Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
29
datasets available to search
ShareScore release 0.7.1
Dataset results
29 results for “research data services”
Jisc Research Data Shared Service metadata focus group use cases
<p>Dataset of use cases collected between July and October 2016 during a series of metadata focus groups conducted with a number of the <strong>Research Data Shared Service</strong> pilots who volunteered for the process.</p> <p>This dataset is available in two formats (including an open format) with the same content: 180 use cases in the following user story structure: </p> <ul> <li><strong>As a</strong></li> <li><strong>Theme</strong></li> <li><strong>I want </strong></li> <li><strong>So that</strong></li> <li><strong>Comments</strong></li> </ul> <p>The .xlsx file contains additional formatting grouping the use cases by theme, role, data and community.</p>
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> ● The Islamic University of Gaza (IUG) ● Al-Quds Open University (QOU) ● Birzeit University (BZU) ● Palestine Technical University-Kadoori (KAD)
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data with Pie Charts
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> <p>● The Islamic University of Gaza (IUG)</p> <p>● Al-Quds Open University (QOU)</p> <p>● Birzeit University (BZU)</p> <p>● Palestine Technical University-Kadoori (KAD)</p> <p>[Data visualised as pie charts]</p> <p> </p>
R code and associated data for: A review of riverine ecosystem service quantification: research gaps and recommendations
<p>This publication contains the R code and associated data used in the Journal of Applied Ecology publication entitled "A review of riverine ecosystem service quantification: research gaps and recommendations". </p>
Dataset for: Developing research data management services and support for researchers: a mixed methods study
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manuscript: <br> Perrier L, Barnes L. Developing research data management services and support for researchers: a mixed methods study. Partnership. 2018;13(1). doi: doi.org/10.21083/partnership.v13i1.4115.</p> <p>Full-text available at: <a href="https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202">https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202</a></p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset: </p> <ol> <li>Coding Scheme: RDMServicesSupport_Codes.txt</li> <li>Transcript, Focus Group 01 (anonymized): RDMServicesSupport_FocusGroup01.pdf</li> <li>Transcript, Focus Group 02 (anonymized): RDMServicesSupport_FocusGroup02.pdf</li> <li>Transcript, Focus Group 03 (anonymized): RDMServicesSupport_FocusGroup03.pdf</li> <li>Transcript, Focus Group 04 (anonymized): RDMServicesSupport_FocusGroup04.pdf</li> </ol> <p>Contact: Laure Perrier: <a href="https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202">orcid.org/0000-0001-9941-7129</a></p>
Digital Scholarship services and supports - an overview from Irish Research and National Libraries - Data with Comments
<p>This dataset contains survey data with comments (cleaned, direct references to institutions removed) and broken down by survey question sections. Some of the data has been converted to counts where it was used to generate the charts.</p> <p>The data is the output of a 2018 CONUL (Ireland’s consortium of research and national libraries) survey focusing on Digital Scholarship services and supports from a Irish Research and National Library perspective.</p>
Identifying and Implementing Relevant Research Data Management Services for the Library at the University of Dodoma, Tanzania
<p>This data set presents the results of research conducted at the University of Dodoma, Tanzania. The purpose of the research was to identify and report on relevant RDM services that need to be implemented so that researchers and university management could collaborate and make our research data accessible to the international community.</p> <p>The data set was used to support both the mini-dissertation as well as a paper published in the Data Science Journal. The journal paper presents findings on important issues for consideration when planning to develop and implement RDM services at a developing country, academic institution. The paper also mentions the requirements for the sustainability of these initiatives.</p>
Research Data Services (RDS) in Spanish Academic Libraries
<p>Files in csv format to analyze Research Data Services implemented in Spanish university libraries (2022).</p>
Research Data Services in Academic Libraries: A Survey of North American Academic Libraries in 2019
<p>To determine the extent to which research data services (RDS) are supported in academic libraries and how that has changed over a decade, in 2019 a research team led by Carol Tenopir at the University of Tennessee Center for Information and Communication Studies, in collaboration with ACRL-Choice, surveyed academic library directors in the United States and Canada. This survey allowed us to compare results with a similar survey conducted in 2012. The goal of both studies was to discover the types of data services offered, the staffing deployed or anticipated for such services, the training necessary to support RDS, and RDS plans for the future.</p> <p>The associated white paper can be accessed at <a href="http://www.choice360.org/librarianship/whitepaper">http://www.choice360.org/librarianship/whitepaper</a> and downloaded at <a href="https://www.research.net/r/CHOICERDSWP">https://www.research.net/r/CHOICERDSWP</a></p>
Research Data Services in Academic Libraries: A Survey of North American Academic Libraries in 2019
Open the record for dataset details and reuse information.
Research Data Services in US Higher Education: A Web-Based Inventory - Raw Data
<p>This dataset represents an inventory of research data services at 120 US colleges and universities. The data was collected using a systematic web content analysis process in late 2019. This dataset underlies the following report: Jane Radecki and Rebecca Springer, "Research Data Services in US Higher Education: A Web-Based Inventory," Ithaka S+R, Nov. 2020, <a href="https://sr.ithaka.org/publications/research-data-services-in-us-higher-education/">https://doi.org/10.18665/sr.314397</a>.</p> <p>We defined research data services as any concrete, programmatic offering intended to support researchers (including faculty, postdoctoral researchers, and graduate students) in working with data, and identified services within the following campus units: library, IT department/research computing, independent research centers and facilities, academic departments, medical school, business school, and other professional schools. We also recorded whether the institution offered local high performance computing facilities. For detailed definitions, exclusions, and data collection procedures, please see the report referenced above.</p>
Figure 3 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 3 Types of campus groups that provide RDS (n=103). Type codes are defined as follows: Admin: a campus administrative unit that does not fall into any other category; Center: research centers or institutes excluding HPC groups; Dept = Departments or colleges; HPC: High Performance Computing and research computing units including HPC run by IT units; Individuals: Individual staff, faculty, students, etc.; IT: Information Technology associated with the entire campus, colleges, or departments excluding HPC groups; Lab: Various labs on campus that do not fall into any other category; Research Office: Groups that oversee university research; Other: Groups that cannot be categorized under any other code.
Figure 2 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 2 Breakdown of the workshops or topics with a tool or programming language code applied (n=47). Only tool codes that have a frequency >1 are shown. Tool code names are self-explanatory (i.e. the name of tool).
Figure 1 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 1 Workshop topic code frequencies. Up to two topic codes were applied to each workshop (n=160). Topic codes are defined as follows: Carpentry: a data or software Carpentry workshop; Cleaning: data cleaning and related techniques; Coding: how to work with data via command line or in a specific language; General: the basics of data management; GIS: geographic information system or spatial data/tools; Grants: the word "grants" or the name of a funding agency was explicitly mentioned in the workshop's title or description; HPC: high performance computing; Locate: focused on how to search and locate datasets; Metadata: metadata and data documentation; Mining: focused on text and data mining; Org: data organization; Other: misc. topics or unclassifiable; Plans: data management plans; Repository: addresses a specific repository, how to use a repository, or data repositories in general; Reproducibility: focused on research reproducibility; StorageSec: data storage and/or security tools and topics; Tool: focused on how to use tools related to data and data management (see Fig. 2); Visualization: data visualization.
Supplementary material 1 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Links to library and university/college research data management policies.
Figure 4 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 4 Disciplinary categorization of campus groups that provide RDS (n=34). Discipline codes are defined as follows: Bio: Groups that specialize in biology, including health and medicine; Bio/Stats: Groups that specialize in biology and statistics; Data: no specific discipline but has the word 'data' in the name; GIS: Groups that specialize in spatial and GIS (Geographic Information Systems) data; Humanities: Groups specializing in humanities; Social/Stats: Groups that specialize in statistics and social science; SocialSci: Groups specializing in social science; Stats: Groups specializing in statistics.
Data from: A review of riverine ecosystem service quantification: research gaps and recommendations
1.Increasing demand for benefits provided by riverine ecosystems threatens their sustainable provision. The ecosystem service concept is a promising avenue to inform riverine ecosystem management, but several challenges have prevented the application of this concept. 2.We quantitatively assess the field of riverine ecosystem services' progress in meeting these challenges. We highlight conceptual and methodological gaps, which have impeded integration of the ecosystem service concept into management. 3.Across 89 relevant studies, 33 unique riverine ecosystem services were evaluated, for a total of 404 ecosystem service quantifications. Studies quantified between one and 23 ecosystem services, although the majority (55%) evaluated three or less. Among studies that quantified more than one service, 58% assessed interactions between services. Most studies (71%) did not include stakeholders in their quantification protocols, and 34% developed future scenarios of ecosystem service provision. Almost half (45%) conducted monetary valuation, using 16 methods. Only 9% did not quantify or discuss uncertainties associated with service quantification. The indicators and methods used to quantify the same type of ecosystem service varied. Only 3% of services used indicators of capacity, flow, and demand in concert. 4.Our results suggest indicators, data sources, and methods for quantifying riverine ecosystem services should be more clearly defined and accurately represent the service they intend to quantify. Furthermore, more assessments of multiple services across diverse spatial extents and of riverine service interactions are needed, with better inclusion of stakeholders. Addressing these challenges will help riverine ecosystem service science inform river management. 5.Synthesis and applications. The ecosystem service concept has great potential to inform riverine ecosystem management and decision making processes. However, this review of riverine ecosystem service quantification uncovers several remaining research gaps, impeding effective use of this tool to manage riverine ecosystems. We highlight these gaps and point to studies showcasing methods that can be used to address them.
Data from: An ecosystem services perspective on brush management: research priorities for competing land use objectives
1. The vegetation of semi-arid and arid landscapes is often comprised of mixtures of herbaceous and woody vegetation. Since the early 1900s, shifts from herbaceous to woody plant dominance, termed woody plant encroachment and widely regarded as a state change, have occurred world-wide. This shift presents challenges to the conservation of grassland and savanna ecosystems and to animal production in commercial ranching systems and pastoral societies. 2. Dryland management focused on cattle and sheep grazing has historically attempted to reduce the abundance of encroaching woody vegetation (hereafter, 'brush management') with the intent of reversing declines in forage production, stream flow or groundwater recharge. Here, we assess the known and potential consequences of brush management actions, both positive and negative, on a broader suite of ecosystem services, the scientific challenges to quantifying these services and the trade-offs among them. 3. Our synthesis suggests that despite considerable investments accompanying the application of brush management practices, the recovery of key ecosystem services may be short-lived or absent. However, in the absence of such interventions, those and other ecosystem services may be compromised, and the persistence of grassland and savanna ecosystem types and their endemic plants and animals threatened. 4. Addressing the challenges posed by woody plant encroachment will require integrated management systems using diverse theoretical principles to design the type, timing and spatial arrangement of initial management actions and follow-up treatments. These management activities will need to balance cultural traditions and preferences, socio-economic constraints and potentially competing land-use objectives. 5. Synthesis. Our ability to predict ecosystem responses to management aimed at recovering ecosystem services where grasslands and savannas have been invaded by native or exotic woody plants is limited for many attributes (e.g. primary production, land surface–atmosphere interactions, biodiversity conservation) and inconsistent for others (e.g. forage production, herbaceous diversity, water quality/quantity, soil erosion, carbon sequestration). The ecological community is challenged with generating robust information about the response of ecosystem services and their interactions if we are to position land managers and policymakers to make objective, science-based decisions regarding the many trade-offs and competing objectives for the conservation and dynamic management of grasslands and savannas.
Research Data Services (RDS) in REBIUN libraries
<p>Results of the survey sent to the managers of the libraries belonging to the Network of Spanish University Libraries (Red de Bibliotecas Universitarias Españolas - REBIUN 2014) during the first four months of 2014. The aim of the responses was to know the state of the Research Data Services (RDS).</p>
Supplementary material 5 from: Neill AM, O`Donoghue C, Stout JC (2023) Spatial analysis of cultural ecosystem services using data from social media: A guide to model selection for research and practice. One Ecosystem 8: e95685. https://doi.org/10.3897/oneeco.8.e95685
MaxEnt Supplementary Info
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.