Find research datasets worth reusing

opencc-by-4.0Nov 2024View details →

Sahana et al. Supplementary Data for Global Transboundary River Research: Databases, Case Study Analysis, and Regional Statistics for Sustainable Management

This dataset supports our comprehensive review article on transboundary river research, exploring its implications for sustainable management worldwide. Utilizing machine learning, we analyzed 4,237 publications and conducted an in-depth desk review of 325 selected papers, examining a total of 4,713 case studies spanning 286 river basins globally. The study provides critical insights into upstream, midstream, and downstream regions, offering a complete view of challenges and opportunities in transboundary river management. Supplementary Data 1 contains the main database used in this study, sourced from Scopus, Web of Science, and Google Scholar. Additionally, Supplementary Data 2 and 3, included in the spreadsheet, offer statistics and further resources essential for understanding regional and cross-regional dynamics in river basin governance. These supplementary resources include key statistics, case study metadata, and tools, helping to facilitate a deeper exploration of basin-specific and global trends in transboundary water management. This collection of data and resources provides a valuable foundation for researchers and policymakers in advancing sustainable transboundary river management practices.

opencc-by-4.0Sep 2022View details →

Serbian researchers papers in Web of Science database in the period 2003-2021

This is dataset about Serbian papers published in journals indexed in Web of Science collections in the period 2003-2021 We used as "serbian" countries: Serbia, Serbia and Montenegro, Yugoslavia The terms Serbian researcher and Serbian paper used in this dataset are defined as follows: Serbian researcher is a researcher affiliated with a Serbian institution, Serbian paper is a paper with at least one Serbian researcher in the list of authors. This means that a paper published by a researcher with non-Serbian nationality (i.e. German) working at a Serbian institution is taken into account in the analysis of Serbian papers described in this paper. Thomson Reuters’ Web of Science (WoS) database was used for data acquisition. We searched Serbian papers in two WoS collections - Science Citation Index Expanded (SCIE) and the Social Science Citation Index (SSCI). The search query executed over those collections on 18th of January, 2022. CU=(%Serbia%  OR %Serbia and Montenegro% OR %Yugoslavia%) AND PY=[2003-2021]   We also analyzed the number of articles of Serbian researchers published in journals with an unstable impact factor (IF), i.e. journals which didn’t have an IF before 2008, and had one in some subperiod of 2008-2015, i.e. lost their IF until 2015. The majority of those journals stopped being indexed in Web of Science as a ban for losing the quality or having predatory journal behavior. We found 143 such journals and their ISSNs by using the JCR (Journal citation reports in the period 2007 - 2015).

opencc-by-4.0Sep 2022View details →

Databases and information systems for research output: digital humanities outlook (DARIAH Bibliographical Data Working Group, September, 30th 2022)

The video recording of the workshop "Databases and information systems for research output: digital humanities outlook" organized by DARIAH Bibliographical Data Working Group.

openmit-licenseMar 2019View details →

Biographische Informationssysteme (DPBs, Digital Knowledge Databases, Virtual Research Environments)

The table is an overview of database and online systems to manage/publish prosopographical and biographical data.

openbsd-3-clause-clearJun 2019View details →

Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software and Other Digital Artifacts

The Research Resource Identifier was introduced in biomedicine in 2014 to more precisely identify the reagents and tools used in published biomedical research and to track use of tools across the breadth of the biomedical literature. The current RRID specification covers key biological and digital resources. Authors are instructed to include an RRID after the first mention of any resource used. RRIDs are designed to be easy to find using  a full text search search engine. The published data sets were used in our comparative study where comparing the output of our RRID curation workflow with the outputs of automated text mining systems that have been used to identify mentions of resources in the text of publications. All files in tab-separated format (tsv). Scibot.tsv: Records of the RRID curation workflow using SciBot. Each record shows that a resource RRID was identified in paper PMID with curator tags (Tag1, Tag2, both optional)     PMID: Pubmed ID      RRID: Research Resource Identifier      Tag1: Curator tags (optional)      Tag2: Additional curator tags (optional) rdwsorted.tsv: Records of the output from RDW, a text mining software. RDW identifies mentions of research resources in papers. Each record shows that a resource RRID was identified in paper PMID.     PMID: Pubmed ID      RRID: Research Resource Identifier rridbyrdw05282019.tsv: Records of the output of the RRID-by-RDW in RDW. RRID-by-RDW is a component in RDW that identifies mentions of research resources in papers by matching patterns of RRID specifications. Each record shows that a resource RRID was identified in paper PMID.     PMID: Pubmed ID      RRID: Research Resource Identifier      Context: Snippet where the RRID was found resource_metadata20190418.tsv: Metadata of RRIDs This file contains metadata of resources and their RRIDs. See file header for column definitions. RRIDCUR-definitions.tsv: Definitions of curator tags used in Scibot.tsv.    tag: Tag name     definition: Definition of the tag

opencc-by-4.0Aug 2024View details →

D1.4 - Consolidated OA data set for responsible research practices and trust in science: POIESIS National and Regional Database

Deliverable 1.4 of the POIESIS project is a consolidated open access data set for responsible research practices and trust in science. D1.4 consists of two databases: the POIESIS National Database and the POEISIS Regional Database. The method and rationale behind the construction of all indicators in both databases are laid out in Work Package 1’s previous deliverable, D1.3 (Bauer et al., 2024). The two database are accompanied by a Guidance Sheet which provides details and relevant notes regarding the structure of the two databases.

opencc-by-4.0Dec 2022View details →

Quantitative databases about Hacker Education Research - School and Hacker Communities

This group of files includes three distinct databases for use in PSPP: - CA_Cycle1 - Indicators about Hacker Education and sociodemographic variables of teachers, researchers and students in the first cycle of the Conecta Escola-Mundo project; - CA_Cycle2 - Indicators about Hacker Education and sociodemographic variables of teachers, researchers and students in the second cycle of the Conecta Escola-Mundo project; - HackerCommunities - Indicators about Hacker Education and sociodemographic variables of 115 hackers participating in eight different movements around the world;

opencc-by-4.0Mar 2023View details →

Database underlying the scientific publication: A global database of seahorse research and innovation, from the beginning to 2022

The present database supports the study "A global database of seahorse research and innovation, from the beginning to 2022".  Scientific knowledge on seahorses is rapidly expanding in response to declines in wild populations due to habitat loss and fishing. A plethora of information has accumulated and up until now, a global, publicly available, curated database has never been produced in a transparent and systematic way. Here, we present the largest open-access repository of scientific publications addressing seahorses and, for the first time, of theses and patents. Compilation followed the “Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) Statement for systematic reviews and meta-analyses, with modifications. The current repository duplicates the number of scientific publication records found from previous bibliometric/literature/review studies, using three extra repositories of source publications, and a lifetime window, e.i. from the beginning to March 2022. A total of 977 scientific publications, 101 theses and 533 patents are gathered in the dataset, covering 41 seahorse species out of 48 currently recognized. In addition, current work presents for the first time new metrics on authors, institutions, and research subject/field/discipline/thematic, as well as the organism’s stage of development (embryo, newborn, juvenile, subadult and adult). To expand metadata usage, the database was also made available in the Dublin Core™ Metadata Initiative format. This contribution can be used as a core reference for scientists, aquaculturists and conservationists, and is useful to rapidly identify relevant literature and knowledge gaps, better understand seahorse research and discover new trends in seahorse research and innovation. The database is available in two formats: 1) <a href="https://zenodo.org/api/files/5651b70d-a7a0-45e6-8ce6-cb92bbe6f7e5/SeahorseBibliometricDatabase.xlsx">SeahorseBibliometricDatabase.xlsx</a> and 2) <a href="https://zenodo.org/api/files/5651b70d-a7a0-45e6-8ce6-cb92bbe6f7e5/SeahorseBibliometricDatabase_DublinCore.xlsx">SeahorseBibliometricDatabase_DublinCore.xlsx</a>, which is a vocabulary standardized (Dublin Core™ Metadata Initiative) version of the previous one, for metadata reuse.

opencc-by-4.0Mar 2023View details →

Database for terrestrial water system research

Database for terrestrial water system research This database was developed in a study of  “Mohanna Zarei & Georgia Destouni, Research gaps and priorities for tressterial water and Earth System connections from catchment to Global scale, Earth's Future, Wiley, 2024. (https://doi.org/10.1029/2023EF003792)). It includes data from a scoping literature review, based on searches performed with the Web of Science (WoS) search engine across all available databases. The search was performed on April 22nd 2022, encompassing the fields of title, abstract, authors’ keywords and WoS generated keywords. See Mohanna Zarei & Georgia Destouni, Research gaps and priorities for tressterial water and Earth System connections from catchment to Global scale, Earth's Future, Wiley, 2024. (https://doi.org/10.1029/2023EF003792) for further search method and other study descriptions.   The database is provided in an Excel (xsls) file, comprising and organised in four sheets as follows: 1. Description of the data and project; 2. Water flow papers; 3. Water storage papers; 4. Water quality papers.   Column A in each data sheet (2-4) lists the published papers by the end of 2021 that address both ground- and surface water at scales of whole catchment or larger, up to global, for the aspects of water flow (Sheet 2: Water flow papers), water storage (Sheet 3: Water storage papers) or water quality (Sheet 4: Water quality papers), as returned from the automatic WOS search, along with their WOS index (column B) and our article number ID (column C). The other columns in each sheet list manually extracted data regarding the: i) study method (columns D-J), ii) study scale (columns K-N), and iii) study region (columns O-U).   Reference Mohanna Zarei & Georgia Destouni, Research gaps and priorities for tressterial water and Earth System connections from catchment to Global scale, Earth's Future, Wiley, 2024. (https://doi.org/10.1029/2023EF003792)

opencc-by-4.0Oct 2022View details →

Exposing New Taxonomic Variation with Inflammation – A Model-Specific Genome Database for Microbiome Researchers

Data deposit for CBAJ-DB v1.2

opencc-zeroOct 2020View details →

The clinical impact of high-profile animal-based research reported in the UK national press: a detailed discussion of articles from 1995, and full search results from the Nexis database

Objectives: We evaluated animal-based biomedical 'breakthroughs' reported in the UK national press in 1995 (25 years prior to the conclusion of this study). Based on evidence of over-speculative reporting of biomedical research in other areas (e.g. press releases and scientific papers), we specifically examined animal research in the media, asking, "In a given year, what proportion of animal research 'breakthroughs' published in the UK national press had translated, more than 20 years later, to approved interventions?" Methods: We searched the Nexis media database (LexisNexis.com) for animal-based biomedical reports in the UK national press. The only restrictions were that the intervention should be specific, such as a named drug, gene, biomedical pathway, to facilitate follow-up, and that there should be claims of some clinical promise. Main Outcome Measures: Were any interventions approved for human use? If so, when and by which agency? If not, why, and how far did development proceed? Were any other, directly related interventions approved? Did any of the reports over-state human relevance? Results: Over-speculation and exaggeration of human relevance was evident in all the articles examined. Of 27 unique published 'breakthroughs', only one had clearly resulted in human benefit. Twenty were classified as failures, three were inconclusive, and three were partially successful. Conclusions: The results of animal-based pre-clinical research studies are commonly over-stated in media reports, to prematurely imply often-imminent 'breakthroughs' relevant to human medicine.

opencc-by-4.0Nov 2019View details →

OPEN-WINDOW: SOUND EVENT DATABASE FOR RESEARCH AND DEVELOPMENT

(1) Background: Situated in the domain of urban sound scene classification by humans and machines, the research in this project will be a first step towards mapping urban noise pollution experienced indoors and finding ways to reduce its negative impact in peoples' homes. The acoustic distinction between outdoor and indoor scenes is an active research field and can be automated with some success. A much subtler difference is the change in the indoor soundscape induced by an open window. Being able to determine this, however, would allow applications in warning systems and be a prerequisite for an app-based urban sound mapping project. Acoustic detection requires neither line of sight nor sensors at the window frame or knowledge of the number of windows or their size. The task, however, varies substantially in difficulty with the amount of sound inside and outside. From the point of machine classification, the lack of specificity is the most problematic aspect: Very few sounds if any can be assumed to originate exclusively from outside and be present at all times to aid automatic detection. The required generalisation ability, however, can be assumed for humans, who might also use very subtle cues in the change of reverberations.   (2) Dataset (a) Recording locations The recordings have been made at three different locations.  <ul> <li>Farm: A farm in Brook, Surrey, United Kingdom. The recordings were made in an open-plan studio flat area in the centre of the farm. The recordings in this location have the lowest levels of background noise, due mainly to a quiet environmental surrounding.</li> <li>Office 1: An office at the University of Surrey, Guildford, United Kingdom. The recordings were made in an open-plan office located on the first floor, at the Centre for Vision, Speech and Signal Processing (CVSSP). Since this office accommodates 16 researchers, recordings in this location have the highest level of background noise</li> <li>Office 2: An office at the University of Surrey, Guildford, United Kingdom. The recordings were made in a small size open-plan office at the CVSSP. This office accommodates 8 researchers and the recordings made in this office considered to have a medium level of background noise.</li> </ul> (b) Recording equipment The recordings made at the two offices and a studio flat in a farm used a dedicated laptop, Focusrite Clarett 4pre USB external sound card (44,100 Hz sample rate at 16 bits per sample) 1, and a Behringer ECM 8000 microphone. (c) Recording setup The Behringer ECM 8000 microphone is connected to the External Line Return (XLR) input of the Focusrite Clarett external sound card via an XLR cable. The external sound card is connected to the dedicated laptop and controlled using Ableton Live 10 software for setting configurations and exporting the recorded audio files. The microphone is located approximately 10 cm away from the window and fixed using a microphone holder. At each location 90 audio sessions are recorded; 60 one minute recordings for static state setup and 30 fifteen seconds recordings for transitional state setup. (d) File naming conventions The naming convention for audio recording is as follows: [Location] [State] [Time] [IDX] [State] will be one of the following: “O stands for open, C stands for Close, OC means a transition from Open to Close and CO stands for a transition from Close to Open.” [Time] stamp will be one of the following: “AM stands for morning between 9:00 to 12:00, N stands for noon which is between 13:00 to 15:00 and PM which stands for an afternoon which is between 17:00 to 20:00.” [IDX] is representing the file ID number. For example, “Farm C PM 01.wav”, means this file is recorded at the farm and in the afternoon when the window is closed and the file ID is 01. (e) Dataset acquisition: A recording kit consisting of a dedicated laptop and microphone will be given to volunteers. Custom-programmed software will remind the user to specify the window state (establishing the so-called ground truth). (f) Specifications   - Open-Window contains 270 audio recordings totalling 3.37 hours of audio.   - Each audio recording belongs to one of the four classes representing the window states; two stationary states (Open, Close) and two transitional states (Open-Close, Close-Open).   - The recordings were carried out in different locations and at different times of the day.       - Three locations: Office1, Office2, Farm       - Three periods of the day: Morning, Afternoon, Evening   - The recordings are split into six-folds.       - Fold 1 is the test set.       - Fold 2 is the validation set.       - Folds 3-6 comprise the training set.     Each fold is balanced in terms of the class and location distribution.   - The annotations/metadata can be found in annotations.csv.   - The recordings for the stationary states are approximately 60 seconds, while the recordings for the transitional states are approximate 15 seconds.   - The format of the recordings is 2-channel 16-bit PCM sampled at 44.1 kHz.

opencc-zeroDec 2015View details →

Data from: A social-ecological database to advance research on infrastructure development impacts in the Brazilian Amazon

Recognized as one of the world's most vital natural and cultural resources, the Amazon faces a wide variety of threats from natural resource and infrastructure development. Within this context, rigorous scientific study of the region's complex social-ecological system is critical to inform and direct decision-making toward more sustainable environmental and social outcomes. Given the Amazon's tightly linked social and ecological components and the scope of potential development impacts, effective study of this system requires an easily accessible resource that provides a broad and reliable data baseline. This paper brings together multiple datasets from diverse disciplines (including human health, socio-economics, environment, hydrology, and energy) to provide investigators with a variety of baseline data to explore the multiple long-term effects of infrastructure development in the Brazilian Amazon.

opencc-zeroDec 2016View details →

Data from: Towards an integrated database on Canadian ocean resources: benefits, current states, and research gaps

Oceanic ecosystem services support a range of human benefits, and Canada has extensive research networks producing growing data sets. We present a first effort to compile, link, and harmonize available information to provide new perspectives on the status of Canadian ocean ecosystems and corresponding research. The metadata database currently includes 1094 individual assessments and data sets from government (n = 716), nongovernment (n = 320), and academic sources (n = 58), comprising research on marine species, natural drivers and resources, human activities, ecosystem services, and governance, with data sets spanning 1979–2012 on average. Overall, research shows a strong prevalence towards single-species fishery studies, with an underrepresentation of economic and social aspects, and of the Arctic region in general. Nevertheless, the number of studies that are multispecies or ecosystem-based have increased since the 1960s. We present and discuss two illustrative case studies — marine protected area establishment in Canada and herring resource use by the Heiltsuk First Nation — highlighting the potential use of multidisciplinary data sets drawn from metadata records. Identifying knowledge gaps is key to achieving the comprehensive, accessible and interdisciplinary data sets and subsequent analyses necessary for new sustainability policies that meet both ecological and socioeconomic needs.

opencc-zeroJan 2024View details →

Data from: Improper data practices erode the quality of global ecological databases and impede the progress of ecological research

The scientific community has entered an era of big data. However, with big data comes big responsibilities, and best practices for how data are contributed to databases have not kept pace with the collection, aggregation, and analysis of big data. Here, we rigorously assess the quantity of data for specific leaf area (SLA) available within the largest and most frequently used global plant trait database, the TRY Plant Trait Database, exploring how much of the data were applicable (i.e., original, representative, logical, and comparable) and traceable (i.e., published, cited, and consistent). Over three-quarters of the SLA data in TRY either lacked applicability or traceability, leaving only 22.9% of the original data usable compared to the 64.9% typically deemed usable by standard data cleaning protocols. The remaining usable data differed markedly from the original for many species, which led to altered interpretation of ecological analyses. Though the data we consider here make up only 4.5% of SLA data within TRY, similar issues of applicability and traceability likely apply to SLA data for other species as well as other commonly measured, uploaded, and downloaded plant traits. We end with suggested steps forward for global ecological databases, including suggestions for both uploaders to and curators of databases with the hope that, through addressing the issues raised here, we can increase data quality and integrity within the ecological community.

opencc-by-4.0Mar 2024View details →

Research database - Regulations, Manuals and Technical Standards Professional Career Pharmaceutical Sciences and Biochemistry

This database contains information on Regulations, Manuals and Technical Standards of the Professional Career of Pharmaceutical Sciences and Biochemistry. Inca Garcilaso de la Vega University. Lima Peru

opencc-by-4.0Sep 2024View details →

CARPE Database of Empirical Research on Assessment for the Leaving Certificate in Ireland (May 2024)

This is the download site for the CARPE Database of Empirical Research on Leaving Certificate Assessment in Ireland (May 2024). We hope that this database will act as a guide and resource for any future research regarding the Leaving Certificate and the assessment methods used therein. If you do use this database as a reference or tool, please cite it as: Lehane, P., O'Connor, G. & O'Leary, M. (2024). CARPE Database of Empirical Research on Leaving Certificate Assessment in Ireland [Database]. Dublin City University.  We realise that there are current and future studies that should be included in this database now and in the years to come. We intend on updating this database on an annual basis with missing or new studies. If you wish to suggest an empirical study that could be added to this database, please fill in the relevant details on this <a href="https://forms.gle/ggi53t1psYXJXqi77">Google Form</a>.