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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.
DaSCH is the trusted platform and partner for open research data in the Humanities. DaSCH develops and operates a FAIR long-term repository and a generic virtual research environment for open research data in the humanities in Switzerland. We provide long-term direct access to the data, enable their continuous editing and allow for precise citation of single objects within a dataset. We ensure interoperability with tools used by the Humanities and Cultural Sciences communities and foster the use of standards. The development of our platform happens in close cooperation with these communities. We provide training and advice in the area of research data management, promote open data and the use of standards. DaSCH is the coordinating institution and representative of Switzerland in the European Research Infrastructure Consortium ‘Digital Research Infrastructure for the Arts and Humanities’ (DARIAH ERIC). Within this mandate, we actively engage in community building within Switzerland and abroad. DaSCH cooperates with national and international organizations and initiatives in order to provide services that are fit for purpose within the broader Swiss open research data landscape and that are coordinated with other institutions such as FORS. We base our actions on the values reliability, flexibility, appreciation, curiosity, and persistence. Furthermore, DARIAH’s activities in Switzerland are coordinated by DaSCH and DaSCH is acting as DARIAH-CH Coordination Office.
For datasets big and small; Store your research data online. Quickly and easily upload files of any type and we will host your research data for you. Your experimental research data will have a permanent home on the web that you can refer to.
The Genomic Observatories Meta-Database (GEOME) is a web-based database that captures the who, what, where, and when of biological samples and associated genetic sequences. GEOME helps users with the following goals: ensure the metadata from your biological samples is findable, accessible, interoperable, and reusable; improve the quality of your data and comply with global data standards; and integrate with R, ease publication to NCBI's sequence read archive, and work with an associated LIMS. The initial use case for GEOME came from the Diversity of the Indo-Pacific Network (DIPnet) resource.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.