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Found 31 result(s)
The centerpiece of the Global Trade Analysis Project is a global data base describing bilateral trade patterns, production, consumption and intermediate use of commodities and services. The GTAP Data Base consists of bilateral trade, transport, and protection matrices that link individual country/regional economic data bases. The regional data bases are derived from individual country input-output tables, from varying years.
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
Country
Lithuanian Data Archive for Social Sciences and Humanities (LiDA) is a virtual digital infrastructure for SSH data and research resources acquisition, long-term preservation and dissemination. All the data and research resources are documented in both English and Lithuanian according to international standards. Access to the resources is provided via Dataverse repository. LiDA curates different types of resources and they are published into catalogues according to the type: Survey Data, Aggregated Data (including Historical Statistics), Encoded Data (including News Media Studies), and Textual Data. Also, LiDA holds collections of social sciences and humanities data deposited by Lithuanian science and higher education institutions and Lithuanian state institutions (Data of Other Institutions). LiDA is hosted by the Centre for Data Analysis and Archiving of Kaunas University of Technology (data.ktu.edu).
SUNScholarData is an institutional research data repository which can be used for the registration, archival storage, sharing and dissemination of research data produced or collected in relation to research conducted under the auspices of Stellenbosch University. The repository has a public interface which can be used for finding content. It also has private user accounts which can be used by Stellenbosch University users in order to upload, share or publish their research data. In addition to this Stellenbosch University researchers can also use SUNScholarData in order to collaborate with researchers from other institutions whilst working on their research projects. The repository creates a medium through which Stellenbosch University’s research data can be made findable and accessible. It also facilitates the interoperability and re-usability of the university’s research data.
The National Sleep Research Resource (NSRR) is an NHLBI-supported repository for sharing large amounts of sleep data (polysomnography, actigraphy and questionnaire-based) from multiple cohorts, clinical trials, and other data sources. Launched in April 2014, the mission of the NSRR is to advance sleep and circadian science by supporting secondary data analysis, algorithmic development, and signal processing through the sharing of high-quality data sets.
The University of Cape Town (UCT) uses Figshare for institutions for their data repository, which was launched in 2017 and is called ZivaHub: Open Data UCT. ZivaHub serves principal investigators at the University of Cape Town who are in need of a repository to store and openly disseminate the data that support their published research findings. The repository service is provided in terms of the UCT Research Data Management Policy. It provides open access to supplementary research data files and links to their respective scholarly publications (e.g. theses, dissertations, papers et al) hosted on other platforms, such as OpenUCT.
Country
The Digital Repository of Ireland (DRI) is a national trusted digital repository (TDR) for Ireland’s social and cultural data. We preserve, curate, and provide sustained access to a wealth of Ireland’s humanities and social sciences data through a single online portal. The repository houses unique and important collections from a variety of organisations including higher education institutions, cultural institutions, government agencies, and specialist archives. DRI has staff members from a wide variety of backgrounds, including software engineers, designers, digital archivists and librarians, data curators, policy and requirements specialists, educators, project managers, social scientists and humanities scholars. DRI is certified by the CoreTrustSeal, the current TDR standard widely recommended for best practice in Open Science. In addition to providing trusted digital repository services, the DRI is also Ireland’s research centre for best practices in digital archiving, repository infrastructures, preservation policy, research data management and advocacy at the national and European levels. DRI contributes to policy making nationally (e.g. via the National Open Research Forum and the IRC), and internationally, including European Commission expert groups, the DPC, RDA and the OECD.
Country
The Australian Data Archive (ADA) provides a national service for the collection and preservation of digital research data and to make these data available for secondary analysis by academic researchers and other users. Data are stored in seven sub-archives: Social Science, Historical, Indigenous, Longitudinal, Qualitative, Crime & Justice and International. Along with Australian data, ADA International is also a repository for studies by Australian researchers conducted in other countries, particularly throughout the Asia-Pacific region. The ADA International data catalogue includes links to studies from countries including New Zealand, Bangladesh, Cambodia, China, Indonesia, and several other countries. In 2017 the archive systems moved from the existing Nesstar platform to the new ADA Dataverse platform https://dataverse.ada.edu.au/
The Government is releasing public data to help people understand how government works and how policies are made. Some of this data is already available, but data.gov.uk brings it together in one searchable website. Making this data easily available means it will be easier for people to make decisions and suggestions about government policies based on detailed information.
The DesignSafe Data Depot Repository (DDR) is the platform for curation and publication of datasets generated in the course of natural hazards research. The DDR is an open access data repository that enables data producers to safely store, share, organize, and describe research data, towards permanent publication, distribution, and impact evaluation. The DDR allows data consumers to discover, search for, access, and reuse published data in an effort to accelerate research discovery. It is a component of the DesignSafe cyberinfrastructure, which represents a comprehensive research environment that provides cloud-based tools to manage, analyze, curate, and publish critical data for research to understand the impacts of natural hazards. DesignSafe is part of the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI), and aligns with its mission to provide the natural hazards research community with open access, shared-use scholarship, education, and community resources aimed at supporting civil and social infrastructure prior to, during, and following natural disasters. It serves a broad national and international audience of natural hazard researchers (both engineers and social scientists), students, practitioners, policy makers, as well as the general public. It has been in operation since 2016, and also provides access to legacy data dating from about 2005. These legacy data were generated as part of the NSF-supported Network for Earthquake Engineering Simulation (NEES), a predecessor to NHERI. Legacy data and metadata belonging to NEES were transferred to the DDR for continuous preservation and access.
Apollo (previously DSpace@Cambridge) is the University of Cambridge’s Institutional Repository (IR), preserving and providing access to content created by members of the University. The repository stores a range of content and provides different levels of access, but its primary focus is on providing open access to the University’s research publications.
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.