Conference on a FAIR Data Infrastructure for Materials Genomics

Conference on a FAIR Data Infrastructure for Materials Genomics

3 - 5 June, 2020 I virtual meeting

In order to facilitate poster discussions, we need a fair amount of self-organization in order to match poster presenters and their audience. Besides the schedules Poster Sessions, presenters and attendees may contact eachother by E-Mail (see presenter's address at the bottom of the page) and will have access to a chat platform to discuss and to coordinate video calls.

  • Please register here in order to join the FAIRDI2020 team channel to meet and discuss your work among the participants.
  • Besides the official meeting rooms, participants are encouraged to organize video calls among themselves. A platform that works for small groups and without registration is Jitsi. For example via the FHI’s jitsi server: https://jitsi.fhi.mpg.de/

Poster Details

Poster: 45 | Presenter: Tatyana Sheveleva

STREAM Project: Semantic Representation, Networking and Curation of Quality Assured Material Data

Tatyana Sheveleva1, Javad Chamanara1, Sören Auer1

1 German National Library of Science and Technology (TIB) Leibniz Information Centre for Science and Technology and University Library

The STREAM project deals with the issue of digitizing material data and aims to establish a uniform FAIR compliant [1] implementation for the semantic representation, networking and curation of material data. Currently, there are different implementations based on different standards, methods, and structures. The FAIR conformity of material data is therefore difficult to achieve. The FAIR compliant implementation planned in STREAM is therefore beneficial, because it addresses several aspects of the FAIR conformity. It is general in itself and can be reused in further digitizing activities: Firstly, a uniform data structure in the form of an ontology is being developed to enable the semantic representation of material data. Secondly, a domain-specific maturity model [2] is being established to determine the quality of the material data and to improve if necessary. Furthermore, a mapping of the already existing heterogeneous material data is being applied to efficiently integrate the material data into multiple research data repositories. As a result, the intended FAIR conformity of the material data is achieved and the data is available for further research activities.

[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18.
[2] RDA FAIR Data Model Working Group, 2019-2020: Fair Data Maturity Model: specification and guidelines, DOI: 10.15497/rda00045.
 
Please contact the poster presenters via E-Mail: tatyana.sheveleva@tib.eu

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