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Found 49 result(s)
The Whitehall II study was established to explore the relationship between socio-economic status, stress and cardiovascular disease. A cohort of 10,308 participants aged 35-55, of whom 3,413 were women and 6,895 men, was recruited from the British Civil Service in 1985. Since this first wave of data collection, self-completion questionnaires and clinical data have been collected from the cohort every two to five years with a high level of participation. Data collection is intended to continue until 2030.
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Since 2004, the Leibniz Institute for Prevention Research and Epidemiology – BIPS has been working on the establishment and maintenance of the project-based German Pharmacoepidemiological Research Database (short GePaRD). GePaRD is based on claims data from statutory health insurance (SHI) providers and currently includes information on about 20 million persons who have been insured with one of the participating providers since 2004. Per data year, there is information on approximately 17% of the general population from all geographical regions of Germany.
The Netherlands Cancer Registry is the national registration since 1989, providing statistics on cancer in the Netherlands. The registry is maintained by the Netherlands Comprehensive Cancer Organisation (IKNL). Data on incidence, prevalence, survival, mortality can be viewed in NCR data & figures on the IKNL website.
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Health Data Nova Scotia (HDNS), is a data repository based in the Faculty of Medicine's, Department of Community Health and Epidemiology at Dalhousie University, focused on supporting data driven research for a healthier Nova Scotia. HDNS facilitates research and innovation in Nova Scotia by providing access to linkable administrative health data and analysis for research and health service assessment purposes in a secure, controlled environment, while respecting the privacy and confidentiality of Nova Scotians.
The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.
A premier source for United States cancer statistics, SEER gathers information related to incidence, prevalence, and survival from specific geographic areas that represent 28 percent of the population, as well as compiles related reports and reports on the national cancer mortality rates. Their aim is to provide information related to cancer statistics and decrease the burden of cancer in the national population. SEER has been collecting data from cancer cases since 1973.
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With ARS - Antimicrobial Resistance Surveillance in Germany - the infrastructure for a nationwide surveillance of antimicrobial resistance has been established, which covers both the inpatient medical care and the ambulatory care sector. This is intended to reliable data on the epidemiology of antimicrobial resistance in Germany and differential statements provided by structural features of the health care and by region are possible. ARS is designed as a laboratory-based surveillance system for continuous collection of resistance data from routine for the full range of clinically relevant bacterial pathogens. Project participants and thus data suppliers are laboratories that analyze samples of medical facilities and doctors' offices microbiologically.
The Pennsieve platform is a cloud-based scientific data management platform focused on integrating complex datasets, fostering collaboration and publishing scientific data according to all FAIR principles of data sharing. The platform is developed to enable individual labs, consortiums, or inter-institutional projects to manage, share and curate data in a secure cloud-based environment and to integrate complex metadata associated with scientific files into a high-quality interconnected data ecosystem. The platform is used as the backend for a number of public repositories including the NIH SPARC Portal and Pennsieve Discover repositories. It supports flexible metadata schemas and a large number of scientific file-formats and modalities.
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BenchSci is a free platform designed to help biomedical research scientists quickly and easily identify validated antibodies from publications. Using various filters including techniques, tissue, cell lines, and more, scientists can find out published data along with the antibody that match specific experimental contexts within seconds. Free registration & access for academic research scientists.
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CANJEM (CANadian Job-Exposure Matrix) is a large source of retrospective information on job-based exposure for a given occupation and time period. Covering most occupations and many agents, it provides information on the probability, frequency and intensity of exposure from a list of 258 occupational risk factors. CANJEM was built from past individual expert evaluations of occupational exposures in a series of four case control studies of various cancers conducted since the mid-1980s up to 2010 in the greater Montreal area. During these studies over 30 000 jobs from 1930 to 2005 held by close to 10 000 subjects were evaluated by experts who assigned exposures based on descriptions of tasks, processes, work environment, and exposure control measures."
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DDBJ Sequence Read Archive (DRA) is the public archive of high throughput sequencing data. DRA stores raw sequencing data and alignment information to enhance reproducibility and facilitate new discoveries through data analysis. DRA is a member of the International Nucleotide Sequence Database Collaboration (INSDC) and archiving the data in a close collaboration with NCBI Sequence Read Archive (SRA) and EBI Sequence Read Archive (ERA).
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<<<!!!<<< As detected 2017-11-24 TBNet India is no longer accessible >>>!!!>>> TBNet India is an initiative by the Department of Biotechnology, Govt of India with special focus on Indian contributions on research and various issues related to tuberculosis. Around 13 institutions across India are apart of this initiative. TB Net India focuses to gather clinical, epidemiological and molecular data and make it available to the biomedical community.
COViMS (COVID-19 Infections in MS & Related Diseases) is a joint effort of the National MS Society, Consortium of MS Centers and Multiple Sclerosis Society of Canada to capture information on outcomes of people with MS and other CNS demyelinating diseases (Neuromyelitis Optica, or MOG antibody disease) who have developed COVID-19.
ICD serves as the international standard for diagnostic classification for all general epidemiological, many health management purposes and clinical use. The ICD's resources include the analysis of different population groups' general health situations, monitoring of the incidence and prevalence of diseases in relation to the characteristics of the individuals affected, reimbursement, resource allocation, quality, and guidelines. The records provide the basis for the compilation of national mortality and morbidity statistics, and enable the storage and retrieval of diagnostic information for clinical epidemiological and quality purposes.
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The German National Cohort (NAKO) has been inviting men and women aged between 20 and 69 to 18 study centers throughout Germany since 2014. The participants are medically examined and questioned about their living conditions. The GNC’s aim is to investigate the causes of chronic diseases, such as cancer, diabetes, cardiovascular diseases, rheumatism, infectious diseases, and dementia in order to improve prevention, early diagnoses and treatment of these very widely spread diseases.
EM-DAT is a global database on natural and technological disasters, containing essential core data on the occurrence and effects of more than 22,000 disasters in the world, from 1900 to present. EM-DAT provides geographical, temporal, human and economic information on disasters at the country level. The database is compiled from various sources, including UN agencies, non-governmental organisations, insurance companies, research institutes and press agencies.
The European Mouse Mutant Archive – EMMA is a non-profit repository for the collection, archiving (via cryopreservation) and distribution of relevant mutant mouse strains essential for basic biomedical research. The laboratory mouse is the most important mammalian model for studying genetic and multi-factorial diseases in man. The comprehensive physical and data resources of EMMA support basic biomedical and preclinical research, and the available research tools and mouse models of human disease offer the opportunity to develop a better understanding of molecular disease mechanisms and may provide the foundation for the development of diagnostic, prognostic and therapeutic strategies.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.
CDC.gov is the Centers for Disease Control and Prevention primary online communication channel. CDC.gov provides users with credible, reliable health information on Data and Statistics, Diseases and Conditions, Emergencies and Disasters, Environmental Health, Healthy Living, Injury, Violence and Safety,Life Stages and Populations, Travelers' Health, Workplace Safety and Health
We are a leading international centre for genomics and bioinformatics research. Our mandate is to advance knowledge about cancer and other diseases, to improve human health through disease prevention, diagnosis and therapeutic approaches, and to realize the social and economic benefits of genomics research.
The Harvard Dataverse is open to all scientific data from all disciplines worldwide. It includes the world's largest collection of social science research data. It is hosting data for projects, archives, researchers, journals, organizations, and institutions.
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The Biobanque québécoise de la COVID-19 (BQC19) is a pan-provincial initiative that collects, stores and shares data and blood samples from COVID-19 patients, both severe and non-severe cases and control cases, in an effort to respond effectively to the public health challenges posed by the pandemic. BQC19 believes that better understanding the disease will help society in returning to social activities and in preparing for future pandemics. It sees access to high-quality samples and data as essential in fulfilling research and works to bring about national and international research collaborations.