SIGDIUS Seminar - online -

May 6, 2020, 2:00 p.m. (CEST)

Time: 5/6/20, 2:00 p.m. – 4:00 p.m.
  This seminar will be a virtual meeting via Webex Teams. For participation, please send an e-mail to with the subject line "SIGDIUS seminar 6.5."
Download as iCal:

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 6 May 2020. Due to the current situation, this seminar will be held as an online seminar.  For participation, please send an e-mail to with the subject line "SIGDIUS seminar 6.5."

Heidi Seibold* (LMU München) will talk about "Research Software Engineers and Their Role for Open and Reproducible Research"

Many of the proposed solutions to the reproducibility crisis are technical solutions. Open and reproducible research require researchers to learn new technical skills. In this talk I will show some of the tools and strategies I use to make  my research open and reproducible. I argue that not all researchers can become experts in these tools and strategies. Instead we need research software engineers (RSEs) and reproducibility support.

Leonardo Gizzi (IMSB, Uni Stuttgart) will talk about "Treating neuromechanical data for reproducibility: the hard lesson I am learning"

* Heidi Seibold is a data science researcher and research software engineer. She believes that good research is reproducible, reusable and open and spends most of her time trying to improve the way we do research. She is a member of the LMU Open Science Center, a member of the Knowledge Exchange Open Scholarship expert group and a core member of OpenML. She teaches machine learning, R, and open and reproducible research. Heidi studied statistics at LMU Munich and did her PhD in computational Biostatistics at the University of Zurich. She worked as lead of the DIFUTURE analysis group, as deputy professor of biostatistics at LMU, and is currently working at LMU Munich, Bielefeld University and Helmholtz Zentrum München.

At the University of Stuttgart an increasing number of working groups want to comply with the FAIR Data Principles. Therefore they want to use a laboratory-information-management-system / electronic laboratory book (LIMS/ELN) for their experimental work or a documentation system for simulation work. Such systems are used for data integration and facilitate for example the connection of experimentally acquired data to the respective modelling environment.

The development of methods, standards and tools for research data management (RDM) is currently very dynamic; the scientific fields are fragmented in terms of processes and standards. This fragmentation is particularly evident in a number of about 300 existing LIMS/ELN products, which on the one hand offer very specific solutions for individual applications and on the other hand try to serve a broad spectrum of users. Under these conditions, it is difficult to select the appropriate RDM strategy.

April 2023

March 2023

February 2023

January 2023

December 2022

November 2022

October 2022

September 2022

July 2022

June 2022

May 2022

April 2022

March 2022

February 2022

January 2022

December 2021

November 2021

October 2021

September 2021

July 2021

June 2021

May 2021

April 2021

March 2021

February 2021

January 2021

December 2020

November 2020

October 2020

August 2020

July 2020

June 2020

May 2020

March 2020

February 2020

January 2020

December 2019

November 2019

October 2019

September 2019

July 2019

June 2019

May 2019

June 2019

November 2019

To the top of the page