SIGDIUS Seminar - online - 2pm

July 12, 2023, 2:00 p.m. (CEST)

Time: July 12, 2023, 2:00 p.m. (CEST)
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The Special Interest Group Data Infrastructure offers a forum to interested working groups that want to set up or further develop an RDM infrastructure at working group or institute level. We invite you to a monthly SIGDIUS seminar, to which we invite internal and external experts for presentations and discussions. SIGDIUS members will have the opportunity to exchange their experiences with concrete RDM infrastructures.

We cordially invite all interested parties to our next meeting on 12 July 2023 at 2 pm. This seminar will be held as an online seminar. For participation, please send an e-mail to Juergen.Pleiss@itb.uni-stuttgart.de.

Gustavo Durand
(Harvard University)
Dataverse software - new features and future plans

In this presentation, we will talk about the Dataverse project, an open-source platform to publish, cite, and archive research data and the Community that supports it. We will then discuss some of the features that have been developed for Dataverse within the past year, as well as what is currently being worked on and planned for this upcoming year and beyond.

Hamza Oukili
(SFB1313 / University of Stuttgart)
RDM and RSEng in the SFB1313

The Information Infrastructure Project (INF-SFB1313) is dedicated to ensuring compliance with the FAIR principles, specifically in relation to research data and software generated by the CRC1313. Our efforts are focused on making the data Findable, Accessible, Interoperable, and Reusable. With regards to research data and the institutional data repository DaRUS (built on Dataverse), we provide assistance in automating the upload process for data and metadata, as well as expanding the capabilities for analyzing and reproducing stored simulation results. We prioritize the standardization of workflows for data management and software engineering activities. By enhancing existing software development processes, we strive to enhance the quality of the software as a research output. To ensure and monitor this quality, we incorporate automated testing and continuous integration practices. Additionally, we aim to improve software interoperability and reusability by developing interfaces that connect smaller software projects to well-established packages or integrating them directly. Our evaluation of continuous integration practices has involved the inclusion of code analyzers in the development pipeline. We have also established collaborations both within the project and with external partners to explore various possibilities for software and data implementation. Through these efforts, we aim to drive the advancement of research data and software engineering practices while adhering to FAIR principles.

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