If Knowledge Extraction and Knowledge Management are to serve people and workers, then the semantic web research has to include more cooperative principles in knowledge sharing and reuse.
Can you tell something about your work/research focus?
My research focus deals with various methodological and technical issues related to knowledge extraction from text and ontology engineering. After many years of collaborations with linguists and terminologists, I work more with colleagues with a machine learning background in order to build tools for relation extraction from text. We are trying to identify efficient techniques for each type of structure in texts (tables, item lists, titles etc) and to use them in a complementary way.
Which trends and challenges you see for linked data/semantic web?
The challenge for linked data is being able to scale up the tagging task using meta-data. Another challenge is to promote techniques that ensure the trust and reliability of data. This issue arises when extracting data from text too. Companies are expecting a lot from data reuse and they must trust the data they use when needed.
What are your expectations about Semantics 2017 in Amsterdam?
Semantics is a special conference with a double scope including research and innovation in companies. I wish I could meet people from companies that will share their feedback from using or producing linked data, or applications based on this data. I wish I could meet people interested in text-based applications. Advances in Semantic Web research are closely depending on the evolvement of a large community including companies. So another expectation is to see innovative applications that could provide services to a large set of people.
And one question especially for you: your research is about knowledge engineering and management, where does this end?
The frontiers of KE and KM have been evolving over the years, in particular because knowledge, intelligence and problem solving did not mean the same in sofware applications. I am convinced that it will go on changing. Knowledge is now hidden in almost any application. Yet we moved from explicit and declarative rules to implicit knowledge learned from large data sets. So if KE and KM are to serve people and workers, then the semantic web research has to include more cooperative principles in knowledge sharing and reuse.