The I-ADOPT framework: The I-ADOPT framework is based on the I-ADOPT ontology designed to be used as a semantic broker between existing variable description models (including ontologies, taxonomies, and structured controlled vocabularies).
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.
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.
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.
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.
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.
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
Hackathons providing sandbox environments for practicing reproducible research. Use the Hub to organise events, submit papers for reproduction, record and feed back reviews
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.
Annif is an open source toolkit for automated subject indexing. It integrates several machine learning and AI based algorithms for text classification.
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.
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
"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
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.