WS3
The third EERAdata Workshop will take place between 11 and 15 October 2021.
Objectives of WS3 will be the following:
- Characterize data for the implementation of FAIR and open principles
- Develop a workflow for the general approach to the FAIRification and opening of databases.
- Community paper on relevance of FAIR data for the energy communities and how AI technologies can support workflows
A preparatory workshop has been planned.
Preparatory workshop
Preparatory workshop is planned for 6th of July 2021. It is part of a series of workshops dedicated to the FAIRification and opening of energy research data in and with the low carbon energy research community. Workshop will take the form of an online discussion with invited talks and a panel discussion.
Gathering 40 participants, this EERAdata online discussion focused on the state of the art and needs for data management and workflows through best-practice lectures about the organisation of the FAIRification processes. The workshop is part of the the third EERAdata workshop which continue in October.
Agenda
| 6th July, 10-12 CET | Agenda
Registration link: Link |
|---|---|
| 10:00 - 10:05 | Welcome and introduction, Massimo Celino (ENEA) |
| 10:05 - 10:20 | FAIR data collective, Nikola Vasiljevic, (DTU Wind Energy, GOFAIR Facilitator Team) |
| 10:20-10:35 | FAIR data resources - examples from the life sciences, Susanna-Assunta Sansone, (University of Oxford) |
| 10:35-10:50 | Data management in the BIG-MAP project and its relation with the BATTERY 2030+ community, Ivano Castelli, (DTU Energy) |
| 10:50-11:00 | Break |
| 11:00-11:15 | From energy community principles to the EERAdata platform, Manfred Paier (AIT) |
| 11:15-12:00 | Panel discussion with Q&A |
Objective
The objective of the online discussion is to prepare the 3rd EERAdata community workshop. In this workshop participants explore use cases to:
- manage the implementation of FAIR and open principles,
- identify and test workflows for the FAIRification and opening of databases, and
- collaborate on a community paper “AI & data-driven science for the energy transition”.
