Introducing ConnOSS - Connected Open-Source Software
Year: 2026
Type: article
Abstract: Our project Connected Open-Source Software (ConnOSS) aims at providing an infrastructure to automatically extract, enrich, and harmonize research software metadata. Building on existing efforts based on schema.org, such as CodeMeta and Bioschemas, and together with its extraction and enrichment metadata pipeline, ConnOSS will increase metadata coverage beyond direct extraction (e.g., from GitHub API or citation files). ConnOSS goals are summarized as follows:- reducing researcher effort, by automating metadata extraction, making it easier for research groups to align with good practices;- improving FAIRness, by providing high-quality, machine-actionable metadata, boosting the findability and overall FAIRness of the research software; and- facilitating aggregation, by enabling aggregators, knowledge graphs, and registries to easily access good quality metadata. Furthermore, the ConnOSS project emphasizes community support, providing adoption tutorials and corresponding training. The resulting extractors, AI models, and infrastructure, along with the extracted metadata provided also as a knowledge graph, will themselves adhere to FAIR and open-access practices. Visit ConnOSS webpage for more information, news, and latest developments, https://connoss-project.github.io/ This work is part of the deRSE26 - Conference for Research Software Engineering in Germany, see https://events.hifis.net/event/2945/contributions/21160/ ConnOSS is funded by the Deutsche Forschungsgemeinschaft (DFG) under grant number 561044496, as part of the "Research Data and Software" program within the Scientific Library Services and Information Systems (LIS) funding scheme.
Authors: Sefidbari, Maryam, Venkatesh, Suhasini, Gan, Lu, Jafarbigloo, Aida, Ferenz, Stephan, Mathiak, Brigitte, Nieße, Astrid, Werth, Oliver, Castro, Leyla Jael
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
Award: G7679809651
OpenAlex ID: W7133266595
FWCI:
Cites:
Cited by:
Related to:
