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Found 44 result(s)
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
Water DAMS (Water Data Analysis and Management System) provides access to foundational water treatment technology data that enable researchers and decision-makers to identify and quantify opportunities for technology innovations to reduce the cost and energy intensity of desalination. It is the submission point for all data generated by research conducted by the National Alliance for Water Innovation (NAWI) and is designed to be used by the broader water research community. With publicly accessible contributions from a variety of academic and industrial partners, Water DAMS seeks to enable data discoverability, improve accessibility, and accelerate collaboration that contributes to pipe parity and innovation in water treatment technologies.
FungiDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the kingdom Fungi. FungiDB was first released in early 2011 as a collaborative project between EuPathDB and the group of Jason Stajich (University of California, Riverside). At the end of 2015, FungiDB was integrated into the EuPathDB bioinformatic resource center. FungiDB integrates whole genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining.
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The Research Data Center for Higher Education Research and Science Studies (FDZ-DZHW) at the German Centre for Higher Education Research and Science Studies (DZHW) in Hannover provides the scientific community with quantitative and qualitative research data from the field of higher education and science studies for research and teaching purposes. The data pool of the Research Data Centre is based on two sources: Firstly, it contains the current surveys of the panels conducted in-house (especially DZHW Graduate Panel, Social Survey, DZHW Panel Study of School Leavers with a Higher Education Entrance Qualification, DZHW Scientists Survey), which are integrated by default. Secondly, the Research Data Centre constantly processes, documents and integrates inventory data of the DZHW and its prior organisations. External data from the research area is also integrated into the FDZ data pool.
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jPOSTrepo (Japan ProteOme STandard Repository) is a repository of sharing MS raw/processed data. It consists of a high-speed file upload process, flexible file management system and easy-to-use interfaces. Users can release their "raw/processed" data via this site with a unique identifier number for the paper publication. Users also can suspend (or "embargo") their data until their paper is published. The file transfer from users’ computer to our repository server is very fast (roughly ten times faster than usual file transfer) and uses only web browsers – it does not require installing any additional software.
The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary cancer by providing electronic access to: Information on endogenous spontaneous and induced tumors in mice, including tumor frequency & latency data, Information on genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice) in which tumors arise, Information on genetic factors associated with tumor susceptibility in mice and somatic genetic-mutations observed in the tumors, Tumor pathology reports and images, References, supporting MTB data and Links to other online resources for cancer.
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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.
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Kinsources is an open and interactive platform to archive, share, analyze and compare kinship data used in scientific research. Kinsources is not just another genealogy website, but a peer-reviewed repository designed for comparative and collaborative research. The aim of Kinsources is to provide kinship studies with a large and solid empirical base. Kinsources combines the functionality of communal data repository with a toolbox providing researchers with advanced software for analyzing kinship data. The software Puck (Program for the Use and Computation of Kinship data) is integrated in the statistical package and the search engine of the Kinsources website. Kinsources is part of a research perspective that seeks to understand the interaction between genealogy, terminology and space in the emergence of kinship structures. Hosted by the TGIR HumaNum, the platform ensures both security and free access to the scientific data is validated by the research community.
By stimulating inspiring research and producing innovative tools, Huygens ING intends to open up old and inaccessible sources, and to understand them better. Huygens ING’s focus is on Digital Humanities, History, History of Science, and Textual Scholarship. Huygens ING pursues research in the fields of History, Literary Studies, the History of Science and Digital Humanities. Huygens ING aims to publish digital sources and data responsibly and with care. Innovative tools are made as widely available as possible. We strive to share the available knowledge at the institute with both academic peers and the wider public.
The Infectious Diseases Data Observatory (IDDO) assembles clinical, laboratory and epidemiological data on a collaborative platform to be shared with the research and humanitarian communities. The data are analysed to generate reliable evidence and innovative resources that enable research-driven responses to the major challenges of emerging and neglected infections. Access is available to individual patient data held for malaria and Ebola virus disease. Resources for visceral leishmaniasis, schistosomiasis and soil transmitted helminths, Chagas disease and COVID-19 are under development. IDDO contains the following repositories : COVID-19 Data Platform, Chagas Data Platform, Schistosomiasis & Soil Transmitted Helminths Data Platform, Visceral Leishmaniasis Data Platform, Ebola Data Platform, WorldWide Antimalarial Resistance Network (WWARN)
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The YODA Project is an effort by a group of academically-based clinical researchers to facilitate access to participant-level clinical research data and/or comprehensive reports of clinical research, such as full Clinical Study Reports (CSRs), a level of detail not customarily found in journal publications, with the aim of promoting scientific research that may advance science or lead to improvements in individual and public health and healthcare delivery. The YODA Project is guided by the following core principles, which reflect the overall mission of the project to promote open science by: Promoting the sharing of clinical research data to advance science and improve public health and healthcare, Promoting the responsible conduct of research, Ensuring good stewardship of clinical research data, and Protecting the rights of research participants
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NIMRF offers state-owned specimens with scientific values, including minerals, rocks and fossils. As a data provider, it is our mission to advance the understanding of geo-resources and to provide services for academia, education and scientific popularization in the field of geoscience through collecting, organizing, and sharing specimen resources as well as attaching links to rock-mineral-fossil websites worldwide.
Atmosphere to Electrons (A2e) is a new, multi-year, multi-stakeholder U.S. Department of Energy (DOE) research and development initiative tasked with improving wind plant performance and mitigating risk and uncertainty to achieve substantial reduction in the cost of wind energy production. The A2e strategic vision will enable a new generation of wind plant technology, in which smart wind plants are designed to achieve optimized performance stemming from more complete knowledge of the inflow wind resource and complex flow through the wind plant.
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RADAR4Culture is a low-threshold and easy-to use service for sustainable publication and preservation of cultural heritage research data. It offers free publication for any data type and format according to the FAIR principles, independent of the researcher´s institutional affiliation. Through persistent identifiers (DOI) and a guaranteed retention period of at least 25 years, the research data remain available, citable and findable long-term. Currently, the offer is aimed exclusively at researchers at publicly funded research institutions and (art) universities as well as non-commercial academies, galleries, libraries, archives and museums in Germany. No contract is required and no data publication fees are charged. The researchers are responsible for the upload, organisation, annotation and curation of research data as well as the peer-review process (as an optional step) and finally their publication.
MassBank of North America (MoNA) is a metadata-centric, auto-curating repository designed for efficient storage and querying of mass spectral records. It intends to serve as a the framework for a centralized, collaborative database of metabolite mass spectra, metadata and associated compounds. MoNA currently contains over 200,000 mass spectral records from experimental and in-silico libraries as well as from user contributions.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
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The CORA. Repositori de dades de Recerca is a repository of open, curated and FAIR data that covers all academic disciplines. CORA. Repositori de dades de Recerca is a shared service provided by participating Catalan institutions (Universities and CERCA Research Centers). The repository is managed by the CSUC and technical infrastructure is based on the Dataverse application, developed by international developers and users led by Harvard University (https://dataverse.org).
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Kenya Open Data offers visualizations tools, data downloads, and easy access for software developers. Kenya Open Data provides core government development, demographic, statistical and expenditure data available for researchers, policymakers, developers and the general public. Kenya is the first developing country to have an open government data portal, the first in sub-Saharan Africa and second on the continent after Morocco. The initiative has been widely acclaimed globally as one of the most significant steps Kenya has made to improve governance and implement the new Constitution’s provisions on access to information.
The Alaska Native Language Archive houses documentation of the various Native languages of Alaska and helps to preserve and cultivate this unique heritage for future generations. As the premier repository worldwide for information relating to the Native languages of Alaska, the Archive serves researchers, teachers and students, as well as members of the broader community. The collection includes both published and unpublished materials in or on all of the Alaska Native languages and related languages. The collection has enduring cultural, historic, and intellectual value, particularly for Alaska Native language speakers and their descendants
A Research Data Repository (RDR) for researchers in India. Any registered researchers of Indian Universities can manage their research data on eSHODHMANTHAN-RDR free of cost. This research data repository is configured to provide free of cost research data management services to existing and forthcoming researchers throughout their research life. eSHODHMANTHAN-RDR is powered by Dataverse project of Harvard University
The WDC is concerned with the collection, management, distribution and utilization of data from Chinese provinces, autonomous regions and counties,including: Resource data:management,distribution and utlilzation of land, water, climate, forest, grassland, minerals, energy, etc. Environmental data:pollution,environmental quality, change, natural disasters,soli erosion, etc. Biological resources:animals, plants,wildlife Social economy:agriculture, industry, transport, commerce,infrastructure,etc. Population and labor Geographic background data on scales of 1:4M,1:1M, 1:(1/2)M, 1:2500, etc.
The Tromsø Repository of Language and Linguistics (TROLLing) is a FAIR-aligned repository of linguistic data and statistical code. The archive is open access, which means that all information is available to everyone. All data are accompanied by searchable metadata that identify the researchers, the languages and linguistic phenomena involved, the statistical methods applied, and scholarly publications based on the data (where relevant). Linguists worldwide are invited to deposit data and statistical code used in their linguistic research. TROLLing is a special collection within DataverseNO (http://doi.org/10.17616/R3TV17), and C Centre within CLARIN (Common Language Resources and Technology Infrastructure, a networked federation of European data repositories; http://www.clarin.eu/), and harvested by their Virtual Language Observatory (VLO; https://vlo.clarin.eu/).