Knowledge Organization Systems
Linked/Open Data quality
Spatial Data Infrastructure
Geographical Information Systems
Environmental Data Sharing and re-use
Digital Archive management
Monica De Martino is currently a researcher at CNR-IMATI-Genova. She graduated from the Department of Mathematics, University of Genova in 1992. She started her research activity on image processing and surface modeling as guest researcher at I.N.R.I.A. in Sophia Antipolis, France. Since 1993, she has been working at the IMATI in Genova on spatial data processing and analysis and their application within specific domains such as geographic information, environment, manufacturing and cultural heritage. Currently her research interests are in the fields of Knowledge Management and Spatial Data Infrastructure. Her expertise is on Metadata Analysis, methods for semantic similarity and granularity, Knowledge Organization System exploitation for multicultural/multilingual issue and Linked Data consumption. She has published extensively in high profile journals and conferences.
She has been involved in a lot of National and International Projects. In particular she has been the scientific responsible for CNR-IMATI of research projects funded by EU related to the Knowledge Management technology and its application within the geographic information context: eENVplus, NatureSDI, INVISIP, etc. The main outcomes of her activiies are:
- LusTRE - Linked Thesaurus fRamework for Environment (http://linkeddata.ge.imati.cnr.it/) It has been developed in order to support metadata compilation and data discovery. It provides a shared standard and scientific terms for a common understanding of environmental data among the different communities operating in the different field of the Environment through linked thesauri and a set of services for their exploitation in client application. It has been developed within two consecutive EU project NatureSDIplus and eENVplus.
- SSONDE- semantic similarity framework on LiNked Data Entities (https://purl.org/NET/SSONDE), is a open source framework providing an instance similarity enabling in a detailed comparison and ranking of resources through the comparison of their RDF ontology driven metadata.
- Linkset Quality metrics specifically designed to estimate how linksets affect the dataset integration. Linked data quality metrics address linkset completeness as a mean to estimate possible losses in completeness when fusing two datasets via their linkset.