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Found 44 result(s)
The Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system was developed to share data across the entire TBI research field and to facilitate collaboration between laboratories, as well as interconnectivity with other informatics platforms. Sharing data, methodologies, and associated tools, rather than summaries or interpretations of this information, can accelerate research progress by allowing re-analysis of data, as well as re-aggregation, integration, and rigorous comparison with other data, tools, and methods. This community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches.
Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.
The Health and Medical Care Archive (HMCA) is the data archive of the Robert Wood Johnson Foundation (RWJF), the largest philanthropy devoted exclusively to health and health care in the United States. Operated by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, HMCA preserves and disseminates data collected by selected research projects funded by the Foundation and facilitates secondary analyses of the data. Our goal is to increase understanding of health and health care in the United States through secondary analysis of RWJF-supported data collections
A community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Spinal Cord Injury research through sharing of data from basic and clinical research.
The DOE Data Explorer (DDE) is an information tool to help you locate DOE's collections of data and non-text information and, at the same time, retrieve individual datasets within some of those collections. It includes collection citations prepared by the Office of Scientific and Technical Information, as well as citations for individual datasets submitted from DOE Data Centers and other organizations.
INDEPTH is a global network of research centres that conduct longitudinal health and demographic evaluation of populations in low- and middle-income countries (LMICs). INDEPTH aims to strengthen global capacity for Health and Demographic Surveillance Systems (HDSSs), and to mount multi-site research to guide health priorities and policies in LMICs, based on up-to-date scientific evidence. The data collected by the INDEPTH Network members constitute a valuable resource of population and health data for LMIC countries. This repository aims to make well documented anonymised longitudinal microdata from these Centres available to data users.
NACDA acquires and preserves data relevant to gerontological research, processing as needed to promote effective research use, disseminates them to researchers, and facilitates their use. By preserving and making available the largest library of electronic data on aging in the United States, NACDA offers opportunities for secondary analysis on major issues of scientific and policy relevance
!!! >>> integrated in https://www.re3data.org/repository/r3d100012653 <<< !!! The National Database for Clinical Trials Related to Mental Illness (NDCT) is an informatics platform for the sharing of human subjects data from all clinical trials funded by the National Institute of Mental Health (NIMH).
Explore, search, and download data and metadata from your experiments and from public Open Data. The ESRF data repository is intended to store and archive data from photon science experiments done at the ESRF and to store digital material like documents and scientific results which need a DOI and long term preservation. Data are made public after an embargo period of maximum 3 years.
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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.
This library is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The Cell Image Library has been merged with "Cell Centered Database" in 2017. The purpose of the database is to advance research on cellular activity, with the ultimate goal of improving human health.
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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.
The Protein Data Bank (PDB) archive is the single worldwide repository of information about the 3D structures of large biological molecules, including proteins and nucleic acids. These are the molecules of life that are found in all organisms including bacteria, yeast, plants, flies, other animals, and humans. Understanding the shape of a molecule helps to understand how it works. This knowledge can be used to help deduce a structure's role in human health and disease, and in drug development. The structures in the archive range from tiny proteins and bits of DNA to complex molecular machines like the ribosome.
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 CyberCell database (CCDB) is a comprehensive collection of detailed enzymatic, biological, chemical, genetic, and molecular biological data about E. coli (strain K12, MG1655). It is intended to provide sufficient information and querying capacity for biologists and computer scientists to use computers or detailed mathematical models to simulate all or part of a bacterial cell at a nanoscopic (10-9 m), mesoscopic (10-8 m).The CyberCell database CCDB actually consists of 4 browsable databases: 1) the main CyberCell database (CCDB - containing gene and protein information), 2) the 3D structure database (CC3D – containing information for structural proteomics), 3) the RNA database (CCRD – containing tRNA and rRNA information), and 4) the metabolite database (CCMD – containing metabolite information). Each of these databases is accessible through hyperlinked buttons located at the top of the CCDB homepage. All CCDB sub-databases are fully web enabled, permitting a wide variety of interactive browsing, search and display operations. and microscopic (10-6 m) level.
>>> !!! the repository is offline !!! <<< More information see: https://dknet.org/about/NURSA_Archive All NURSA-biocurated transcriptomic datasets have been preserved for data mining in SPP through an enhanced and expanded version of Transcriptomine named Ominer. To access these datasets, dkNET provides users with the information of 527 transcriptomic datasets that contain data related to nuclear receptors and nuclear receptor coregulators in the NURSA Datasets table view and redirects users to the current SPP dataset page. Once users find the specific dataset of research interest, users can download the dataset by clicking DOI and then clicking the Download Dataset button at the Signaling Pathways Project webpage. See https://www.re3data.org/repository/r3d100013650
The GenitoUrinary Development Molecular Anatomy Project (GUDMAP) is a consortium of laboratories working to provide the scientific and medical community with tools to facilitate research. The key components are: (1) a molecular atlas of gene expression for the developing organs of the GenitoUrinary (GU) tract; (2) a high resolution molecular anatomy that highlights development of the GU system; (3) mouse strains to facilitate developmental and functional studies within the GU system; (4) tutorials describing GU organogenesis; and (5) rapid access to primary data via the GUDMAP database.
PSI is a global health organization dedicated to improving the health of people in the developing world by focusing on serious challenges like a lack of family planning, HIV and AIDS, barriers to maternal health, and the greatest threats to children under five, including malaria, diarrhea, pneumonia and malnutrition. A hallmark of PSI is a commitment to the principle that health services and products are most effective when they are accompanied by robust communications and distribution efforts that help ensure wide acceptance and proper use. PSI works in partnership with local governments, ministries of health and local organizations to create health solutions that are built to last. We use original data to monitor and evaluate our programs, generate consumer insight, estimate the impact of our solutions, and evaluate the health of the markets we work to strengthen.
Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.
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The project brings together national key players providing environmentally related biological data and services to develop the ‘German Federation for Biological Data' (GFBio). The overall goal is to provide a sustainable, service oriented, national data infrastructure facilitating data sharing and stimulating data intensive science in the fields of biological and environmental research.
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From April 2020 to March 2023, the Covid-19 Immunity Task Force (CITF) supported 120 studies to generate knowledge about immunity to SARS-CoV-2. The subjects addressed by these studies include the extent of SARS-CoV-2 infection in Canada, the nature of immunity, vaccine effectiveness and safety, and the need for booster shots among different communities and priority populations in Canada. The CITF Databank was developed to further enhance the impact of CITF funded studies by allowing additional research using the data collected from CITF-supported studies. The CITF Databank centralizes and harmonizes individual-level data from CITF-funded studies that have met all ethical requirements to deposit data in the CITF Databank and have completed a data sharing agreement. The CITF Databank is an internationally unique resource for sharing epidemiological and laboratory data from studies about SARS-CoV-2 immunity in different populations. The types of research that are possible with data from the CITF Databank include observational epidemiological studies, mathematical modelling research, and comparative evaluation of surveillance and laboratory methods.
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The National Archives makes Denmark's largest collection of questionnaire-based research data available to researchers and students. Order quantitative research data, conduct analyzes online and access register data and international survey data. Formerly known as the Danish Data Archive (DDA), it was the national social science data archive.
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.