations based on science discipline expertise. Today, EOSDIS consists of 12 DAACs and 12 Science Investigator-led Processing Systems (SIPS), processing data from the EOS missions, as well as the Suomi National Polar Orbiting Partnership mission, and other satellite and airborne missions. The DAACs archive and distribute the vast majority of data from NASA’s Earth science missions, with data holdings exceeding 12 petabytes The data held by EOSDIS are available to all users consistent with NASA’s free and open data policy, which has been in effect since 1990. The EOSDIS archives consist of raw instrument data counts (level 0 data), as well as higher level standard products (e.g., geophysical parameters, products mapped to standard spa


How the Open Data Policy of the Landsat Program Has Advanced Our Understanding of Environmental Change

Abstract: A time series is a sequence of observations of a phenomenon taken sequentially in time. A crucial characteristic of a time series is the dependence among adjacent observations, techniques for analyzing this dependence are referred to as time series analysis.  This analytical approach enables us to predict or forecast future values of a time series, study the impact of various inputs on the observed phenomenon, and examine interrelationships among related time series variables. Within the geographical sciences, time series analysis has historically been limited to coarse-resolution satellite data, as constructing time series of data suitable for studying land cover and land use dynamics, such as Landsat data, were prohibitively costly. A transformative shift occurred in 2008 when the U.S. Government decided to make free and open all past and future data collected by the Landsat satellite program. The decision brought about a paradigm shift away from analyzing individual images or observations to continuous monitoring in time. Of particular relevance to environmental remote sensing is the ability to forecast observations, if we can predict how future observations should behave, we


A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth

Mohammadali Hemati
Mahdi Hasanlou
Masoud Mahdianpari
Fariba Mohammadimanesh

Abstract: With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding of the dynamics of the Earth’s surface at a spatial scale relevant to management, scientific inquiry, and policy development. In this study, we identify trends in Landsat-informed change detection studies by surveying 50 years of published applications, processing, and change detection methods. Specifically, a representative database was created resulting in 490 relevant journal articles derived from the Web of Science and Scopus. From these articles, we provide a review of recent developments, opportunities, and trends in Landsat change detection studies. The impact of the Landsat free and open data policy in 2008 is evident in the literature as a turning point in the number and nature of change detection studies. Based upon the search terms used and articles included, average number of Landsat images used in studies increased from 10 images before 2008 to 100,000 images in 2020. The 2008 opening of the Landsat archive resulted in a marked increase in the number of images used per study, typically providing the basis for the other trends in evidence. These key trends include an increase in automated processing, use of analysis-ready


Fifty years of Landsat science and impacts

Michael A. Wulder
David P. Roy
Volker C. Radeloff
Thomas R. Loveland
Martha C. Anderson
David M. Johnson
Sean P. Healey
Zhe Zhu

Abstract: Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets was limited. The early years of the Landsat program delivered a series of technological breakthroughs, pioneering new methods, and demonstrating the ability and capacity of digital satellite imagery, creating a template for other global Earth observation missions and programs. Innovations driven by the Landsat program have paved the way for subsequent science, application, and policy support activities. The economic and scientific value of the knowledge gained through the Landsat program has been long recognized, and despite periods of funding uncertainty, has resulted in the program's 50 years of continuity, as well as substantive and ongoing improvements to payload and mission performance. Free and open access to Landsat data, enacted in 2008, was unprecedented for medium spatial resolution Earth observation data and substantially increased usage and led to a proliferation of science and application opportunities. Here, we highlight key developments over the past 50 years of the Landsat program that have influenced and changed our scientific understanding of the Earth system. Maj


US data policy for Earth observation from space

Abstract: Distribution of data from U.S. Earth observations satellites is subject to different data policies and regulations depending on whether the systems in question are operational or experimental. Specific laws, regulations, and policies are in place for the distribution of satellite data from the National Oceanic and Atmospheric Administration (NOAA) operational environmental satellites and from NASA experimental systems. There is a government wide policy for exchange of data for global change research. For the Earth Observing System (EOS) and its international partner programs, a set of data exchange principles is nearing completion. The debate over the future of the LANDSAT program in the U.S. will impact policy for the programs, but the outcome of the debate is not yet known.


Satellite Remote Sensing Data Policy: Benefits of Free and Open Data


Operational continental-scale land cover mapping of Australia using the Open Data Cube

Christopher J. Owers
R. Lucas
D. Clewley
Belle Tissott
Sean M. T. Chua
Gabrielle Hunt
N. Mueller
Carole Planque

Abstract: ABSTRACT To comprehensively support national and international initiatives for sustainable development, land cover products need to be reliably and routinely generated within operational frameworks. Coupled with consistent semantics and taxonomies, ensuring confidence in mapping land cover for multiple time periods, facilitates informed decision-making at scales appropriate to multiple policy domains. The United Nations Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) provides a taxonomy that comparable at different scales, level of detail and geographic location. The Open Data Cube (ODC) initiative offers a framework for operational continental-scale land cover mapping using analysis-ready Earth Observation data. This study utilised the FAO LCCS framework and the Landsat sensor data through Digital Earth Australia (DEA; Australia’s ODC instance) to generate consistent and continent-wide land cover mapping (DEA Land Cover) of the Australian continent. DEA Land Cover provides annual maps from 1988 to 2020 at 25 m resolution. Output maps were validated with ∼12,000 independent validation points, giving an overall map accuracy of 80%. DEA Land Cover provides Australia with a nationally consistent picture of land cover, with an open-source software package using readily available global coverage data and demonstrates a pathway of adoption for national implementations across the world.


The Role and Evolution of NASA's Earth Science Data Systems

Abstract: One of the three strategic goals of NASA is to Advance understanding of Earth and develop technologies to improve the quality of life on our home planet (NASA strategic plan 2014). NASA's Earth Science Data System (ESDS) Program directly supports this goal. NASA has been launching satellites for civilian Earth observations for over 40 years, and collecting data from various types of instruments. Especially since 1990, with the start of the Earth Observing System (EOS) Program, which was a part of the Mission to Planet Earth, the observations have been significantly more extensive in their volumes, variety and velocity. Frequent, global observations are made in support of Earth system science. An open data policy has been in effect since 1990, with no period of exclusive access and non-discriminatory access to data, free of charge. NASA currently holds nearly 10 petabytes of Earth science data including satellite, air-borne, and ground-based measurements and derived geophysical parameter products in digital form. Millions of users around the world are using NASA data for Earth science research and applications. In 2014, over a billion data files were downloaded by users from NASAs E


A computational framework for processing time-series of earth observation data based on discrete convolution: global-scale historical Landsat cloud-free aggregates at 30 m spatial resolution

Davide Consoli
Leandro Parente
Rolf Simoes
Murat Şahin
Xuemeng Tian
Martijn Witjes
Lindsey Sloat
Tomislav Hengl

Abstract: Processing large collections of earth observation (EO) time-series, often petabyte-sized, such as NASA’s Landsat and ESA’s Sentinel missions, can be computationally prohibitive and costly. Despite their name, even the Analysis Ready Data (ARD) versions of such collections can rarely be used as direct input for modeling because of cloud presence and/or prohibitive storage size. Existing solutions for readily using these data are not openly available, are poor in performance, or lack flexibility. Addressing this issue, we developed TSIRF (Time-Series Iteration-free Reconstruction Framework), a computational framework that can be used to apply diverse time-series processing tasks, such as temporal aggregation and time-series reconstruction by simply adjusting the convolution kernel. As the first large-scale application, TSIRF was employed to process the entire Global Land Analysis and Discovery (GLAD) ARD Landsat archive, producing a cloud-free bi-monthly aggregated product. This process, covering seven Landsat bands globally from 1997 to 2022, with more than two trillion pixels and for each one a time-series of 156 samples in the aggregated product, required approximately 28 hours of computation using 1248 Intel® Xeon® Gold 6248R CPUs. The quality of the result was assessed using a benchmark dataset derived from the aggregated product and comparing different imputation strategies. The resulting reconstructed images can be used as input for machine learning models or to map biop


Optical remotely sensed time series data for land cover classification: A review

Cristina Gómez
Joanne C. White
Michael A. Wulder

ISPRS Journal of Photogrammetry and Remote Sensing

Abstract: Accurate land cover information is required for science, monitoring, and reporting. Land cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring and mapping of land cover and land cover change in a consistent and robust manner over large areas is made possible with Earth Observation (EO) data. Land cover products satisfying a range of science and policy information needs are currently produced periodically at different spatial and temporal scales. The increased availability of EO data-particularly from the Landsat archive (and soon to be augmented with Sentinel-2 data)-coupled with improved computing and storage capacity with novel image compositing approaches, have resulted in the availability of annual, large-area, gap-free, surface reflectance data products. In turn, these data products support the development of annual land cover products that can be both informed and constrained by change detection outputs. The inclusion of time series change in the land cover mapping process provides information on class stability and informs on logical class transitions (both temporally and categorically). In this review, we present the issues and opportunities associated with generating and validating time-series informed annual, large-area, land cover products, and identify methods suited to incorporating time series information and other novel inputs for land cover characterization. © 2016.


Stewardship of NASA's Earth Science Data and Ensuring Long-Term Active Archives

Abstract: Program, NASA has followed an open data policy, with non-discriminatory access to data with no period of exclusive access. NASA has well-established processes for assigning and or accepting datasets into one of 12 Distributed Active Archive Centers (DAACs) that are parts of EOSDIS. EOSDIS has been evolving through several information technology cycles, adapting to hardware and software changes in the commercial sector. NASA is responsible for maintaining Earth science data as long as users are interested in using them for research and applications, which is well beyond the life of the data gathering missions. For science data to remain useful over long periods of time, steps must be taken to preserve: (1) Data bits with no corruption, (2) Discoverability and access, (3) Readability, (4) Understandability, (5) Usability' and (6). Reproducibility of results. NASAs Earth Science data and Information System (ESDIS) Project, along with the 12 EOSDIS Distributed Active Archive Centers (DAACs), has made significant progress in each of these areas over the last decade, and continues to evolve its active archive capabilities. Particular attention is being paid in recent years to ensure that


Copernicus User Uptake: From Data to Applications

Lorenza Apicella
Mónica De Martino
Alfonso Quarati

ISPRS International Journal of Geo-Information

Abstract: The European Programme Copernicus, one of the principal sources of free and open Earth Observation (EO) data, intends to sustain social and economic advancements to the European Union. To this end, User Uptake initiatives have been undertaken to increase Copernicus awareness, dissemination, and competencies, thus supporting the development of downstream applications. As part of the activities performed in the EO-UPTAKE project, we illustrate a set of application scenario workflows exemplifying usage practices of the data and tools available in the Copernicus ecosystem. Through the know-how gained in the design and development of the application scenarios and the bibliographic analysis on downstream applications, we discuss a series of practical recommendations to promote the use of Copernicus resources towards a wider audience of end-users boosting the development of new EO applications along with some advice to data providers to improve their publication practices.


A Review of Open Remote Sensing Data with GIS, AI, and UAV Support for Shoreline Detection and Coastal Erosion Monitoring

D. Christofi
C. Mettas
E. Evagorou
Neophytos Stylianou
M. Eliades
C. Theocharidis
Antonis E. Chatzipavlis
T. Hasiotis

Abstract: This review discusses the evolution and integration of open-access remote sensing technology in shoreline detection and coastal erosion monitoring through the use of Geographic Information Systems (GIS), Artificial Intelligence (AI), Unmanned Aerial Vehicles (UAVs), and Ground Truth Data (GTD). The Sentinel-2 and Landsat 8/9 missions are highlighted as the primary core datasets due to their open-access policy, worldwide coverage, and demonstrated applicability in long-term coastal monitoring. Landsat data have allowed the detection of multi-decadal trends in erosion since 1972, and Sentinel-2 has provided enhanced spatial and temporal resolutions since 2015. Through integration with GIS programs such as the Digital Shoreline Analysis System (DSAS), AI-based processes such as sophisticated models including WaterNet, U-Net, and Convolutional Neural Networks (CNNs) are highly accurate in shoreline segmentation. UAVs supply complementary high-resolution data for localized validation, and ground truthing based on GNSS increases the precision of the produced map results. The fusion of UAV imagery, satellite data, and machine learning aids a multi-resolution approach to real-time shoreline monitoring and early warnings. Despite the developments seen with these tools, issues relating to atmosphere such as cloud cover, data fusion, and model generalizability in different coastal environments continue to require resolutions to be addressed by future studies in terms of enhanced sensors


Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world

Pierre Defourny
Sophie Bontemps
Nicolas Bellemans
Cosmin Cara
Gérard Dedieu
Eric Guzzonato
Olivier Hagolle
Jordi Inglada

Abstract: The convergence of new EO data flows, new methodological developments and cloud computing infrastructure calls for a paradigm shift in operational agriculture monitoring. The Copernicus Sentinel-2 mission providing a systematic 5-day revisit cycle and free data access opens a completely new avenue for near real-time crop specific monitoring at parcel level over large countries. This research investigated the feasibility to propose methods and to develop an open source system able to generate, at national scale, cloud-free composites, dynamic cropland masks, crop type maps and vegetation status indicators suitable for most cropping systems. The so-called Sen2-Agri system automatically ingests and processes Sentinel-2 and Landsat 8 time series in a seamless way to derive these four products, thanks to streamlined processes based on machine learning algorithms and quality controlled in situ data. It embeds a set of key principles proposed to address the new challenges arising from countrywide 10 m resolution agriculture monitoring. The full-scale demonstration of this system for three entire countries (Ukraine, Mali, South Africa) and five local sites distributed across the world was a major challenge met successfully despite the availability of only one Sentinel-2 satellite in orbit. In situ data were collected for calibration and validation in a timely manner allowing the production of the four Sen2-Agri products over all the demonstration sites. The independent validation of


The Sentinels EOPF Toolkit: Driving Community Adoption of the Zarr data format for Copernicus Sentinel Data

Sabrina H. Szeto
Julia Wagemann
Emmanuel Mathot
James Banting

Abstract:
The Standard Archive Format for Europe (SAFE) specification has been the established approach to publishing Copernicus Sentinel data products for over a decade. While SAFE has pushed the ecosystem forward through new ways to search and access the data, it is not ideal for processing large volumes of data using cloud computing. Over the last few years, data standards like STAC and cloud-native data formats like Zarr and COGs have revolutionised how scientific communities work with large-scale geospatial data and are becoming a key component of new data spaces, especially for cloud-based systems.The ESA Copernicus Earth Observation Processor Framework (EOPF) will be providing access to &#8220;live&#8221; sample data from the Copernicus Sentinel missions -1, -2 and -3 in the new Zarr data format. This set of reprocessed data allows users to try out accessing and processing data in the new format and experiencing the benefits thereof with their own workflows.This presentation introduces a community-driven toolkit that facilitates the adoption of the Zarr data format for Copernicus Sentinel data. The creation of this toolkit was driven by several motivating questions:&#160;What common challenges do users face and how can we help them overcome them?&#160;
What resources would make it easier for Sentinel data users to use the new Zarr data format?&#160;
How can we foster a community of users who will actively contribute to the creation of this toolkit and support


Active fire detection using Landsat-8/OLI data

Wilfrid Schroeder
Patricia Oliva
Louis Giglio
Brad Quayle
Eckehard Lorenz
Fabiano Morelli

Abstract: The gradual increase in Landsat-class data availability creates new opportunities for fire science and management applications that require higher-fidelity information about biomass burning, improving upon existing coarser spatial resolution (≥ 1 km) satellite active fire data sets. Targeting those enhanced capabilities we describe an active fire detection algorithm for use with Landsat-8 Operational Land Imager (OLI) daytime and nighttime data. The approach builds on the fire-sensitive short-wave infrared channel 7 complemented by visible and near-infrared channel 1-6 data (daytime only), while also expanding on the use of multi-temporal analysis to improve pixel classification results. Despite frequent saturation of OLI's fire-affected pixels, which includes radiometric artifacts resulting from folding of digital numbers, our initial assessment based on visual image analysis indicated high algorithm fidelity across a wide range of biomass burning scenarios, gas flares and active volcanoes. Additional field data verification confirmed the sensor's and algorithm's ability to resolve fires of significantly small areas compared to current operational satellite fire products. Commission errors were greatly reduced with the addition of multi-temporal analysis tests applied to co-located pixels, averaging less than 0.2% globally. Because of its overall quality, Landsat-8/OLI active fire data could become part of a network of emerging earth observation systems providing enhanced sp


Landsat-7 Mission and Early Results

Abstract: The Landsat-7 mission has the goal of acquiring annual data sets of reflective band digital imagery of the landmass of the Earth at a spatial resolution of 30 meters for a period of five years using the Enhanced Thematic Mapper Plus (ETM+) imager on the Landsat-7 satellite. The satellite was launched on April 15, 1999. The mission builds on the 27-year continuous archive of thematic images of the Earth from previous Landsat satellites. This paper will describe the ETM+ instrument, the spacecraft, and the ground processing system in place to accomplish the mission. Results from the first few months in orbit will be given, with emphasis on performance parameters that affect image quality, quantity, and availability. There will also be a discussion of the Landsat Data Policy and the user interface designed to make contents of the archive readily available, expedite ordering, and distribute the data quickly. Landsat-7, established by a Presidential Directive and a Public Law, is a joint program of the National Aeronautics and Space Administration (NASA) Earth Science Enterprise and the United States Geological Survey (USGS) Earth Resources Observing System (EROS) Data Center.


Policy issues and data communications for NASA earth observation missions until 1985

Abstract: The series of LANDSAT sensors with the highest potential data rates of the missions were examined. An examination of LANDSAT imagery uses shows that relatively few require transmission of the full resolution data on a repetitive quasi real time basis. Accuracy of global crop size forecasting can possibly be improved through information derived from LANDSAT imagery. A current forecasting experiment uses the imagery for crop area estimation only, yield being derived from other data sources.


Disparities in Surgical Research Output Between Hospital Systems and National Healthcare Research Institutions: A Systematic Review of Global Trends

Suhaib J. S. Ahmad
Miriam Khalil
A. Khalid
Ameer Khamise
D. Rawaf
Ahmed R. Ahmed
Anil Lala
Edgar Gelber

Abstract: ABSTRACT This systematic review examined global disparities in surgical research output between hospital systems and national healthcare institutions. A bibliometric analysis of the 50 most cited surgical articles in Web of Science was performed following PRISMA. High-income countries, particularly North America and Western Europe, dominated output, while Sub-Saharan Africa, South Asia, and parts of the Middle East were underrepresented. Male first authors accounted for 88% of articles; female authorship showed comparable citation performance. Higher co-authorship correlated with greater citations but lower evidence levels. Equitable funding, open access, and investment in low-resource settings are essential to foster inclusive, context-relevant innovation. KEY TAKE-AWAYS High-impact surgical research remains concentrated in university-affiliated centers in high-income countries, with no articles originating from national healthcare research institutions or low- and middle-income settings. Despite comparable citation performance, women are underrepresented as first authors (12%), highlighting persistent gender imbalances in surgical academia. Collaborative, multi-author studies and consensus-based methodological guidelines achieve the highest citation densities, underscoring the value of broad research networks and standardized frameworks.


Developments in Landsat Land Cover Classification Methods: A Review

Abstract: Land cover classification of Landsat images is one of the most important applications developed from Earth observation satellites. The last four decades were marked by different developments in land cover classification methods of Landsat images. This paper reviews the developments in land cover classification methods for Landsat images from the 1970s to date and highlights key ways to optimize analysis of Landsat images in order to attain the desired results. This review suggests that the development of land cover classification methods grew alongside the launches of a new series of Landsat sensors and advancements in computer science. Most classification methods were initially developed in the 1970s and 1980s; however, many advancements in specific classifiers and algorithms have occurred in the last decade. The first methods of land cover classification to be applied to Landsat images were visual analyses in the early 1970s, followed by unsupervised and supervised pixel-based classification methods using maximum likelihood, K-means and Iterative Self-Organizing Data Analysis Technique (ISODAT) classifiers. After 1980, other methods such as sub-pixel, knowledge-based, contextual-based, object-based image analysis (OBIA) and hybrid approaches became common in land cover classification. Attaining the best classification results with Landsat images demands particular attention to the specifications of each classification method such as selecting the right training samples, cho


NASA Earth Science Data Systems: Open Data, Services and Software

Abstract: Open, Public, Electronic and Necessary (OPEN) Government Data Act, which requires all non-sensitive government data to be made available in open and machine-readable formats by default is part of the overall Foundations for Evidence-Based Policymaking (FEBP) Act passed in late 2018. This town hall will bring together data officers and policy makers from NOAA, EPA, NASA and others to discuss the impact of the act on data management strategies going forward. In 1994 NASA's Earth Science Division committed to an open data policy for all civilian Earth satellite data. NASA's Earth Observing System Data and Information System (EOSDIS) became the first large scale data system to facilitate public access to global Earth system data and information. This presentation reviews key elements of EOSDIS data policy and data management activities that support the OPEN Government Data Act.


Free and open-access satellite data are key to biodiversity conservation

Woody Turner
Carlo Rondinini
Nathalie Pettorelli
B. Mora
Allison K. Leidner
Zoltan Szantoi
Graham Buchanan
Stefan Dech


Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations

Aleksandra Wolanin
Gustau Camps‐Valls
Luis Gómez‐Chova
Gonzalo Mateo‐García
Christiaan van der Tol
Yongguang Zhang
Luis Guanter

Abstract: Satellite remote sensing has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthetic function and stress, typically rely on empirical or semi-empirical approaches, which tend to over-simplify photosynthetic mechanisms. In this work, we take advantage of all parallel developments in mechanistic photosynthesis modeling and satellite data availability for an advanced monitoring of crop productivity. In particular, we combine process-based modeling with the soil-canopy energy balance radiative transfer model (SCOPE) with Sentinel-2 and Landsat 8 optical remote sensing data and machine learning methods in order to estimate crop GPP. With this approach, we by-pass the need for an intermediate step to retrieve the set of vegetation biophysical parameters needed to accurately model photosynthesis, while still accounting for the complex processes of the original physically-based model. Several implementations of the machine learning models are tested and validated using simulated and flux tower-based GPP data. Our final neural network model is able to estimate GPP at the tested flux tower sites with r2 of 0.92 and RMSE of 1.38 gC d−1 m−2, which outperforms empirical models based on vegetation indices. The first test of applicability of this model to Lan


Status of the Landsat Data Continuity Mission

Abstract: Efforts to begin implementing a successor mission to Landsat 7, called the Landsat Data Continuity Mission (LDCM), suffered a set back in 2003. NASA and the Department of Interior (DOI)/U.S. Geological Survey (USGS) currently manage the Landsat Program as an interagency partnership. The two agencies had planned to purchase data meeting LDCM specifications from a privately owned and commercially operated satellite system beginning in March, 2007. This approach represented a departure from the traditional procurement of a government owned and operated satellite system. NASA, however, cancelled a Request-for-Proposals (RFP) for providing the required data after an evaluation of proposals received from private industry. NASA concluded that the proposals failed to meet a key objective and expectation of the RFP, namely, to form a fair and equitable partnership between the Government and private industry. Alternative strategies for implementing an LDCM are now under consideration. The Executive Office of the President formed an interagency working group on the LDCM following the RFP cancellation. The working group is considering other options for implementing a successor system to Landsa


FORCE, Landsat + Sentinel-2 Analysis Ready Data and Beyond

Abstract: Ever increasing data volumes of satellite constellations call for multi-sensor analysis ready data (ARD) that relieve users from the burden of all costly preprocessing steps. This paper describes the scientific software FORCE (Framework for Operational Radiometric Correction for Environmental monitoring), an ‘all-in-one’ solution for the mass-processing and analysis of Landsat and Sentinel-2 image archives. FORCE is increasingly used to support a wide range of scientific to operational applications that are in need of both large area, as well as deep and dense temporal information. FORCE is capable of generating Level 2 ARD, and higher-level products. Level 2 processing is comprised of state-of-the-art cloud masking and radiometric correction (including corrections that go beyond ARD specification, e.g., topographic or bidirectional reflectance distribution function correction). It further includes data cubing, i.e., spatial reorganization of the data into a non-overlapping grid system for enhanced efficiency and simplicity of ARD usage. However, the usage barrier of Level 2 ARD is still high due to the considerable data volume and spatial incompleteness of valid observations (e.g., clouds). Thus, the higher-level modules temporally condense multi-temporal ARD into manageable amounts of spatially seamless data. For data mining purposes, per-pixel statistics of clear sky data availability can be generated. FORCE provides functionality for compiling best-available-pixel composi


Semantically Enriched Crop Type Classification and Linked Earth Observation Data to Support the Common Agricultural Policy Monitoring

Maria Rousi
Vasileios Sitokonstantinou
G. Meditskos
I. Papoutsis
Ilias Gialampoukidis
Alkiviadis Koukos
V. Karathanassi
Thanassis Drivas

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Abstract: During the last decades, massive amounts of satellite images are becoming available that can be enriched with semantic annotations for the creation of value-added earth observation products. One challenge is to extract knowledge from the raw satellite data in an automated way and to effectively manage the extracted information in a semantic way, to allow fast and accurate decisions of spatiotemporal nature in a real operational scenario. In this work, we present a framework that combines supervised learning for crop type classification on satellite imagery time-series with semantic web and linked data technologies to assist in the implementation of rule sets by the European common agricultural policy (CAP). The framework collects georeferenced data that are available online and satellite images from the Sentinel-2 mission. We analyze image time-series that cover the entire cultivation period and link each parcel with a specific crop. On top of that, we introduce a semantic layer to facilitate a knowledge-driven management of the available information, capitalizing on ontologies for knowledge representation and semantic rules, to identify possible farmers noncompliance according to the Greening 1 (crop diversification) and SMR 1 rule (protection of waters against pollution caused by nitrates) rules of the CAP. Experiments show the effectiveness of the proposed integrated approach in three different scenarios for crop type monitoring and consistency checking for noncompliance t


Intelligent Systems Technologies and Utilization of Earth Observation Data

Abstract: The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings


The Value of Near Real-Time Earth Observations for Improved Flood Disaster Response

Abstract: Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions "on the ground" more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery from NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) system is used to produce operational estimates of inundation depths and economic damages.These rapid Earth observations are coupled with a decision-analytical model to inform decisions on emergency vehicle routing. Emergency response times from vehicles routed using flood damage data are compared with baseline routes without the benefit of advance information on road conditions. Our results illustrate how the application of ne


Remote Sensing Education and Development Countries: Multilateral Efforts through the Committee on Earth Observation Satellites (CEOS)

Abstract: The Committee on Earth Observation Satellites (CEOS) is an international organization which coordinates space-based Earth observations world wide. Created in 1984, CEOS now comprises 38 national space agencies, regional organizations and international space-related and research groups. The aim of CEOS is to achieve international coordination in the planning of satellite missions for Earth observation and to maximize the utilization of data from these missions world-wide. With regard to developing countries, the fundamental aim of CEOS is to encourage the creation and maintenance of indigenous capability that is integrated into the local decision-making process, thereby enabling developing countries to obtain the maximum benefit from Earth observation. Obtaining adequate access to remote sensing information is difficult for developing countries and students and teachers alike. High unit data prices, the specialized nature of the technology , difficulty in locating specific data, complexities of copyright provisions, the emphasis on "leading edge" technology and research, and the lack of training materials relating to readily understood application are frequently noted obstacles. CEO


Advancing Sustainable Development Goals through Earth Observation Satellite Data: Current Insights and Future Directions


The impact of institutional repositories: a systematic review

Michele Demetres
Diana Delgado
D. Wright

Journal of the Medical Library Association

Abstract: Objective Institutional repositories are platforms for presenting and publicizing scholarly output that might not be suitable to publish in a peer-reviewed journal or that must meet open access requirements. However, there are many challenges associated with their launch and up-keep. The objective of this systematic review was to define the impacts of institutional repositories (IRs) on an academic institution, thus justifying their implementation and/or maintenance. Methods A comprehensive literature search was performed in the following databases: Ovid MEDLINE, Ovid EMBASE, the Cochrane Library (Wiley), ERIC (ProQuest), Web of Science (Core Collection), Scopus (Elsevier), and Library, Information Science & Technology Abstracts (EBSCO). A total of 6,593 citations were screened against predefined inclusion and exclusion criteria. Results Thirteen included studies were divided into 3 areas of impact: citation count, exposure or presence, and administrative impact. Those focusing on citation count (n=5) and exposure or presence (n=7) demonstrated positive impacts of IRs on institutions and researchers. One study focusing on administrative benefit demonstrated the utility of IRs in automated population of ORCID profiles. Conclusion Based on the available literature, IRs appear to have a positive impact on citation count, exposure or presence, and administrative burden. To draw stronger conclusions, more and higher-quality studies are needed.


Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud

Barend Mons
Cameron Neylon
Jan Velterop
Michel Dumontier
Luiz Olavo Bonino da Silva Santos
Mark D. Wilkinson

Abstract: The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation. As support for the Principles has spread, so has the breadth of these interpretations. In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not.


Introducing the FAIR Principles for research software

Michelle Barker
Neil Chue Hong
Daniel S. Katz
Anna‐Lena Lamprecht
Carlos Martínez-Ortiz
Fotis Psomopoulos
Jennifer Harrow
Leyla Jael Castro

Abstract: Research software is a fundamental and vital part of research, yet significant challenges to discoverability, productivity, quality, reproducibility, and sustainability exist. Improving the practice of scholarship is a common goal of the open science, open source, and FAIR (Findable, Accessible, Interoperable and Reusable) communities and research software is now being understood as a type of digital object to which FAIR should be applied. This emergence reflects a maturation of the research community to better understand the crucial role of FAIR research software in maximising research value. The FAIR for Research Software (FAIR4RS) Working Group has adapted the FAIR Guiding Principles to create the FAIR Principles for Research Software (FAIR4RS Principles). The contents and context of the FAIR4RS Principles are summarised here to provide the basis for discussion of their adoption. Examples of implementation by organisations are provided to share information on how to maximise the value of research outputs, and to encourage others to amplify the importance and impact of this work.


Data from: Data reuse and the open data citation advantage


Tracing data: A survey investigating disciplinary differences in data citation

Kathleen Gregory
A. Ninkov
Chantal Ripp
Emma Roblin
I. Peters
Stefanie Haustein

Abstract: Abstract Data citations, or citations in reference lists to data, are increasingly seen as an important means to trace data reuse and incentivize data sharing. Although disciplinary differences in data citation practices have been well documented via scientometric approaches, we do not yet know how representative these practices are within disciplines. Nor do we yet have insight into researchers’ motivations for citing, or not citing, data in their academic work. Here, we present the results of the largest known survey (n = 2,492) to explicitly investigate data citation practices, preferences, and motivations, using a representative sample of academic authors by discipline, as represented in the Web of Science (WoS). We present findings about researchers’ current practices and motivations for reusing and citing data and also examine their preferences for how they would like their own data to be cited. We conclude by discussing disciplinary patterns in two broad clusters, focusing on patterns in the social sciences and humanities, and consider the implications of our results for tracing and rewarding data sharing and reuse.


The scientific data reuse and intellectual property of data sharing in biomedical field

M. Fu
Yanru Li
Meichen Guo
Zongjian Wu
Zhimou Li

International Conference on Bioinformatics and Intelligent Computing

Abstract: With the advancement of data technology, the management and research of scientific datasets have attracted extensive attention. Scientific dataset reuse can maximize the value of scientific datasets through effective development and utilization of scientific data resources. This article focuses on the reuse behaviors of scientific researchers and explores their characteristics and preferences, with a view to providing references for scientific researchers' reuse of datasets as well as scientific research organizations' scientific data management and data services. The article uses bibliometric methods to statistically analyze the reuse behavior of scientific datasets in the Open Access literature of PubMed Central from multiple dimensions and analyzes the citation status of scientific datasets and literature with high frequency of reuse. This study show that the reuse of scientific datasets is common among researchers in the biomedical field, and the citation rate of the literature with dataset reuse is higher than that of the literature without dataset reuse; there is a significant positive correlation between the frequency of dataset reuse and the impact of the papers, which indicates that reusing widely used scientific datasets can not only reduce the burden of data acquisition, but also enlarge the impact of research results to a certain extent. This indicates that reuse of widely used scientific datasets not only reduces the burden of data acquisition, but also expands t


Do open access journal articles experience a citation advantage? Results and methodological reflections of an application of multiple measures to an analysis by WoS subject areas

Abstract: This study is one of the first that uses the recently introduced open access (OA) labels in the Web of Science (WoS) metadata to investigate whether OA articles published in Directory of Open Access Journals (DOAJ) listed journals experience a citation advantage in comparison to subscription journal articles, specifically those of which no self-archived versions are available. Bibliometric data on all articles and reviews indexed in WoS, and published from 2013 to 2015, were analysed. In addition to normalised citation score (NCS), we used two additional measures of citation advantage: whether an article was cited at all; and whether an article is among the most frequently cited percentile of articles within its respective subject area (pptopX %). For each WoS subject area, the strength of the relationship between access status (whether an article was published in an OA journal) and each of these three measures was calculated. We found that OA journal articles experience a citation advantage in very few subject areas and, in most of these subject areas, the citation advantage was found on only a single measure of citation advantage, namely whether the article was cited at all. Our results lead us to conclude that access status accounts for little of the variability in the number of citations an article accumulates. The methodology and the calculations that were used in this study are described in detail and we believe that the lessons we learnt, and the recommendations we mak


Open data: The building block of 21st century (open) science

Abstract:
Abstract
	  This paper identifies the potential benefits of data sharing and open science, supported by artificial intelligence tools and services, and dives into the challenges to make data open and findable, accessible, interoperable, and reusable (FAIR).


Sowing the Seeds of Future Research: Data Sharing, Citation and Reuse in Archaeobotany

Abstract: The practices of data sharing, data citation and data reuse are all crucial aspects of the reproducibility of archaeological research. This article builds on the small number of studies reviewing data sharing and citation practices in archaeology, focussing on the data-rich sub-discipline of archaeobotany. Archaeobotany is a sub-discipline built on the time-intensive collection of data on archaeological plant remains, in order to investigate crop choice, crop husbandry, diet, vegetation and a wide range of other past human-plant relationships. Within archaeobotany, the level and form of data sharing is currently unknown. This article first reviews the form of data shared and the method of data sharing in 239 articles across 16 journals which present primary plant macrofossil studies. Second, it assesses data-citation in meta-analysis studies in 107 articles across 20 journals. Third, it assesses data reuse practices in archaeobotany, before exploring how these research practices can be improved to benefit the rigour and reuse of archaeobotanical research.


Unequal Access, Unequal Impact? The Role of Open Access Policies in Publishing and Citation Trends Across Three Countries

Abstract: This bibliometric study investigates Open Access (OA) publication and citation trends in Austria, Israel, and Mexico from 2010 to 2020, three countries with comparable research output but differing OA infrastructures. (1) Background: The study examines how national OA policies, funding mechanisms, and transformative agreements (TAs) shape publication and citation patterns across disciplines. (2) Methods: Using Scopus data, the analysis focuses on four broad subject areas (health, physical, life, and social sciences), applying both three-way ANOVA and a Weighted OA Citation Impact index that adjusts citation shares based on the proportional representation of each subject area in national research output. An OA Engagement Score was also developed to assess each country’s policy and infrastructure support. (3) Results: OA publications consistently receive more citations than closed-access ones, confirming a robust OA citation advantage. Austria leads in both OA publication volume and weighted impact, reflecting its strong policy frameworks and TA coverage. Israel, while publishing fewer OA articles, achieves high citation visibility in specific disciplines. Mexico demonstrates strengths in repositories and Diamond OA journals but lags in transformative agreements. (4) Conclusions: National differences in OA policy maturity, infrastructure, and publishing models shape both visibility and citation impact. Structural limitations and indexing disparities may further affect how resear


Informal data citation for data sharing and reuse is more common than formal data citation in biomedical fields

Hyoungjoo Park
Sukjin You
Dietmar Wolfram

Abstract: Data citation, where products of research such as data sets, software, and tissue cultures are shared and acknowledged, is becoming more common in the era of Open Science. Currently, the practice of formal data citation, where data references are included alongside bibliographic references in the reference section of a publication, is uncommon. We examine the prevalence of data citation, documenting data sharing and reuse, in a sample of full text articles from the biological/biomedical sciences, the fields with the most public data sets available documented by the Data Citation Index (DCI). We develop a method that combines automated text extraction with human assessment for revealing candidate occurrences of data sharing and reuse by using terms that are most likely to indicate their occurrence. The analysis reveals that informal data citation in the main text of articles is far more common than formal data citations in the references of articles. As a result, data sharers do not receive documented credit for their data contributions in a similar way as authors do for their research articles because informal data citations are not recorded in sources such as the DCI. Ongoing challenges for the study of data citation are also outlined.


The open access advantage considering citation, article usage and social media attention

Xianwen Wang
Chen Liu
Wenli Mao
Zhichao Fang

Abstract: In this study, we compare the difference in the impact between open access (OA) and non-open access (non-OA) articles. 1761 Nature Communications articles published from 1 Jan. 2012 to 31 Aug. 2013 are selected as our research objects, including 587 OA articles and 1174 non-OA articles. Citation data and daily updated article-level metrics data are harvested directly from the platform of nature.com. Data is analyzed from the static versus temporal-dynamic perspectives. The OA citation advantage is confirmed, and the OA advantage is also applicable when extending the comparing from citation to article views and social media attention. More important, we find that OA papers not only have the great advantage of total downloads, but also have the feature of keeping sustained and steady downloads for a long time. For article downloads, non-OA papers only have a short period of attention, when the advantage of OA papers exists for a much longer time.


Reconsidering the gold open access citation advantage postulate in a multidisciplinary context: an analysis of the subject categories in the Web of Science database 2009-2014

P. Dorta-González
S. M. González-Betancor
M. Dorta-González

Abstract: Since Lawrence in 2001 proposed the open access (OA) citation advantage, the potential benefit of OA in relation to citation impact has been discussed in depth. The methodology to test this postulate ranges from comparing the impact factors of OA journals versus traditional ones, to comparing citations of OA versus non-OA articles published in the same non-OA journals. However, conclusions are not entirely consistent among fields, and two possible explications have been suggested in those fields where a citation advantage has been observed for OA: the early view and the selection bias postulates. In this study, a longitudinal and multidisciplinary analysis of gold OA citation advantage is developed. All research articles in all journals for all subject categories in the multidisciplinary database Web of Science are considered. A total of 1,138,392 articles, 60,566 (5.3%) OA articles and 1,077,826 (94.7%) non-OA articles, published in 2009 are analysed. The citation window considered goes from 2009 to 2014, and data are aggregated for the 249 disciplines (subject categories). At journal level, we also study the evolution of journal impact factors for OA and non-OA journals in those disciplines whose OA prevalence is higher (top 36 subject categories). As the main conclusion, there is no generalizable gold OA citation advantage, neither at article nor at journal level.


Sustainability of open access citation advantage: the case of Elsevier’s author-pays hybrid open access journals


Does open access foster interdisciplinary citations? Decomposing open access citation advantage

Abstract:
Abstract
          The existence of an open access (OA) citation advantage, that is, whether OA increases citations, has been a topic of interest for many years. Although numerous studies have focused on whether OA increases citations, expectations for OA go beyond that. One such expectation is the promotion of knowledge transfer across various fields. This study aimed to clarify what effects OA, particularly gold OA, has on knowledge transfer across fields. Specifically, we measure the effect of OA on interdisciplinary and within-discipline citation counts by decomposing an existing OA citation advantage metric. OA increased both interdisciplinary and within-discipline citations in many fields studied, and only interdisciplinary citations in chemistry, computer science, and clinical medicine. In these three fields, clinical medicine showed a tendency toward interdisciplinary citations, independent of journal or paper. These findings suggest that OA fosters knowledge transfer across disciplines.


A Decade of Progress: Insights of Open Data Practices in Biosciences at the University of Edinburgh

Haya Deeb
Hwee Yun Wong
Trisha Usman
Megan A. M. Kutzer
Tomasz Zieliński
Andrew J. Millar

Abstract:
The realm of scientific research has evolved beyond traditional publications, recognizing the intrinsic value of the underlying data as a fundamental component. In this context, Open Data emerges as a pivotal element of open research culture, embodying the principles of transparency, collaboration, and resource optimization. This poster critically analyses the progress and current standing of the University of Edinburgh in embracing and implementing open data practices.
The University of Edinburgh, a vanguard in academic research, has been instrumental in advocating the Culture of Open Data. This paradigm shift in research methodology, accentuated by the introduction of the new open research policy in 2021, has placed a significant emphasis on the openness and FAIRness (Findability, Accessibility, Interoperability, and Reusability) of research data. This poster will explore the strides made by the biosciences researchers over the past ten years in aligning with these principles.
Our analysis begins with a review of biosciences research between 2014 and 2022. Approximately 6% (193 papers) of the published papers during this period were subjected to a manual assessment of their data-sharing practices. Unlike Roche et al. (2013), who sampled from a publication list where each article had some data archived, this study involved selecting articles while being blinded as to whether any data was shared. This evaluation was grounded in four main criteria reflecting the Openness and F


Measuring and Mapping Data Reuse: Findings from an Interactive Workshop on Data Citation and Metrics for Data Reuse

Abstract: Widely-adopted standards for data citation are foundational to efforts to track and quantify data reuse. Without the means to track data reuse and metrics to measure impact, it is difficult to reward researchers who share high-value data with meaningful credit for their contribution. Despite initial work on developing guidelines for data citation and metrics, standards have not yet been universally adopted. This article reports on the recommendations collected from a workshop held at the FORCE11 2018 meeting entitled “Measuring and Mapping Data Reuse: An Interactive Workshop on Metrics for Data.” A range of stakeholders were represented among the participants, including publishers, researchers, funders, repository administrators, librarians, and others. Collectively, they generated a set of 68 recommendations for specific actions that could be taken by standards and metrics creators; publishers; repositories; funders and institutions; software and citation creators; and researchers, students, and librarians. These specific, concrete, and actionable recommendations would help facilitate broader adoption of standard citations mechanisms and easier measurement of data reuse.


The CARE Principles for Indigenous Data Governance

Stephanie Russo Carroll
Ibrahim Garba
Óscar Luis Figueroa Rodríguez
Jarita Holbrook
Raymond Lovett
S. A. Materechera
M. A. Parsons
Kay Raseroka

Abstract: Concerns about secondary use of data and limited opportunities for benefit-sharing have focused attention on the tension that Indigenous communities feel between (1) protecting Indigenous rights and interests in Indigenous data (including traditional knowledges) and (2) supporting open data, machine learning, broad data sharing, and big data initiatives. The International Indigenous Data Sovereignty Interest Group (within the Research Data Alliance) is a network of nation-state based Indigenous data sovereignty networks and individuals that developed the ‘CARE Principles for Indigenous Data Governance’ (Collective Benefit, Authority to Control, Responsibility, and Ethics) in consultation with Indigenous Peoples, scholars, non-profit organizations, and governments. The CARE Principles are people- and purpose-oriented, reflecting the crucial role of data in advancing innovation, governance, and self-determination among Indigenous Peoples. The Principles complement the existing data-centric approach represented in the ‘FAIR Guiding Principles for scientific data management and stewardship’ (Findable, Accessible, Interoperable, Reusable). The CARE Principles build upon earlier work by the Te Mana Raraunga Maori Data Sovereignty Network, US Indigenous Data Sovereignty Network, Maiam nayri Wingara Aboriginal and Torres Strait Islander Data Sovereignty Collective, and numerous Indigenous Peoples, nations, and communities. The goal is that stewards and other users of Indigenous data


Using oaDOI &amp; Crossref event data API to calculate your institution's open access citation advantage

Abstract: As a generalist with hands in many pies, I'm prone to throw around terms I barely understand. API or Application Programming Interface might be one of them.&nbsp; But learning about APIs are important as we are using it whether we know it or not. Recently, I have started to get comfortable with them , at least in terms of pulling out the data and parsing the JSON output.


Challenges and opportunities in open scientific data policy development in the Republic of Moldova

Abstract: Open science initiatives are a global phenomenon. If in developed countries research and innovation enjoy significant support from governments, business and the entire society, and open science has become an important component in the landscape of scientific research, developing countries, such as the Republic of Moldova, have a situation a little more special regarding open access to scientific information, the use of new technologies and tools in the sharing and dissemination of knowledge, in the broad participation and collaboration between social partners in the act of research and innovation. New achievements in the field of information and communication technology offer developing countries great opportunities to increase their research capabilities and participate in the development of world science. There are, however, certain specific barriers that still prevent the free circulation of scientific information, the broad collaboration of actors in the field of research. Ensuring open access to research data is a big challenge for the scientific community in the Republic of Moldova. In order to respond to this challenge, it is necessary to develop and implement some policies and some normative acts that contribute to the consolidation of efforts in order to identify and capitalize on the opportunities offered by new technologies, good practices and European and international experience, the establishment of some sustainable mechanisms regarding management and reuse of r


Policy Framework and Roadmap for Open Access, Open Research Data and Open Science

Digital Presentation and Preservation of Cultural and Scientific Heritage

Abstract: Overview of the growth of policies and a critical appraisal of the issues affecting open access, open data and open science policies. Example policies and a roadmap for open access, open research data and open science are included.


Operationalizing the CARE and FAIR Principles for Indigenous data futures

Stephanie Russo Carroll
Edit Herczog
Māui Hudson
Keith Russell
Shelley Stall

Abstract: As big data, open data, and open science advance to increase access to complex and large datasets for innovation, discovery, and decision-making, Indigenous Peoples’ rights to control and access their data within these data environments remain limited. Operationalizing the FAIR Principles for scientific data with the CARE Principles for Indigenous Data Governance enhances machine actionability and brings people and purpose to the fore to resolve Indigenous Peoples’ rights to and interests in their data across the data lifecycle.


The Open Access Citation Advantage: Quality Advantage Or Quality Bias?

Abstract: Many studies have now reported the positive correlation between Open Access (OA) self-archiving and citation counts ("OA Advantage," OAA). But does this OAA occur because (QB) authors are more likely to self-selectively self-archive articles that are more likely to be cited (self-selection "Quality Bias": QB)? or because (QA) articles that are self-archived are more likely to be cited ("Quality Advantage": QA)? The probable answer is both. Three studies [by (i) Kurtz and co-workers in astrophysics, (ii) Moed in condensed matter physics, and (iii) Davis & Fromerth in mathematics] had reported the OAA to be due to QB [plus Early Advantage, EA, from self-archiving the preprint before publication, in (i) and (ii)] rather than QA. These three fields, however, (1) have less of a postprint access problem than most other fields and (i) and (ii) also happen to be among the minority of fields that (2) make heavy use of prepublication preprints. Chawki Hajjem has now analyzed preliminary evidence based on over 100,000 articles from multiple fields, comparing self-selected self-archiving with mandated self-archiving to estimate the contributions of QB and QA to the OAA. Both factors contri


Do open access articles have a citation advantage?, a research based on European Urology Family

Jincong Li
Shuangying Zhang
Ruimeng Yue
Chengxiang Tian
Yuyao Jian
Rui-Zhong Chen
Yang Liu
Yun Peng

Abstract: Background: Open access (OA), referring to the practice of providing unrestricted access to scholarly research outputs, has become a main publishing choice for authors. Previous studies have reported OA articles had a citation advantage compared to non-OA articles. Thus, this research aimed to further explore the impact of OA on article citations.Methods: We searched the Web of Science for research articles and reviews published in European Urology and its sub-journals in 2021. After data extraction, IBM SPSS Statistics 26 was used for statistical analysis, and binary logistic regression analysis was conducted to examine the influence of different variables, particularly OA, on article citation counts.Results: The study included 135 articles from European Urology, 183 articles from European Urology Focus, and 101 articles from European Urology Oncology. The analysis revealed a significant positive effect of OA on article citations in European Urology (OR = 0.391, 95%CI = 0.189-0.810, p = 0.011). However, OA did not have a statistically significant impact on article citations in European Urology Focus (p = 0.847) or European Urology Oncology (p = 0.83).Conclusion: Our analysis suggests OA significantly boosts citations in high-impact journals, but shows minimal effect in lower-impact venues.


Rethinking the open access citation advantage: Evidence from the “reverse‐flipping” journals

Abstract: Although the open access citation advantage (OACA) has been discussed extensively, scholars lack a clear understanding of the mechanisms through which switching from subscription‐based model to open access (OA) model affects the citation impact of a scholarly journal. Many journals have switched from subscription to OA, yet they later also flipped their preswitching articles (i.e., those under subscription model) to OA, thus leaving no subscription article to be compared with their postswitching OA counterparts. To detect the switching effect, our study instead focused on 60 journals that “reverse flipped” from OA to subscription. We use a difference‐in‐difference (DiD) analytical framework to analyze two propositions related to OACA, based on the bibliographic and citation data of pre‐ and postswitching publications in these journals. Our findings indicate that reverse flipping is unlikely to affect the journals' impact through changing the visibility of their articles. Instead, it could lead to a systematical shift in the submissions to the journals and thus considerably affect their impact. Our findings have important theoretical and practical implications for subsequent studies, funding agencies, and scholarly journals considering a reverse flip.


Confirmation Bias and the Open Access Advantage: Some Methodological Suggestions for the Davis Citation Study

Abstract: Davis (2008) analyzes citations from 2004-2007 in 11 biomedical journals. 15% of authors paid to make them Open Access (OA). The outcome is a significant OA citation Advantage, but a small one (21%). The author infers that the OA advantage has been shrinking yearly, but the data suggest the opposite. Further analyses are necessary: (1) Not just author-choice (paid) OA but Free OA self-archiving needs to be taken into account rather than being counted as non-OA. (2) proportion of OA articles per journal per year needs to be reported and taken into account. (3) The Journal Impact Factor and the relation between the size of the OA Advantage article 'citation-bracket' need to be taken into account. (4) The sample-size for the highest-impact, largest-sample journal analyzed, PNAS, is restricted and excluded from some of the analyses. The full PNAS dataset is needed. (5) The interaction between OA and time, 2004-2007, is based on retrospective data from a June 2008 total cumulative citation count. The dates of both the cited articles and the citing articles need to be taken into account. The author proposes that author self-selection bias for is the primary cause of the observed OA Advan


Does open access citation advantage depend on paper topics?

Abstract: Research topics vary in their citation potential. In a metric-wise scientific milieu, it would be probable that authors tend to select citation-attractive topics especially when choosing open access (OA) outlets that are more likely to attract citations. Applying a matched-pairs study design, this research aims to examine the role of research topics in the citation advantage of OA papers. Using a comparative citation analysis method, it investigates a sample of papers published in 47 Elsevier article processing charges (APC)-funded journals in different access models including non-open access (NOA), APC, Green and mixed Green-APC. The contents of the papers are analysed using natural language processing techniques at the title and abstract level and served as a basis to match the NOA papers to their peers in the OA models. The publication years and journals are controlled for in order to avoid their impacts on the citation numbers. According to the results, the OA citation advantage that is observed in the whole sample still holds even for the highly similar OA and NOA papers. This implies that the OA citation surplus is not an artefact of the OA and NOA papers’ differences in their topics and, therefore, in their citation potential. This leads to the conclusion that OA authors’ self-selectivity, if it exists at all, is not responsible for the OA citation advantage, at least as far as selection of topics with probably higher citation potentials is concerned.


Do Open Access Articles Have a Citation Advantage Over Toll Access Articles? A Comparative Analysis of Articles Published in the Journal of Craniofacial Surgery From 2019 to 2023 Based on Web of Science Data

Ş. Şahin
Y. M. Durna
Y. Duymaz
İlhan Bahsi

The Journal of craniofacial surgery (Print)

Abstract: Objective: This study aimed to compare the citation rates of open access (OA), and toll access (TA) articles published in the Journal of Craniofacial Surgery between 2019 and 2023, and to examine whether OA articles received more citations. Methods: Using the Web of Science database, articles published in the Journal of Craniofacial Surgery between 2019 and 2023 were listed, excluding those with corrections or retractions. Articles were divided into 2 groups: OA and TA. The number of articles and citation counts for each group were analyzed by year. Citation rates were compared using the independent sample t test, with a p-value of <0.05 considered statistically significant. Results: A total of 4691 articles were analyzed, of which 7.14% were OA and 92.86% were TA. Published in 2021, 2020, and 2019, OA articles had statistically significantly higher citation counts than TA articles. OA articles were found to be funded at a higher rate than TA articles. Conclusion: This study demonstrated that OA articles received more citations over time and were more likely to be funded. Although it is not definitively clear whether the citation advantage stems from the quality of the articles or their open-access status, the citation advantage of OA articles is striking.


Open Access Citation Advantage: An Annotated Bibliography.

Issues in Science and Technology Librarianship

Abstract: A bibliography on the subject of citations in open access (OA) articles is presented, including the study "Open Access to Scientific Literature: Increasing Citations As An Incentive for Authors to Make Their Publications Freely Accessible," by S. Bernius and M. Hanauske, and the articles "Earlier Web Usage Statistics As Predictors of Later Citation Impact," by T. Brody, S. Harnad, and L. Carr, and "Evolution of Open Access Publishing in Chinese Scientific Journals."


The citation advantage of open‐access articles

Michael Norris
Charles Oppenheim
Fytton Rowland

Journal of the American Society for Information Science and Technology

Abstract: Abstract Four subjects, ecology, applied mathematics, sociology, and economics, were selected to assess whether there is a citation advantage between journal articles that have an open‐access (OA) version on the Internet compared to those articles that are exclusively toll access (TA). Citations were counted using the Web of Science, and the OA status of articles was determined by searching OAIster, OpenDOAR, Google, and Google Scholar. Of a sample of 4,633 articles examined, 2,280 (49%) were OA and had a mean citation count of 9.04 whereas the mean for TA articles was 5.76. There appears to be a clear citation advantage for those articles that are OA as opposed to those that are TA. This advantage, however, varies between disciplines, with sociology having the highest citation advantage, but the lowest number of OA articles, from the sample taken, and ecology having the highest individual citation count for OA articles, but the smallest citation advantage. Tests of correlation or association between OA status and a number of variables were generally found to weak or inconsistent. The cause of this citation advantage has not been determined.


The Open Access Citation Advantage: Does It Exist and What Does It Mean for Libraries?

Abstract: The last literature review of research on the existence of an Open Access Citation Advantage (OACA) was published in 2011 by Philip M. Davis and William H. Walters. This paper reexamines the conclusions reached by Davis and Walters by providing a critical review of OACA literature that has been published 2011, and explores how increases in OA publication trends could serve as a leveraging tool for libraries against the high costs of journal subscriptions.


The influence of funding on the Open Access citation advantage

Pablo Dorta-González
María Isabel Dorta-González

Abstract: Some of the citation advantage in open access is likely due to more access allows more people to read and hence cite articles they otherwise would not. However, causation is difficult to establish and there are many possible bias. Several factors can affect the observed differences in citation rates. Funder mandates can be one of them. Funders are likely to have OA requirement, and well-funded studies are more likely to receive more citations than poorly funded studies. In this paper this hypothesis is tested. Thus, we studied the effect of funding on the publication modality and the citations received in more than 128 thousand research articles, of which 31% were funded. These research articles come from 40 randomly selected subject categories in the year 2016, and the citations received from the period 2016-2020 in the Scopus database. We found open articles published in hybrid journals were considerably more cited than those in open access journals. Thus, articles under the hybrid gold modality are cite on average twice as those in the gold modality. This is the case regardless of funding, so this evidence is strong. Moreover, within the same publication modality, we found that


The Post-Embargo Open Access Citation Advantage: It Exists (Probably), It’s Modest (Usually), and the Rich Get Richer (of Course)

Abstract: Many studies show that open access (OA) articles-articles from scholarly journals made freely available to readers without requiring subscription fees-are downloaded, and presumably read, more often than closed access/subscription-only articles. Assertions that OA articles are also cited more often generate more controversy. Confounding factors (authors may self-select only the best articles to make OA; absence of an appropriate control group of non-OA articles with which to compare citation figures; conflation of pre-publication vs. published/publisher versions of articles, etc.) make demonstrating a real citation difference difficult. This study addresses those factors and shows that an open access citation advantage as high as 19% exists, even when articles are embargoed during some or all of their prime citation years. Not surprisingly, better (defined as above median) articles gain more when made OA.


Analysis on open access citation advantage

Abstract: This study takes 12,354 original research articles which were published in 93 Oxford Open journals in 2009 as a sample, and carries out statistic analyses on the citation frequency that these articles have received by July 2010 to validate 3 hypotheses: (1) there is citation advantage for open access articles(OACA) published in Oxford Open journals over the non-OA ones; (2) OACA varies with disciplines; (3) there is some correlation between the impact factors(IFs) of Oxford Open journals and the OACA of their open access articles. This study discovers that: there exists OACA for open access articles, in this case 138.87% higher over non-OA ones; different subjects have different OACAs, and Humanities journals in Oxford Open have even a negative OACA; Oxford Open journals with lower IFs have stronger OACAs than those with higher IFs.


Prevalence and citation advantage of gold open access in the subject areas of the Scopus database

Pablo Dorta-González
Yolanda Santana-Jiménez

Abstract: The potential benefit of open access (OA) in relation to citation impact has been discussed in the literature in depth. The methodology used to test the OA citation advantage includes comparing OA vs. non-OA journal impact factors and citations of OA versus non-OA articles published in the same non-OA journals. However, one problem with many studies is that they are small -restricted to a discipline or set of journals-. Moreover, conclusions are not entirely consistent among research areas and 'early view' and 'selection bias' have been suggested as possible explications. In the present paper, an analysis of gold OA from across all areas of research -the 27 subject areas of the Scopus database- is realized. As a novel contribution, this paper takes a journal-level approach to assessing the OA citation advantage, whereas many others take a paper-level approach. Data were obtained from Scimago Lab, sorted using Scopus database, and tagged as OA/non-OA using the DOAJ list. Jointly with the OA citation advantage, the OA prevalence as well as the differences between access types (OA vs. non-OA) in production and referencing are tested. A total of 3,737 OA journals (16.8%) and 18,485 non


Abstract: The potential benefit of open access (OA) in relation to citation impact has been discussed in the literature in depth. The methodology used to test the OA citation advantage includes comparing OA vs. non-OA journal impact factors and citations of OA versus non-OA articles published in the same non-OA journals. However, one problem with many studies is that they are small -restricted to a discipline or set of journals-. Moreover, conclusions are not entirely consistent among research areas and 'early view' and 'selection bias' have been suggested as possible explications. In the present paper, an analysis of gold OA from across all areas of research -the 27 subject areas of the Scopus database- is realized. As a novel contribution, this paper takes a journal-level approach to assessing the OA citation advantage, whereas many others take a paper-level approach. Data were obtained from Scimago Lab, sorted using Scopus database, and tagged as OA/non-OA using the DOAJ list. Jointly with the OA citation advantage, the OA prevalence as well as the differences between access types (OA vs. non-OA) in production and referencing are tested. A total of 3,737 OA journals (16.8%) and 18,485 non-OA journals (83.2%) published in 2015 are considered. As the main conclusion, there is no generalizable gold OA citation advantage at journal level.


The impact of free access to the scientific literature: a review of recent research.

Abstract:
OBJECTIVES
The paper reviews recent studies that evaluate the impact of free access (open access) on the behavior of scientists as authors, readers, and citers in developed and developing nations. It also examines the extent to which the biomedical literature is used by the general public.

METHOD
The paper is a critical review of the literature, with systematic description of key studies.

RESULTS
Researchers report that their access to the scientific literature is generally good and improving. For authors, the access status of a journal is not an important consideration when deciding where to publish. There is clear evidence that free access increases the number of article downloads, although its impact on article citations is not clear. Recent studies indicate that large citation advantages are simply artifacts of the failure to adequately control for confounding variables. The effect of free access on the general public's use of the primary medical literature has not been thoroughly evaluated.

CONCLUSIONS
Recent studies provide little evidence to support the idea that there is a crisis in access to the scholarly literature. Further research is needed to investigate whether free access is making a difference in non-research contexts and to better understand the dissemination of scientific literature through peer-to-peer networks and other informal mechanisms.


Open-access publishing: citation advantage is unproven


The Open Access citation advantage: Studies and results to date

ePrints Soton (University of Southampton)

Abstract: This paper presents a summary of reported studies on the Open Access citation advantage. There is a brief introduction to the main issues involved in carrying out such studies, both methodological and interpretive. The study listing provides some details of the coverage, methodological approach and main conclusions of each study.


A scientometric review of health data sharing for secondary use: Insights, frontiers and the path ahead.

M. Krahe
Rebekah Eden
Jason D. Pole
Bernadette Richards
Quita Olsen
Amalie Dyda
Elton H. Lobo
N. Pather

Health information management : journal of the Health Information Management Association of Australia

Abstract:
BACKGROUND
As digital technologies advance, vast amounts of routinely collected health data are increasingly available for quality improvement and research. However, concerns persist around the reuse of personal health information. Understanding public attitudes and knowledge is essential to building social licence and enabling ethical, large-scale data use.

OBJECTIVE
This study explores key research themes in sharing health data for secondary use since 2020, highlighting major topics, emerging research frontiers and future directions for practice.

METHOD
An analysis of 95 publications from Web of Science, PubMed and Scopus was conducted using scientometric methods. Citation, co-citation and keyword co-occurrence analyses, along with strategic diagrams, were performed using VOSviewer to identify thematic clusters.

RESULTS
Research has shifted from early exploratory studies to more multidisciplinary and technology-focused approaches. Key themes include digital tool adoption, integrated data systems and ethical data sharing solutions. The concept of consent has seen the most theoretical development, while public attitudes - particularly around ethical and sociocultural issues - remain underexplored but crucial.

CONCLUSION
Ethical governance, transparency and community engagement are central to advancing health data sharing. Building public trust and securing a social licence are foundational to success, especially as challenges around consent, data linkage and public pe


Policy shaping the impact of open-access publications: a longitudinal assessment


A data citation roadmap for scientific publishers

Helena Cousijn
Amye Kenall
Emma Ganley
Melissa Harrison
David Kernohan
Thomas Lemberger
Fiona Murphy
Patrick Polischuk

Abstract: This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP), a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE program. The structure of the roadmap presented here follows the "life of a paper" workflow and includes the categories Pre-submission, Submission, Production, and Publication. The roadmap is intended to be publisher-agnostic so that all publishers can use this as a starting point when implementing JDDCP-compliant data citation. Authors reading this roadmap will also better know what to expect from publishers and how to enable their own data citations to gain maximum impact, as well as complying with what will become increasingly common funder mandates on data transparency.


The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index

Abstract: The growth rate of scientific publication has been studied from 1907 to 2007 using available data from a number of literature databases, including Science Citation Index (SCI) and Social Sciences Citation Index (SSCI). Traditional scientific publishing, that is publication in peer-reviewed journals, is still increasing although there are big differences between fields. There are no indications that the growth rate has decreased in the last 50 years. At the same time publication using new channels, for example conference proceedings, open archives and home pages, is growing fast. The growth rate for SCI up to 2007 is smaller than for comparable databases. This means that SCI was covering a decreasing part of the traditional scientific literature. There are also clear indications that the coverage by SCI is especially low in some of the scientific areas with the highest growth rate, including computer science and engineering sciences. The role of conference proceedings, open access archives and publications published on the net is increasing, especially in scientific fields with high growth rates, but this has only partially been reflected in the databases. The new publication channels challenge the use of the big databases in measurements of scientific productivity or output and of the growth rate of science. Because of the declining coverage and this challenge it is problematic that SCI has been used and is used as the dominant source for science indicators based on publicati


The bibliometric analysis of scholarly production: How great is the impact?

Abstract: Bibliometric methods or "analysis" are now firmly established as scientific specialties and are an integral part of research evaluation methodology especially within the scientific and applied fields. The methods are used increasingly when studying various aspects of science and also in the way institutions and universities are ranked worldwide. A sufficient number of studies have been completed, and with the resulting literature, it is now possible to analyse the bibliometric method by using its own methodology. The bibliometric literature in this study, which was extracted from Web of Science, is divided into two parts using a method comparable to the method of Jonkers et al. (Characteristics of bibliometrics articles in library and information sciences (LIS) and other journals, pp. 449-551, 2012: The publications either lie within the Information and Library Science (ILS) category or within the non-ILS category which includes more applied, "subject" based studies. The impact in the different groupings is judged by means of citation analysis using normalized data and an almost linear increase can be observed from 1994 onwards in the non-ILS category. The implication for the dissemination and use of the bibliometric methods in the different contexts is discussed. A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact. A noticeable shift is observed in those countries which


Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies

Jeroen Baas
Michiel Schotten
Andrew Plume
Grégoire Côté
Reza Karimi

Abstract: Scopus is among the largest curated abstract and citation databases, with a wide global and regional coverage of scientific journals, conference proceedings, and books, while ensuring only the highest quality data are indexed through rigorous content selection and re-evaluation by an independent Content Selection and Advisory Board. Additionally, extensive quality assurance processes continuously monitor and improve all data elements in Scopus. Besides enriched metadata records of scientific articles, Scopus offers comprehensive author and institution profiles, obtained from advanced profiling algorithms and manual curation, ensuring high precision and recall. The trustworthiness of Scopus has led to its use as bibliometric data source for large-scale analyses in research assessments, research landscape studies, science policy evaluations, and university rankings. Scopus data have been offered for free for selected studies by the academic research community, such as through application programming interfaces, which have led to many publications employing Scopus data to investigate topics such as researcher mobility, network visualizations, and spatial bibliometrics. In June 2019, the International Center for the Study of Research was launched, with an advisory board consisting of bibliometricians, aiming to work with the scientometric research community and offering a virtual laboratory where researchers will be able to utilize Scopus data.


Impact of open access on academic visibility: a systematic review of the literature

Abstract:
 This study systematically reviews the impact of open access (OA) on academic visibility, focusing on how different OA models affect citations, altmetrics, downloads and page views. It aims to clarify whether OA provides a consistent visibility advantage and under which disciplinary, geographic and methodological conditions it emerges.

 A systematic search of the Web of Science (WoS) Core Collection was conducted on March 15, 2025, identifying 157 records. After screening and eligibility assessment, 45 peer-reviewed articles published between 2006 and 2024 were included. Data analysis combined descriptive statistics with bibliometric methods using Microsoft Excel and R Bibliometrix (Biblioshiny). Trends in publications, journals and authors were examined alongside international collaboration networks, keyword co-occurrence maps and temporal keyword evolution. A structured synthesis table summarized study characteristics, methodologies and findings.

 The evidence shows that OA enhances academic visibility but in a heterogeneous manner. Green OA and preprints consistently increase citations and accelerate readership, while Gold OA produces mixed outcomes: positive in medicine and biology, but neutral or negative in economics, library science, and translation studies. Altmetrics highlight OA's broader societal impact, especially in the humanities and social sciences, where freely available works attract attention from social media, blogs and policy documents. Inte


Achieving human and machine accessibility of cited data in scholarly publications

Joan Starr
Eleni Castro
Mercè Crosas
Michel Dumontier
Robert R. Downs
Ruth Duerr
Haak Laurel
Melissa Haendel

Abstract: Reproducibility and reusability of research results is an important concern in scientific communication and science policy. A foundational element of reproducibility and reusability is the open and persistently available presentation of research data. However, many common approaches for primary data publication in use today do not achieve sufficient long-term robustness, openness, accessibility or uniformity. Nor do they permit comprehensive exploitation by modern Web technologies. This has led to several authoritative studies recommending uniform direct citation of data archived in persistent repositories. Data are to be considered as first-class scholarly objects, and treated similarly in many ways to cited and archived scientific and scholarly literature. Here we briefly review the most current and widely agreed set of principle-based recommendations for scholarly data citation, the Joint Declaration of Data Citation Principles (JDDCP). We then present a framework for operationalizing the JDDCP; and a set of initial recommendations on identifier schemes, identifier resolution behavior, required metadata elements, and best practices for realizing programmatic machine actionability of cited data. The main target audience for the common implementation guidelines in this article consists of publishers, scholarly organizations, and persistent data repositories, including technical staff members in these organizations. But ordinary researchers can also benefit from these recomme


Assessing the Needs of NASA's Near Real-Time Earth Observation Products

Abstract: "The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers w


Revisiting event study designs: robust and efficient estimation

Kirill Borusyak
Xavier Jaravel
Jann Spiess
Alberto Abadie
Isaiah Andrews
Raj Chetty
Itzik Fadlon
Ed Glaeser

Abstract: We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects.We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent strong restrictions on treatmenteffect homogeneity.We then derive the efficient estimator addressing this challenge, which takes an intuitive "imputation" form when treatment-effect heterogeneity is unrestricted.We characterize the asymptotic behavior of the estimator, propose tools for inference, and develop tests for identifying assumptions.Extensions include time-varying controls, triple-differences, and certain non-binary treatments.We show the practical relevance of these insights in a simulation study and an application.Studying the consumption response to tax rebates in the United States, we find that the notional marginal propensity to consume is between 8 and 11 percent in the first quarter -about half as large as benchmark estimates used to calibrate macroeconomic models -and predominantly occurs in the first month after the rebate.