Terminologies for ENVRIs: why, what and how

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TEACHERS

• Dr. Clement Jonquet (LIRMM, Univ. of Montpellier), PhD in Informatics, Associate Professor and former postdoc & visiting scholar at Stanford University, has 12-year experience in ontologies and semantic Web research applied to biomedicine and agronomy. He works on the design and development of ontology repositories, ontology-based services especially semantic annotation as the PI of ANR-JCJC & H2020-MSCA supported SIFR project (www.lirmm.fr/sifr), co-PI of ANR PractiKPharma (http://practikpharma.loria.fr) and PI of ANR D2KAB (www.d2kab.org). Since 2015, he gathers the national and international agronomy community around the AgroPortal initiative to build a reference vocabulary and ontology repository for agronomy, food and plant sciences.
• Barbara Magagna: holding a master degree in landscape planning and in geoinformatics has 14 years of experience in ontology engineering and process facilitation, abilities she could apply in several national and European semantic projects. She had been working for the University of Natural Resources and Applied Life Sciences, the University of Vienna and since December 2007 for the Environment Agency Austria (Umweltbundesamt GmbH) where she undertakes the function of a semantic analyst and database designer. She was involved in the development process of terminologies like SERONTO and EnvThes. She has experience as work package lead related to data management, in the design of UML models and XML schemas in the air quality data reporting area, in the design of semantic models in projects related to Environmental Research Infrastructures (ENVRI). She is now co-chairing the RDA Working Group I-ADOPT which aims at producing an interoperability framework for the semantic representation of observable properties.
• Markus Stocker: Markus leads the Knowledge Infrastructures research group at the TIB Leibniz Information Centre for Science and Technology. He holds a PhD in Environmental Informatics from the University of Eastern Finland; a MSc in Environmental Science from the University of Eastern Finland; and a Diploma (MSc) in Informatics from the University of Zurich, Switzerland. His research interests lie at the intersection between research infrastructures and research communities, and how such infrastructures acquire, maintain, and share scientific knowledge about human and natural worlds. Prior to TIB, he held a postdoctoral research associate position at PANGAEA, the Data Publisher for Earth & Environmental Science, at the MARUM Center for Marine Environmental Sciences, University of Bremen, Germany. As a member of the Research Data Alliance (RDA), he is involved in various groups, in particular the WG Persistent Identification of Instruments.

TARGET GROUPS

Data center staff (IT people with good grasp of metadata as such, but much less knowledge of ontologies, linked open data, vocabularies etc.)

COURSE GOAL

The course will give a good introduction into ontologies and how these can help “putting the I into FAIR”. Participants will understand key concepts of the Semantic Web and knowledge representation techniques and see different examples of ontology & vocabulary portals. The course will cover all ENVRI-FAIR sub-domains (atmosphere, marine, solid earth, and terrestrial ecosystem/biodiversity).

COURSE CONTENT

We will introduce the basics about terminologies and the Semantic Web, covering:
– The semantic gradient (taxonomies, thesauri, ontologies)
– Knowledge representation languages (RDFS, OWL)
– Basic features of terminologies (classes, properties, assertions, etc.)
– Lightweight exercise in Protégé (building a small environmental terminology)

Next, we present how to use ontologies (or other semantic resources) through domain specific ontology repositories such as BioPortal/AgroPortal/EcoPortal. We will cover:
– Ontology selection and recommendation
– How to use an ontology in the repository
– Semantic annotation of text data
– Ontology alignements management
– Automatic access to ontologies within the repositories (SPARQL & REST)