Category: Newsletter

Updates from Golo – Data Quality Metrics Website

ield experiments mostly take place under difficult conditions. Due to the large number of sensors and computers, large amounts of data are usually generated, and data acquisition can be affected by small errors or external events. For further processing and analysis of field data, verification of data quality is essential. To assist researchers, TA Golo has documented a website – the Data Quality Metrics Website.

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Guidelines for Text and Data Mining for research purposes in Germany completed!

The recently published “Guidelines zum Text und Data Mining für Forschungszwecke in Deutschland” describe under which conditions text and data mining may be carried out for scientific purposes and what risks exist. An online workshop, “Urheberrechtliche Fragestellungen bei der Gestaltung von Dienstleistungen zum Text und Data Mining” will take place on April 25th to address copyright issues in designing services to support text and data mining.

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ing.grid: Open Access, Open Peer Review, Open Science

The international online journal ing.grid is now accepting submissions addressing FAIR data management in engineering sciences. With an open access policy, the journal bridges a gap in the field, offering a platform and recognition for sound scientific practice in generating research data, developing reusable tools for processing that data and curating the data to make it findable, accessible, interoperable, and reusable (FAIR).

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NFDI4Ing Awards 2022

It was a close contest, but in the end two nominees prevailed in the NFDI4Ing Awards 2022 against 41 other contributors. We happily congratulate the winners, Wendy (Pengyin) Shan from the University of Alberta Library in Canada, and Rory Macneil from Edinburgh, Scotland. The awards were endowed with 500€ each, sponsored by the WZL Aachen Stiftung.

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Final report: NFDI4Ing Seed Fund OntoHuman

Manual development and maintenance of ontologies are tedious tasks and require extra training to use ontology modelling tools. Therefore, a semi-automatic process to enrich ontologies can assist domain experts, who are not necessarily ontology experts, to map knowledge into ontologies. OntoHuman pursues a Human-in-the-Loop (HiL) approach to address this, which requires humans to provide feedback to an automated system for information extraction from technical documents.

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Towards a standardized research data management

In recent years, concepts, tools and services have been developed that enable good research data management. However, in most disciplines there are not yet any established standards. See how we want to solve this issue for the community.

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