Filter
Reset all

Subjects

Content Types

Countries

API

Data access

Data access restrictions

Database access

Database access restrictions

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 7 result(s)
The Scholarly Database (SDB) at Indiana University aims to serve researchers and practitioners interested in the analysis, modeling, and visualization of large-scale scholarly datasets. The online interface provides access to six datasets: MEDLINE papers, registered Clinical Trials, U.S. Patent and Trademark Office patents (USPTO), National Science Foundation (NSF) funding, National Institutes of Health (NIH) funding, and National Endowment for the Humanities funding – over 26 million records in total.
The data in the U of M’s Clinical Data Repository comes from the electronic health records (EHRs) of more than 2 million patients seen at 8 hospitals and more than 40 clinics. For each patient, data is available regarding the patient's demographics (age, gender, language, etc.), medical history, problem list, allergies, immunizations, outpatient vitals, diagnoses, procedures, medications, lab tests, visit locations, providers, provider specialties, and more.
Junar provides a cloud-based open data platform that enables innovative organizations worldwide to quickly, easily and affordably make their data accessible to all. In just a few weeks, your initial datasets can be published, providing greater transparency, encouraging collaboration and citizen engagement, and freeing up precious staff resources.
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.
!!! >>> merged with https://www.re3data.org/repository/r3d100012653 <<< !!! RDoCdb is an informatics platform for the sharing of human subjects data generated by investigators as part of the NIMH's Research Domain Criteria initiative, and to support this initiative's aims. It also accepts and shares appropriate data related to mental health from other sources.
This database contains individual-based life history data that have been collected from wild primate populations by nine working group participants over a minimum of 19 years.