Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Data access

Data access restrictions

Database access

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 14 result(s)
The CiardRING is a global directory of web-based information services and datasets for agricultural research for development (ARD). It is the principal tool created through the CIARD initiative to allow information providers to register their services and datasets in various categories and so facilitate the discovery of sources of agriculture-related information across the world. The RING aims to provide an infrastructure to improve the accessibility of the outputs of agricultural research and of information relevant to agriculture.
RAVE (RAdial Velocity Experiment) is a multi-fiber spectroscopic astronomical survey of stars in the Milky Way using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO). The RAVE collaboration consists of researchers from over 20 institutions around the world and is coordinated by the Leibniz-Institut für Astrophysik Potsdam. As a southern hemisphere survey covering 20,000 square degrees of the sky, RAVE's primary aim is to derive the radial velocity of stars from the observed spectra. Additional information is also derived such as effective temperature, surface gravity, metallicity, photometric parallax and elemental abundance data for the stars. The survey represents a giant leap forward in our understanding of our own Milky Way galaxy; with RAVE's vast stellar kinematic database the structure, formation and evolution of our Galaxy can be studied.
MGnify (formerly: EBI Metagenomics) offers an automated pipeline for the analysis and archiving of microbiome data to help determine the taxonomic diversity and functional & metabolic potential of environmental samples. Users can submit their own data for analysis or freely browse all of the analysed public datasets held within the repository. In addition, users can request analysis of any appropriate dataset within the European Nucleotide Archive (ENA). User-submitted or ENA-derived datasets can also be assembled on request, prior to analysis.
CERN, DESY, Fermilab and SLAC have built the next-generation High Energy Physics (HEP) information system, INSPIRE. It combines the successful SPIRES database content, curated at DESY, Fermilab and SLAC, with the Invenio digital library technology developed at CERN. INSPIRE is run by a collaboration of CERN, DESY, Fermilab, IHEP, IN2P3 and SLAC, and interacts closely with HEP publishers, arXiv.org, NASA-ADS, PDG, HEPDATA and other information resources. INSPIRE represents a natural evolution of scholarly communication, built on successful community-based information systems, and provides a vision for information management in other fields of science.
The Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. DisProt is a community resource annotating protein sequences for intrinsically disorder regions from the literature. It classifies intrinsic disorder based on experimental methods and three ontologies for molecular function, transition and binding partner.
The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical state, variability and dynamics of the ocean and marine ecosystems for the global ocean and the European regional seas. The observations and forecasts produced by the service support all marine applications, including: Marine safety; Marine resources; Coastal and marine environment; Weather, seasonal forecasting and climate. For instance, the provision of data on currents, winds and sea ice help to improve ship routing services, offshore operations or search and rescue operations, thus contributing to marine safety. The service also contributes to the protection and the sustainable management of living marine resources in particular for aquaculture, sustainable fisheries management or regional fishery organisations decision-making process. Physical and marine biogeochemical components are useful for water quality monitoring and pollution control. Sea level rise is a key indicator of climate change and helps to assess coastal erosion. Sea surface temperature elevation has direct consequences on marine ecosystems and appearance of tropical cyclones. As a result of this, the service supports a wide range of coastal and marine environment applications. Many of the data delivered by the service (e.g. temperature, salinity, sea level, currents, wind and sea ice) also play a crucial role in the domain of weather, climate and seasonal forecasting.
B2SHARE is a user-friendly, reliable and trustworthy way for researchers, scientific communities and citizen scientists to store and share small-scale research data from diverse contexts and disciplines. B2SHARE is able to add value to your research data via (domain tailored) metadata, and assigning citable Persistent Identifiers PIDs (Handles) to ensure long-lasting access and references. B2SHARE is one of the B2 services developed via EUDAT and long tail data deposits do not cost money. Special arrangements such as branding and special metadata elements can be made on request.
The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature.
The CESSDA Data Catalogue contains the metadata of all data in the holdings of CESSDA service providers. It is a one-stop-shop for search and discovery, enabling effective access to European research data for researchers. Details of over 40, 000 data collections are listed. These are harvested from fifteen different CESSDA Service Providers.
GWAS Central (previously the Human Genome Variation database of Genotype-to-Phenotype information) is a database of summary level findings from genetic association studies, both large and small. We actively gather datasets from public domain projects, and encourage direct data submission from the community.
ZENODO builds and operates a simple and innovative service that enables researchers, scientists, EU projects and institutions to share and showcase multidisciplinary research results (data and publications) that are not part of the existing institutional or subject-based repositories of the research communities. ZENODO enables researchers, scientists, EU projects and institutions to: easily share the long tail of small research results in a wide variety of formats including text, spreadsheets, audio, video, and images across all fields of science. display their research results and get credited by making the research results citable and integrate them into existing reporting lines to funding agencies like the European Commission. easily access and reuse shared research results.
InterPro collects information about protein sequence analysis and classification, providing access to a database of predictive protein signatures used for the classification and automatic annotation of proteins and genomes. Sequences in InterPro are classified at superfamily, family, and subfamily. InterPro predicts the occurrence of functional domains, repeats, and important sites, and adds in-depth annotation such as GO terms to the protein signatures.
The PRIDE PRoteomics IDEntifications database is a centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. PRIDE encourages and welcomes direct user submissions of mass spectrometry data to be published in peer-reviewed publications.
BBMRI-ERIC is a European research infrastructure for biobanking. We bring together all the main players from the biobanking field – researchers, biobankers, industry, and patients – to boost biomedical research. To that end, we offer quality management services, support with ethical, legal and societal issues, and a number of online tools and software solutions. Ultimately, our goal is to make new treatments possible. The Directory is a tool to share aggregate information about the biobanks that are willing external collaboration. It is based on the MIABIS 2.0 standard, which describes the samples and data in the biobanks at an aggregated level.