MEchanics GAthering –MEGA- Seminar: On the necessity of curation for datasets to achieve FAIR standard goals in scientific publications

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Event details

Date 11.04.2024
Hour 16:1517:15
Speaker Guillaume Anciaux (LSMS, EPFL)
Location Online
Category Conferences - Seminars
Event Language English
Abstract: Academic knowledge is traditionally disseminated by academic journals. However, nowadays, the production of scientific data in any given project exceeds by a vast amount what can be contained in a few journal pages. Reproducible scientific data and publications must be associated to boost scientific collaborations and discoveries. There is today an always increasing pressure coming from universities and funding institutions towards publishing open data, despite the important workload it represents. Thus far, only limited solutions/tools to curate and share data produced by experiments and simulations. At large, this situation does not favor open science.
In this presentation, I will start with a small history of the academic press, up to the diamond open access principles and the role that can be played by scientists themselves. Naturally the evolution of practices towards digitization and computational disciplines will bring us to consider datasets.  The possibilities and the rather limited curative requirements for datasets in generalist repositories such as Zenodo will be detailed.
I also will present the recent initiative of the overlay diamond open access "Journal of Theoretical, Computational and Applied Mechanics" towards the curation of the datasets accompanying published paper. Just like for the paper review procedure, it is believed that datasets can only become valuable when correctly cleaned, annotated, documented and proved with minimal reproducibility. The JTCAM could make this move thanks to the Dissemination of Computational Solid Mechanics (DCSM) project, which aimed at developing a web platform and an open-source software (Solidipes) to support scientists when curating and publishing their datasets. Such a platform will be briefly presented and illustrated with show case papers+datasets.
Finally, the ideal curation framework will be sketched. In particular, the need for specific ontologies, describing the relational hierarchy between objects, will be linked with robust and simplified recognition/validation procedures. In other terms, a normalization of the (discipline dependent) scientific community output is called for. While this certainly represents an important amount of work, it has the potential of reducing the workload for dataset curators, which is a sine qua non condition to convince dataset reviewers to highlight our digital production.

Bio: Guillaume Anciaux got his master's from the Graduate School in Electronics, Computer Sciences, Telecommunications, Mathematics and Mechanics (ENSEIRB-MATMECA), Bordeaux, France, with a Computer Science degree in 2003.  Then, he started his PhD in 2003 with Prof. Coulaud and Prof. Roman in the High Performance Computing team ScAlApplix at INRIA (Bordeaux, France). His Ph.D work focused on multiscale concurrent coupling methods to bridge molecular dynamics with finite elements. He then joined the team of J.F. Molinari at EPFL, where he explored computational solid mechanics, for various scales, models, and computing architecture. In particular, contact mechanics, tribology, and material defects were topics he contributed to during the past decade. More recently, G. Anciaux worked on promoting Open Research Data to mechanics disciplines. For instance he got involved in the editorial board of the Diamond Open Access journal JTCAM, with the goal to introduce dataset curation to the publishing procedure of the JTCAM.
 

Practical information

  • General public
  • Free

Organizer

  • MEGA.Seminar Organizing Committee

Tags

curation datasets FAIR diamond open access

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