Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Certificates

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 13 result(s)
META-SHARE, the open language resource exchange facility, is devoted to the sustainable sharing and dissemination of language resources (LRs) and aims at increasing access to such resources in a global scale. META-SHARE is an open, integrated, secure and interoperable sharing and exchange facility for LRs (datasets and tools) for the Human Language Technologies domain and other applicative domains where language plays a critical role. META-SHARE is implemented in the framework of the META-NET Network of Excellence. It is designed as a network of distributed repositories of LRs, including language data and basic language processing tools (e.g., morphological analysers, PoS taggers, speech recognisers, etc.). Data and tools can be both open and with restricted access rights, free and for-a-fee.
EBRAINS offers one of the most comprehensive platforms for sharing brain research data ranging in type as well as spatial and temporal scale. We provide the guidance and tools needed to overcome the hurdles associated with sharing data. The EBRAINS data curation service ensures that your dataset will be shared with maximum impact, visibility, reusability, and longevity, https://ebrains.eu/services/data-knowledge/share-data. Find data - the user interface of the EBRAINS Knowledge Graph - allows you to easily find data of interest. EBRAINS hosts a wide range of data types and models from different species. All data are well described and can be accessed immediately for further analysis.
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.
ICOS Carbon Portal is the data portal of the Integrated Carbon Observation System. It provides observational data from the state of the carbon cycle in Europe and the world. The Carbon Portal is the data center of the ICOS infrastructure. ICOS will collect greenhouse gas concentration and fluxes observations from three separate networks, all these observations are carried out to support research to help us understand how the Earth’s greenhouse gas balance works, because there are still many and large uncertainties!
ForestPlots.net is a web-accessible secure repository for forest plot inventories in South America, Africa and Asia. The database includes plot geographical information; location, taxonomic information and diameter measurements of trees inside each plot; and participants in plot establishment and re-measurement, including principal investigators, field assistants, students.
Cocoon "COllections de COrpus Oraux Numériques" is a technical platform that accompanies the oral resource producers, create, organize and archive their corpus; a corpus can consist of records (usually audio) possibly accompanied by annotations of these records. The resources registered are first cataloged and stored while, and then, secondly archived in the archive of the TGIR Huma-Num. The author and his institution are responsible for filings and may benefit from a restricted and secure access to their data for a defined period, if the content of the information is considered sensitive. The COCOON platform is jointly operated by two joint research units: Laboratoire de Langues et civilisations à tradition orale (LACITO - UMR7107 - Université Paris3 / INALCO / CNRS) and Laboratoire Ligérien de Linguistique (LLL - UMR7270 - Universités d'Orléans et de Tours, BnF, CNRS).
Content type(s)
MatDB is a database application for experimentally measured engineering materials data. It supports open, registered, and restricted access. It presently hosts more than 20.000 unique data sets coming mainly from European and Member State research programmes. It supports web interfaces for entering, browsing, and retrieving data. MatDB is also enabled for innovative services, including data citation and interoperability standards. The data citation service relies on DataCite DOIs. The historic data sets are being enabled for citation. For all new projects where MatDB is used for managing project data, end-users are encouraged to request DataCite DOIs. There is though no obligation as regards the access level as it is considered sufficient simply that the data sets are made discoverable through data citation. The service that relies on interoperability standards leverages the outputs from a series of CEN Workshops that aim to deliver Standards-compliant data formats for engineering materials data. In this context, MatDB is used to validate and demonstrate said formats with a view to promoting their adoption. MatDB is part of the ODIN Portal https://odin.jrc.ec.europa.eu/alcor/
The goal of the Center of Estonian Language Resources (CELR) is to create and manage an infrastructure to make the Estonian language digital resources (dictionaries, corpora – both text and speech –, various language databases) and language technology tools (software) available to everyone working with digital language materials. CELR coordinates and organises the documentation and archiving of the resources as well as develops language technology standards and draws up necessary legal contracts and licences for different types of users (public, academic, commercial, etc.). In addition to collecting language resources, a system will be launched for introducing the resources to, informing and educating the potential users. The main users of CELR are researchers from Estonian R&D institutions and Social Sciences and Humanities researchers all over the world via the CLARIN ERIC network of similar centers in Europe. Access to data is provided through different sites: Public Repository https://entu.keeleressursid.ee/public-document , Language resources https://keeleressursid.ee/en/resources/corpora, and MetaShare CELR https://metashare.ut.ee/
The FAIRDOMHub is built upon the SEEK software suite, which is an open source web platform for sharing scientific research assets, processes and outcomes. FAIRDOM (Web Site) will establish a support and service network for European Systems Biology. It will serve projects in standardizing, managing and disseminating data and models in a FAIR manner: Findable, Accessible, Interoperable and Reusable. FAIRDOM is an initiative to develop a community, and establish an internationally sustained Data and Model Management service to the European Systems Biology community. FAIRDOM is a joint action of ERA-Net EraSysAPP and European Research Infrastructure ISBE.
Content type(s)
Scicat allows users to access the metadata of raw and derived data which is taken at experiment facilities. Scientific datasets are linked to proposals and samples. Scientific datasets are can be linked to publications (DOI, PID). SciCat helps keeping track of data provenance (i.e. the steps leading to the final results). Scicat allows users to find data based on the metadata (both your own data and other peoples’ public data). In the long term, SciCat will help to automate scientific analysis workflows.
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.
FORS is the Swiss Centre of Expertise in the Social Sciences. FORS maintains a national digital archive for social science research data, implements large-scale national and international surveys, offers data and research information services to researchers and academic institutions, and conducts methodological and thematic research. FORS Data Service is FORS’ resource centre for research and teaching in the social sciences. It provides data management support and training, and it archives, disseminates and promotes quantitative and qualitative data. The Data Service maintains a comprehensive and up-to-date inventory of social science research projects in Switzerland, and makes available a wide range of datasets for secondary analysis. Databases at the FORS Data Service are: SWISSUbase and DeVisu (for variable level metadata for important surveys).
Launched in December 2013, Gaia is destined to create the most accurate map yet of the Milky Way. By making accurate measurements of the positions and motions of stars in the Milky Way, it will answer questions about the origin and evolution of our home galaxy. The first data release (2016) contains three-dimensional positions and two-dimensional motions of a subset of two million stars. The second data release (2018) increases that number to over 1.6 Billion. Gaia’s measurements are as precise as planned, paving the way to a better understanding of our galaxy and its neighborhood. The AIP hosts the Gaia data as one of the external data centers along with the main Gaia archive maintained by ESAC and provides access to the Gaia data releases as part of Gaia Data Processing and Analysis Consortium (DPAC).