| Time: | June 2, 2021, 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 2 June 2021 at 2pm. Due to the current situation, this seminar will be held as an online seminar. For participation, please send an e-mail to Juergen.Pleiss@itb.uni-stuttgart.de with the subject line "SIGDIUS seminar 2.6."
Thomas Wortmann (ICD, University of Stuttgart):
"openBIM vs. Open Source in the Architecture, Engineering and Construction industry"
Interoperability, i.e., exchanging data across different file formats and software is an ongoing concern in the Architecture, Engineering and Construction (AEC) industry. The ongoing digitization of the AEC industry increases the need for this interoperability and presents new opportunities and challenges. The Cluster of Excellence Integrative Computational Design and Construction for Architecture (IntCDC) is a laboratory for developing and testing new interoperability approaches that support co-design and integrate digital fabrication constraints and allow the application of machine learning and other artificial intelligence methods. In this talk, I will present the Industry Foundation Classes (IFC) as the current interoperability paradigm of openBIM, problems with this approach, as well as an emergent alternative rooted in community-based, open-source development.
Hannah Dienhart (IBTB, University of Stuttgart):
"Management of research data workflows by Jupyter Notebook"
Alongside the rise of the FAIR principles, formats to manage and store research data emerge. Workflow scenarios can facilitate and encourage the use of these formats. I will demonstrate such a workflow scenario in a Jupyter Notebook for the data format EnzymeML.