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Found 369 result(s)
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The purpose of the JKU Repository is to record and archive the academic and scientific output of all scholars at Jan Kochanowski University, as well as making the data available, thus ensuring unrestricted access to knowledge and maintaining the principle of transparency.
Country
The Biodiversity Information System of Ecuador, SiB-Ec, is a technological tool that will become the core of the national information exchange network that promotes and facilitates interoperability, standardisation and implementation of guidelines for the management of data and information on biodiversity, through the National Catalogue of Biological Objects (CNOB), so that this information is available with different levels of access, and is used for the benefit of conservation, sustainable use of biodiversity, decision making and generation of public policy. SiB-Ec also makes it possible to manage the information generated on the country's Natural Heritage and to coordinate the efforts of the actors involved in the generation, management, publication and use of national biodiversity data and information. SiB-Ec also makes it possible to manage the information generated on the country's Natural Heritage and to coordinate the efforts of the actors involved in the generation, management, publication and use of national biodiversity data and information. Within SIB-Ec there is an IPT (The Integrated Publishing Toolkit) which is connected to GBIF for the exchange of biodiversity data in this network.
Open access repository for digital research created at the University of Minnesota. U of M researchers may deposit data to the Libraries’ Data Repository for U of M (DRUM), subject to our collection policies. All data is publicly accessible. Data sets submitted to the Data Repository are reviewed by data curation staff to ensure that data is in a format and structure that best facilitates long-term access, discovery, and reuse.
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The Leibniz Data Manager (LDM) is a scientific repository for research data from the fields of science and technology. The service supports a better re-usability of research data for scientific projects. The LDM fosters the management and access to heterogeneous research data publications and assists researchers in the selection of relevant data sets for their respective disciplines. The LDM currently offers the following functions for the visualization of research data: · Supports data collections and publications with different formats. · Different views on the same data set (2D and 3D support). · Visualization of Auto CAD files. · Jupyter Notes for demonstrating live code. · RDF Description of data collections.
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DataverseNO (https://dataverse.no) is a curated, FAIR-aligned national generic repository for open research data from all academic disciplines. DataverseNO commits to facilitate that published data remain accessible and (re)usable in a long-term perspective. The repository is owned and operated by UiT The Arctic University of Norway. DataverseNO accepts submissions from researchers primarily from Norwegian research institutions. Datasets in DataverseNO are grouped into institutional collections as well as special collections. The technical infrastructure of the repository is based on the open source application Dataverse (https://dataverse.org), which is developed by an international developer and user community led by Harvard University.
Merritt is a curation repository for the preservation of and access to the digital research data of the ten campus University of California system and external project collaborators. Merritt is supported by the University of California Curation Center (UC3) at the California Digital Library (CDL). While Merritt itself is content agnostic, accepting digital content regardless of domain, format, or structure, it is being used for management of research data, and it forms the basis for a number of domain-specific repositories, such as the ONEShare repository for earth and environmental science and the DataShare repository for life sciences. Merritt provides persistent identifiers, storage replication, fixity audit, complete version history, REST API, a comprehensive metadata catalog for discovery, ATOM-based syndication, and curatorially-defined collections, access control rules, and data use agreements (DUAs). Merritt content upload and download may each be curatorially-designated as public or restricted. Merritt DOIs are provided by UC3's EZID service, which is integrated with DataCite. All DOIs and associated metadata are automatically registered with DataCite and are harvested by Ex Libris PRIMO and Thomson Reuters Data Citation Index (DCI) for high-level discovery. Merritt is also a member node in the DataONE network; curatorially-designated data submitted to Merritt are automatically registered with DataONE for additional replication and federated discovery through the ONEMercury search/browse interface.
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The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. The platform aggregates and harmonizes information already entered in various public repositories such as DRKS, clinicaltrials.gov, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated. The service started during the COVID-19 pandemic.
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Rodare is the institutional research data repository at HZDR (Helmholtz-Zentrum Dresden-Rossendorf). Rodare allows HZDR researchers to upload their research software and data and enrich those with metadata to make them findable, accessible, interoperable and retrievable (FAIR). By publishing all associated research software and data via Rodare research reproducibility can be improved. Uploads receive a Digital Object Identfier (DOI) and can be harvested via a OAI-PMH interface.
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The purpose of the Repository of the University of Life Sciences in Lublin is to disseminate the academic achievements of the University' employees and to promote research conducted at the University. The repository contains resources from various fields of life sciences. Only the community of the University is allowed to upload new records.
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University of Warsaw Research Data Repository aims to collect, archive, preserve and make available all types of research data. Storing and making data available is possible for users affiliated with the University of Warsaw, Poland, or those involved in projects carried out in partnership with the University of Warsaw. Browsing and downloading publicly available research data is open to all interested.
MINDS@UW is designed to gather, distribute, and preserve digital materials related to the University of Wisconsin's research and instructional mission. Content, which is deposited directly by UW faculty and staff, may include research papers and reports, pre-prints and post-prints, datasets and other primary research materials, learning objects, theses, student projects, conference papers and presentations, and other born-digital or digitized research and instructional materials.
The Brown Digital Repository (BDR) is a place to gather, index, store, preserve, and make available digital assets produced via the scholarly, instructional, research, and administrative activities at Brown.
MorphoSource is a data repository specialized for 3D representing physical objects used in research in education (e.g., from museum or laboratory collections). It allows researchers and museum collection staff to store and organize, share, and distribute their own 3d data. Furthermore any registered user can immediately search for and download 3d morphological data sets that have been made accessible through the consent of data authors.
The EUR Data Repository [EDR] is the institutional data repository from the Erasmus University Rotterdam. The EUR Data Repository is an online platform where you showcase your research and make it findable, citable, and reusable for others.
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The Common Research Data Repository (Deposita Dados) is a database for archiving, publishing, disseminating, preserving and sharing digital research data and its mission is to promote, support and facilitate the adoption of open access to the datasets of Brazilian researchers linked to scientific institutions that do not yet have their own research data repositories and/or of Brazilian researchers who have executed their datasets through scientific collaboration in foreign teaching and research institutions.
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AMS Acta is the institutional open access repository which enables the researchers of the Alma Mater Studiorum - University of Bologna to share, preserve and showcase their scientific results making them easily accessible, citable and reusable. The repository collects and disseminates scientific publications, research data and preprints. AMS Acta is the archiving infrastructure for the University of Bologna’s researchers participating in the European programme H2020 that requires open access and the mandatory deposit of all funded peer-reviewed publications in a repository. AMS Acta collects both publications and research data so it is also a suitable archiving solution for the funded projects participating in the H2020 Open Research Data Pilot.
In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.
LibraData is a place for UVA researchers to share data publicly. It is UVA's local instance of Dataverse. LibraData is part of the Libra Scholarly Repository suite of services which includes works of UVA scholarship such as articles, books, theses, and data.
Content type(s)
The National Archives and Records Administration (NARA) is the nation's record keeper. Of all documents and materials created in the course of business conducted by the United States Federal government, only 1%-3% are so important for legal or historical reasons that they are kept by us forever. Those valuable records are preserved and are available to you, whether you want to see if they contain clues about your family’s history, need to prove a veteran’s military service, or are researching an historical topic that interests you.
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OpenAgrar is an open access repository which publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains amongst others theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.