VIMMP provides an easily accessible, user-friendly hub to access all tangible and intangible components, such as information, knowledge, services and tools to support the efficient decision making, uptake and effective use of materials. At the core of VIMMP will be a metadata enriched data environment that eases the tasks of all actors. In particular it will facilitate the translation of a scientific problem into modelling workflows, ready for simulation using a range of software tools integrated into an open simulation platform and deployed on cloud services. The VIMMP platform is open, so that any provider can easily integrate and deploy their software codes as well as services.
Status: Recognised & Endorsed The Metadata IG will concern itself with all aspects of metadata for research data. In particular it will attempt to coordinate the efforts of the WGs concerned with metadata to produce a coherent approach to metadata covering metadata modalities of description, restriction, navigation, provenance, preservation and the use of metadata for the purposes discovery, contextualisation, validation, analytical processing, simulation, visualisation and interoperation. It will also liaise with the other WGs especially Data Foundation and Terminology, PIDs, Standardisation of data categories and codes and Data Citation. This IG activity relates to data management policies and plans of research organisations and researchers, and to policies and standards of research funders and of research communities which may or may not be official standards.
Im Onlineportal finden Nutzerinnen und Nutzer zunächst die bereits bekannten Leitlinien und ihre Erläuterungen. Neu hinzu kommen nun allgemeine und fachspezifische Kommentierungen, Fallbeispiele, eine Übersicht über häufig gestellte Fragen, Verweise auf Gesetze und andere Normen, zugehörige DFG-Stellungnahmen sowie externe Quellen. Für die Nutzerinnen und Nutzer des Portals existieren verschiedene Such- und Zugangsmodi. Eine englische Fassung soll 2021 freigeschaltet werden.
"Open-source Dropbox" with added description features. It is a data storage and description platform designed to help researchers and other users to describe their data files, built on Linked Open Data and ontologies. Users can use Dendro to publish data to CKAN, Zenodo, DSpace or EUDAT's B2Share and others. - feup-infolab/dendro
Slides give an overview over the actual situation of AAI and the used technologies (SAML, OAuth) and implementations (Shibboleth, ...) and outlook to a possible future
This document describes RML, a generic mapping language, based on and extending [R2RML]. The RDF Mapping language (RML) is a mapping language defined to express customized mapping rules from heterogeneous data structures and serializations to the RDF [RDF-CONCEPTS] data model. RML is defined as a superset of the W3C-standardized mapping language [R2RML], aiming to extend its applicability and broaden its scope, adding support for data in other structured formats. [R2RML] is the W3C standard to express customized mappings from relational databases to RDF. RML follows exactly the same syntax as R2RML; therefore, RML mappings are themselves RDF graphs. The present document describes the RML language and its concepts through definitions and examples.
Annif is an open source toolkit for automated subject indexing. It integrates several machine learning and AI based algorithms for text classification.
Decentralized identifiers (DIDs) are a new type of identifier that enables verifiable, decentralized digital identity. A DID refers to any subject (e.g., a person, organization, thing, data model, abstract entity, etc.) as determined by the controller of the DID. In contrast to typical, federated identifiers, DIDs have been designed so that they may be decoupled from centralized registries, identity providers, and certificate authorities. Specifically, while other parties might be used to help enable the discovery of information related to a DID, the design enables the controller of a DID to prove control over it without requiring permission from any other party. DIDs are URIs that associate a DID subject with a DID document allowing trustable interactions associated with that subject.
Hackathons providing sandbox environments for practicing reproducible research. Use the Hub to organise events, submit papers for reproduction, record and feed back reviews
scholaraly infrastructure to provide access to global scholarly bibliographic and citation data with full provenance (where, wen, who of the source data + change tracking)
Data provided under CC0
Omeka is a free, flexible, and open source web-publishing platform for the display of library, museum, archives, and scholarly collections and exhibitions. Its five-minute setup makes launching an online archive or exhibition as easy as launching a blog.
FAIR-IMPACT identifies practices, policies, tools and technical specifications to guide researchers, repository managers, research performing organisations, policy makers and citizen scientists towards a FAIR data management cycle. The focus is on persistent identifiers (PIDs), metadata, ontologies, metrics, certification and interoperability, starting with real-life use cases on social sciences and humanities, the photon and neutron sciences, life sciences and agri-food and environmental sciences.
The Library of Congress and its digital preservation partners from the federal, library, creative, publishing, technology, and copyright communities are working to develop a national strategy to collect, archive, and preserve digital content.
Home page for Library of Congress Recommended Formats Statement (RFS). RFS identifies analog and digital formats suitable for the large-scale acquisition of and long-term access to library collections. The identified formats have been selected to maximize the preservation and accessibility of creative content into the future.
Ein bedeutendes neues Handlungsfeld der Forschung, welches im Zuge der Digitalisierung entstanden ist, ist das Management von digitalen Forschungsdaten. Wissenschaftler*innen benötigen für ein nachhaltiges Forschungsdatenmanagement (FDM) neben Kenntnissen und Fähigkeiten im fachlichen Bereich zusätzliche Kompetenzen im Umgang mit digitalen Daten. Die Vermittlung dieser Kenntnisse sollte idealerweise bereits im Studium erfolgen. Zudem besteht ein steigender Bedarf an forschungsunterstützendem Personal, z.B. in Form von Data Stewards, der nur über geeignete Aus- und Weiterbildungsmaßnahmen gedeckt werden kann. Die vorliegende Lernzielmatrix fasst für das FDM relevante Vermittlungsinhalte sowie zugehörige Lernziele auf den Qualifikationsstufen Bachelor, Master, PhD und Data Steward aus einer Reihe von nationalen wie internationalen Projekten und Fortbildungskonzepten zum Themenbereich FDM in einheitlicher Form zusammen und bietet Nachnutzenden eine Orientierungshilfe für die Identifikation von relevanten Inhaltsaspekten sowie eine Arbeitsgrundlage, etwa für eine erweiterte fach- oder veranstaltungsspezifische Ausgestaltung. Die Lernzielmatrix entstand im Rahmen der DINI/nestor AG Forschungsdaten UAG Schulungen/Fortbildungen unter Einbezug externer Kolleg*innen.