Find research datasets worth reusing

opencc-by-4.0Jan 2024View details →

Video 3 - Open Science: a better return on investment.

An interview with Roberto Sabatino, Research Engagement Officer at HEAnet, Dublin Ireland; Nadia Tonello, Data Management Manager at the Barcelona Supercomputing Centre; and Eva Mendes, PhD in Library and Information Science on the potential of Open Science to enhance humanity’s ability to respond to crises and to provide a better return on investment. Science is increasingly collaborative, and this includes sharing data. Funding needs to include data management, sharing, and infrastructure. Increased interoperability in research can help humanity collaboratively face challenges such as climate change. The response to the Covid-19 pandemic was also facilitated by data sharing, showing the positive societal impact and net benefit of Open Science.

opencc-by-4.0Mar 2024View details →

GAPs Data Repository on Return: Guideline, Data Samples and Codebook

The GAPs Data Repository provides a comprehensive overview of available qualitative and quantitative data on national return regimes, now accessible through an advanced web interface at <a href="https://data.returnmigration.eu/" target="_new">https://data.returnmigration.eu/</a>. This updated guideline outlines the complete process, starting from the initial data collection for the return migration data repository to the development of a comprehensive web-based platform. Through iterative development, participatory approaches, and rigorous quality checks, we have ensured a systematic representation of return migration data at both national and comparative levels. The Repository organizes data into five main categories, covering diverse aspects and offering a holistic view of return regimes: country profiles, legislation, infrastructure, international cooperation, and descriptive statistics. These categories, further divided into subcategories, are based on insights from a literature review, existing datasets, and empirical data collection from 14 countries. The selection of categories prioritizes relevance for understanding return and readmission policies and practices, data accessibility, reliability, clarity, and comparability. Raw data is meticulously collected by the national experts. The transition to a web-based interface builds upon the Repository’s original structure, which was initially developed using REDCap (Research Electronic Data Capture). It  is a secure web application for building and managing online surveys and databases.The REDCAP ensures systematic data entries and store them on Uppsala University’s servers while significantly improving accessibility and usability as well as data security. It also enables users to export any or all data from the Project when granted full data export privileges. Data can be exported in various ways and formats, including Microsoft Excel, SAS, Stata, R, or SPSS for analysis. At this stage, the Data Repository design team also converted tailored records of available data into public reports accessible to anyone with a unique URL, without the need to log in to REDCap or obtain permission to access the GAPs Project Data Repository. Public reports can be used to share information with stakeholders or external partners without granting them access to the Project or requiring them to set up a personal account. Currently, all public report links inserted in this report are also available on the Repository’s webpage, allowing users to export original data.     This report also includes a detailed codebook to help users understand the structure, variables, and methodologies used in data collection and organization. This addition ensures transparency and provides a comprehensive framework for researchers and practitioners to effectively interpret the data. The GAPs Data Repository is committed to providing accessible, well-organized, and reliable data by moving to a centralized web platform and incorporating advanced visuals. This Repository aims to contribute inputs for research, policy analysis, and evidence-based decision-making in the return and readmission field. Explore the GAPs Data Repository at <a href="https://data.returnmigration.eu/" target="_new">https://data.returnmigration.eu/</a>.

Who's Who of American Returned Students 遊美同學錄 (1917): Kinship Data

Who's Who of American Returned Students 遊美同學錄 (1917): Affiliation Data (Chinese)

This dataset is derived from the Whoʻs Who of American Returned Students 遊美同學錄 [Youmei Tongxue Lu] published in Peking [Beijing] in 1917, compiled by the Returned Students’ Information Bureau (Liumei xuesheng tongxunchu 留美學生通訊處) established at Tsinghua School in 1915. This book is crucial for documenting the early liumei's experiences during the transitional period between the late Qing dynasty and the early years of the Republic (1911-).   The dataset records all the institutions to which the students were affiliated in the course of their lives, including the educational institutions in which they studied in China, the United States, and other countries; the public or private organizations in which they were employed; as well as their memberships in clubs and associations. The names of organizations were retrieved automatically from the Chinese biographies using <a href="https://bookdown.enpchina.eu/rpackage/HistTextRManual.html#4_Named_Entity_Recognition">named entity recognition</a> (SpaCy model), then manually cleaned, classified, and validated by the author.  The attached file contains three tabs for (1) the list of affiliations (data); (2) the classification of organizations (class), and (3) the description of variables (key). The dataset records a total of 2,883 affiliations, linking 401 unique individuals to 1,344 unique institutions, distributed as followed:  <table> <tbody> <tr> <td>category</td> <td>n</td> </tr> <tr> <td>education</td> <td>565</td> </tr> <tr> <td>association</td> <td>271</td> </tr> <tr> <td>administration</td> <td>132</td> </tr> <tr> <td>business</td> <td>110</td> </tr> <tr> <td>facility</td> <td>92</td> </tr> <tr> <td>media</td> <td>66</td> </tr> <tr> <td>government</td> <td>49</td> </tr> <tr> <td>factory</td> <td>30</td> </tr> <tr> <td>other</td> <td>22</td> </tr> <tr> <td>military</td> <td>7</td> </tr> </tbody> </table>

Who's Who of American Returned Students 遊美同學錄 (1917): Affiliation Data (English)

This dataset is derived from the Whoʻs Who of American Returned Students 遊美同學錄 [Youmei Tongxue Lu] published in Peking [Beijing] in 1917, compiled by the Returned Students’ Information Bureau (Liumei xuesheng tongxunchu 留美學生通訊處) established at Tsinghua School in 1915. This book is crucial for documenting the early liumei's experiences during the transitional period between the late Qing dynasty and the early years of the Republic (1911-).   The dataset records all the institutions to which the students were affiliated in the course of their lives, including the educational institutions in which they studied in China, the United States, and other countries; the public or private organizations in which they were employed; as well as their memberships in clubs and associations. The names of organizations were retrieved automatically using <a href="https://bookdown.enpchina.eu/rpackage/HistTextRManual.html#4_Named_Entity_Recognition">named entity recognition</a> (SpaCy model), then manually cleaned, classified, and validated by the author.  The attached file contains three tabs for (1) the list of affiliations (data), (2) the classification of institutions (class); (3) the description of variables (key). The dataset records a total of 3,431 affiliations, linking 401 unique individuals to 1,305 unique institutions, distributed as followed:  <table> <tbody> <tr> <td>category_main</td> <td>n</td> </tr> <tr> <td>education</td> <td>535</td> </tr> <tr> <td>association</td> <td>255</td> </tr> <tr> <td>media</td> <td>108</td> </tr> <tr> <td>administration</td> <td>92</td> </tr> <tr> <td>business</td> <td>85</td> </tr> <tr> <td>facility</td> <td>47</td> </tr> <tr> <td>executive</td> <td>43</td> </tr> <tr> <td>railway</td> <td>39</td> </tr> <tr> <td>production</td> <td>33</td> </tr> <tr> <td>banking</td> <td>15</td> </tr> <tr> <td>other</td> <td>15</td> </tr> <tr> <td>event</td> <td>13</td> </tr> <tr> <td>military</td> <td>13</td> </tr> <tr> <td>judiciary</td> <td>8</td> </tr> <tr> <td>legislative</td> <td>4</td> </tr> </tbody> </table>

Who's Who of American Returned Students 遊美同學錄 (1917): Vital Data

opencc-by-4.0Oct 2022View details →

Diminishing returns on labor in the global marine food system: Dataset S1 and code for analysis

Dataset on the number of marine fishers 1950-2015 accompanying the manuscript "Diminishing returns on labor in the global marine food system" by K. J. N. Scherrer, Y. Rousseau, L. C. L. Teh, U. R. Sumaila and E. D. Galbraith. Includes 1) script for data analysis, 2) processed fisheries labor data set, 3) separate data file with average socioeconomic indicators by country needed for analysis, 4) data documentation.

edi44/100

Peeking under the canopy: anomalously short fire-return intervals alter subalpine forest understory plant communities

Changing climate and fire regimes are profoundly affecting temperate coniferous forests, driving greatly reduced tree cover postfire. However, whether similar changes are present in the understory of these forests remains less well-understood. We sampled understory plant communities in 20 plot pairs across Greater Yellowstone (Wyoming, USA) in July and August 2021, with each including one plot burned at short (<30 year) fire-return interval and one plot burned in the same most recent fire but not burned previously for >125 years. We also included 11 plot pairs meeting our definition of short- and long-interval fire that were sampled 12 years after the 1988 Yellowstone fires in summer 2000. We also used previously collected published and unpublished data to compare understory communities following recent (2016) short-interval fires to those following the previous long-interval fire in the same general area. In each plot, percent cover of understory plant species was estimated in 0.25-m2 quadrats, and species richness determined via a whole-plot sweep. Understory plant community cover, richness, and diversity did not differ by interval class, but species able to persist in drier conditions and in lower vegetation zones became more abundant following shot interval fire. Further, previously distinct understory communities following long-interval fire in two regions of Greater Yellowstone became slightly more similar following recent short-interval fire. Dissimilarity between plot pairs increased with greater historical snowfall and decreased with time since fire and postfire winter snowfall. These changes to understory plant communities may continue with ongoing shifts in climate and fire across temperate and boreal forests.

openCC (other)May 2023View details →

edi44/100

Return on Investment Metrics for Data Repositories in Earth and Environmental Sciences

Despite a growing recognition of the importance of data to the economy and to science, investment in repositories to manage and disseminate that data in easily accessible and understandable ways is scarce. Keeping repository services active and up-to-date for a long time period is difficult due to this funding situation. As a result, repositories must continually provide proof of their value, their Return on Investment (ROI) to their sponsors; yet doing so has always been difficult, problematic and not always successful. In this work, an analysis of approaches for assessing the ROI of several scientific data repositories has identified various techniques that repositories use to report on the impact and value of their data products and services. A survey of selected repositories rated the set of metrics identified and rated each by its importance as well as the ease with which the metric could be measured. The discussion is broken down into considerations for calculating costs, perceived value of repositories and suggested metrics that would allow a repository to calculate an ROI. The authors, representatives of environmental data repositories, concluded that easily obtainable data use metrics, such as data downloads, etc., have limited value while more informative analyses would require additional resources.

openCC (other)Feb 2019View details →

opencc-by-4.0Nov 2020View details →

BDRC Returned Students Network Data

These two files correspond to the edge list and the node list used to build the network of returned students in the Biographical Dictionary of Republican China (BDRC).

opencc-zeroSep 2016View details →

Further analysis by ContentMine of OA Papers Returned by Querying EuropePMC with 'zika'

Facts and metadata extracted from papers returned from querying EuropePMC with the phrase 'zika' using the ContentMine Cambridge pipeline. With dictionaries available at https://github.com/contentmine/dictionaries. Query and dictionaries used as of 2016-09-19. This dataset contains metadata and facts from 524 papers. A large number of the terms in the dictionaries used now contain wikidata IDs. Canary Version: 2ab2e9e7d95c2d6f81636739f383e52543befeff Dictionaries Version: 2498cf1bae660ae44437bcba388ef8436cc8554c

opencc-by-4.0Oct 2023View details →

Dataset: Maurel et al. "Hayabusa 2 returned samples reveal a weak to null magnetic field during aqueous alteration of Ryugu's parent body"

Samples: C0005 and A0154a from asteroid Ryugu (JAXA Hayabusa 2 mission), CI chondrite Orgueil, CM2 chondrite Daoura 003 <ul> <li>C0005: NRM, ARM, IRM demagnetization and anisotropy of ARM (AARM), IRM acquisition</li> <li>A0154a: NRM demagnetization, AARM</li> <li>Orgueil: NRM and ARM demagnetization</li> <li>Daoura 003: NRM demagnetization</li> </ul>

opencc-by-4.0Jan 2022View details →

Absence of neocytolysis in humans returning from a 3-week high-altitude sojourn

This dataset refers to the article "Absence of neocytolysis in humans returning from a 3-week high-altitude sojourn" Acta Physiologica. 2021;232:e13647  https://doi.org/10.1111/apha.13647

opencc-by-4.0Dec 2021View details →

The Return of the Templates: Revisiting the Galactic Center Excess with Multi-Messenger Observations

We provide here the galactic diffuse emission maps used in "The Return of the Templates: Revisiting the Galactic Center Excess with Multi-Messenger Observations".

opencc-by-4.0Sep 2022View details →

Investigation on Dynamic Characteristics of Lightning Return Stroke Channel

The dynamic characteristics in lightning discharge plasma channel are of great significance in studying the micro-physical mechanism of the discharge process. This paper established a simplified radiation-hydrodynamic model (RHM) of the return stroke channel radial expansion based on the fluid dynamics theory, and for the first time, considered the affect of the light radiation loss in the discharge process. The temporal evolutions of the characteristic parameters, such as temperature, pressure and expansion rate for return stroke channel were analyzed. The results indicated that the current peak value and the risetime are important factors in determining the  channel dynamics characteristics. At the initial stage of return stroke, the light radiation loss has a distinct influence on channel temperature, which leads to a transitory drop in temperature forming a bimodal waveform structure. Following the peak current, the channel reaches peak pressure, which leads to a subsequent  secondary temperature peak and accelerates the expansion of the channel. Peak current and the risetime are the indicator parameters of strong discharge and the main factors of lightning disaster. This work provides reference data for further research on the radial energy transport of lightning return stroke channel and the formation mechanism of shock waves.The dynamic characteristics in lightning discharge plasma channel are of great significance in studying the micro-physical mechanism of the discharge process. This paper established a simplified radiation-hydrodynamic model (RHM) of the return stroke channel radial expansion based on the fluid dynamics theory, and for the first time, considered the affect of the light radiation loss in the discharge process. The temporal evolutions of the characteristic parameters, such as temperature, pressure and expansion rate for return stroke channel were analyzed. The results indicated that the current peak value and the risetime are important factors in determining the  channel dynamics characteristics. At the initial stage of return stroke, the light radiation loss has a distinct influence on channel temperature, which leads to a transitory drop in temperature forming a bimodal waveform structure. Following the peak current, the channel reaches peak pressure, which leads to a subsequent  secondary temperature peak and accelerates the expansion of the channel. Peak current and the risetime are the indicator parameters of strong discharge and the main factors of lightning disaster. This work provides reference data for further research on the radial energy transport of lightning return stroke channel and the formation mechanism of shock waves.