10:00-12:30 Why Open Science is needed
We will start with an analysis of the current crisis in scientific communication to discuss the need for Open Science and the sharing of data and results as early and as openly as possible, in light of the lessons learned during the pandemic. We will look at Open Science practices and tools to open up every stage of research.
14:00-14:10 Greetings and welcome address
We will look specifically at the new Horizon Europe requirements on mandatory and recommended Open practices in the Methodology-Excellence section of the project proposal, the importance of FAIR data and the Data Management Plan for open and reproducible research.
Learn More09:15-11:00 FAIR data: key components and procedures
Data is becomming more and more important every day. In these context, a correct management and sharing of the data and of the procedures adopted, for the purpose of reuse, interoperability and reproducibility of the experiment (FAIR) becomes central. We will look at the main key components, in particular: data, metadata, datasets, standards and procedures, together with some examples of use of online Repositories.
11:15-12:00 Computational Ontologies, OWL/RDF and related technologies
The analysis of research data is one of the fundamental steps toward reproducibility and interoperability (FAIR) as it allows information to be structured through the definition of the semantic data model and related ontologies. The concepts of computational ontology (OWL) and coding through the RDF (Resource Description Framework) mode, a tool that enables the definition of structured data and guarantees semantic interoperabilty, will be introduced.
12:00-12:30 Introduction to MRI formats for Neuroimaging
An overview of the most popular data formats in the field of MRI neuroimaging (Dicom, Nifti, BIDS) and the tools used for their handling will be presented.
12:30-13:00 EEG-BIDS and MEG-BIDS for sharing neurophysiological data
An overview of the similarities and differences of the BIDS structures for EEG and MEG conceptualized to reflect the peculiarities of the two methods, will be presented along with an introduction to the software that allows exporting and importing data in this format and the repositories for EEG/MEG data sharing.
14:00-15:30 The Data Management Plan: a tool for responsible data management - Theory
The Data Management Plan (DMP) is becoming a more and more central 360°-thinking tool for the correct management of research data. We will see together the structure of a DMP and the information needed to compile it
Tudor Groza - EMBL-EBI Phenomics Team Lead Component of the International Mouse Phenotyping Consortium (https://www.mousephenotype.org/)
09:30-13:30 Cross-species phenotype knowledge representation and processing
General presentation on computational phenotyping ("phenomics") and FAIR data -covering topics such as: identifiers, ontologies and associated tooling, standards for phenotype data, cross-species phenotype data integration and clinical applications.
14:30-17:00 Use Case: International Mouse Phenotype Consortium
A particular use case: the architecture and tooling used by the Core Data Archive component of the International Mouse Phenotyping Consortium (https://www.mousephenotype.org/) - EBI, with concrete tooling used to manage FAIR data, including standardization process, data acquisition, ETL, handling imaging data and data releases.
09:15-13:30 e 14:30-17:00 FAIR Data to Boost Research and Diagnosis
Medical data and big data are becoming increasingly important in our society and in the scientific community and it is important to decrease data fragmentation and increase data quality by raising the level of capacities and help data sharing in a FAIR ecosystem. The day of the workshop titled "FAIR Data to Boost Research and Diagnosis", with the partecipation of national and international colleagues, will focus on FAIR guiding principles and the main steps of FAIRification that have aroused great interest in the scientific community. Partecipants will have the opportunity to view the potential and the importance of FAIR data within the Rare Disease Community. Moreover there is a time slot to discuss FAIR data management and FAIR project planning. International speakers from Elixir and the Department of Computer Science of the University of Turin will speak.
09:15-10:15 Platforms: from computation to reproducibility through data
The proper management and maintenance of the structures supporting FAIR data are a key element for the data to become linkable and machine readible, fitting into the already existing infrastructures at European level (Elixir).
The activities underway at the Computer Science Department for the realization of the infrastructure supporting FAIR data will be introduced: computing infrastructure (HPC4AI), tools supporting data reproducibility, experimentation with software repositories (Dataverse).