Table of Contents
Franck Michel
Université Côte d’Azur, CNRS, Inria.
I am a CNRS research engineer involved in the integration of heterogeneous data and their publication and sharing as Knowledge Graphs on the Web, using knowledge engineering, the Semantic Web and Linked Open Data technologies.
I am a member of I3S laboratory's SPARKS group, and a member of Inria's Wimmics team.
Research activities
Knowledge Graphs, Integration of Heterogeneous Data
I am involved in research activities meant to enable the integration of heterogeneous data based on a knowledge engineering approach, as well as the sharing and reuse of these data. My work addresses several research questions:
- How to build FAIR Knowledge Graphs complying with the Linked Data 4-star principles?
- How to overcome data structural and semantic heterogeneity in order to reconcile and make sense of large data sets distributed at Web-scale?
- How to foster data reuse by publishing them in machine-processable formats? This work is concerned with leveraging the Linked Data principles to integrate heterogeneous legacy data sources and make them available in the Web of Data. This was the main topic of my Ph.D that I defended in 2017, with a specific focus on the translation of data from NoSQL databases into RDF.
- How to enable the Web-scale discovery and consumption of data? This work is concerned with methods to make data and query services discoverable, and the types of interfaces that are suitable to consume Linked Data.
I hold several collaborations with researchers in the biodiversity domain. To understand the effects of climate change on biodiversity, researchers have a pressing need to make sense of myriad data produced all over the world by biodiversity-related projects. In this context, I work with the French National Museum of Natural History towards the publication of their data as Linked Open Data. More generally, together with communities like Bioschemas.org, we strive to enable Web-scale integration of biodiversity.
Research projects and communities
Here are the main projects I'm currently involved in:
- D2KAB (ANR): From Data to Knowledge in Agronomy, Agriculture and Biodiversity
- DeKaloG (ANR): Decentralized Knowledge Graphs
- ISSA 2 (Collex-Persée): Indexation Sémantique d'une archive scientifique et Services Associés pour la science ouverte
- TAXREF-LD: the French Linked Data Taxonomic Registry
Here are the community projects I'm currently involved in:
- Bioschemas: Schema.org for Life Sciences
Publications
Contact
Address:
Université Côte d’Azur, CNRS, Inria - I3S, UMR 7271
930 route des Colles - Bât. Les Templiers
BP 145 - 06903 Sophia Antipolis CEDEX - France
Email: fmichel [at] i3s.unice [dot] fr, franck [dot] michel [at] inria [dot] fr
Find me on: ResearchGate, Github, LinkedIn, Twitter, SlideShare, Flickr, Instagram
Selected talks
Open Science, reproducibible research, and the citation of articles, code and data alike
Given 2024-04-04.
ISSA: Generic Knowledge Model and Visualization tools to Help Scientists Make Sense of Archive
Wimmics Monthly Seminar 2022-12-15 / ISWC 2022 resource track replay
Covid-on-the-Web: Knowledge Graph and Services to Advance COVID-19 Research
Presented at the ISWC 2020 conference, resource track.
Bioschemas: Marking up biodiversity websites for data discovery & integration
TDWG webinar series, 2021-03.
Integration of biodiversity data from web pages to knowledge graphs, a computer scientist view point
DIADE research unit seminars (http://diade.ird.fr), 2021-04-13.
Creation/publication of datasets
ISSA Agritrop Dataset, Semantic index of the Agritrop open scientific archive. github DOI
TAXREF-LD, Linked Data knowledge graph of the French taxonomic register. Franck MICHEL, Catherine FARON, Sandrine TERCERIE, Olivier GARGOMINY. 2017(2022. github sparql article DOI
Covid-on-the-Web. Franck Michel, Fabien Gandon, Valentin Ah-Kane, Anna Bobasheva, Elena Cabrio, Olivier Corby, Raphaël Gazzotti, Alain Giboin, Santiago Marro, Tobias Mayer, Mathieu Simon, Serena Villata, Marco Winckler. 2020. github sparql article DOI.
WASABI RDF Knowledge Graph. An RDF representation of the WASABI corpus of songs enriched with metadata extracted from music databases on the Web, and resulting from the processing of song lyrics and from audio analysis. 2020. github sparql article DOI
WeKG-MF, Weather Knowledge Graph of Météo France Meteorological Observations. 2022. github sparql article DOI
WheatGenomicsSLKG, Wheat Genomics Scientific Literature Knowledge Graph. 2023. github sparql DOI
Software Development
ISSA visualization and search web application: Franck MICHEL, Youssef Mekouar (2022). Github: visu and backend
ISSA Processing Pipeline: Anna Bobasheva, Franck MICHEL (2022). github DOI
SPARQL Micro-Services: Querying Web APIs with SPARQL. Franck Michel. 2018. github
Morph-xR2RML: MongoDB-to-RDF translation and SPARQL rewriting: Franck Michel, Freddy Pryiatna. Implementation of the xR2RML mapping language for MongoDB databases. 2017. github DOI
The VO Administration and operations PORtal (VAPOR). Franck Michel, Flavien Forestier. 2014. web DOI
EGI Virtual Organisations Support Tools. Franck Michel. 2013. web DOI
NeuroLOG platform. Alban Gaignard, Franck Michel, Johan Montagnat, Javier Rojas Balderrama, Farooq Ahmad, Bacem Wali. 2008. web
Background and Position
- CNRS Research engineer (IR), Université Côte d'Azur, CNRS, Inria, I3S laboratory. Jan. 2011 until now.
- PhD in Computer Sciences at Université Côte d'Azur, March 2017. Manuscript
- Expert software engineer in IRISA team VisAGeS, May 2008 to Dec. 2010
- Expert telecom engineer, company Capgemini Telecom, Media Networks, 1999 à 2008
- Development engineer, company Nortel Networks France, 1995 à 1999
- Engineering degree in Computer Sciences, INSA de Rennes, 1995
Organizing and Program Committees
I was/am a member of the program committees for the following conferences and/or workshops:
- ECAI 2024, European Conference on AI
- ESWC 2024, The Extended Semantic Web Conference
- The Web Conference 2024, The Extended Semantic Web Conference
- SEMANTiCS 2023, 15th International Conference on Semantic Systems
- ESWC 2022, The Extended Semantic Web Conference
- KGCW 2022, Third International Workshop on Knowledge Graph Construction
- SCG 2021, First workshop on Squaring the circle on graphs
- KGCW 2021, Second International Workshop on Knowledge Graph Construction
- ESWC 2021, The Extended Semantic Web Conference
- ICCS 2020, The International Conference on Computational Science
- IJCAI 2020, 29th International Joint Conference on Artificial Intelligence
- SEMANTiCS 2019, 15th International Conference on Semantic Systems
- Knowledge Graph Building (KBD), workshop of the Extended Semantic Web Conference 2019 (ESWC)
- Hypermedia Multi-Agent Systems (HyperAgents 2019), workshop of the Web Conference 2019
- EKAW 2018, 21th International Conference on Knowledge Engineering and Knowledge Management
- SEMANTiCS 2018, 14th International Conference on Semantic Systems
- ISWC 2018, 17th International Semantic Web Conference
- ICCS 2018, 23rd International Conference on Conceptual Structures
- WWW 2018, The Web Conference 2018
- ISWC 2017, 16th International Semantic Web Conference
- SEMANTiCS 2017, 13th International Conference on Semantic Systems
- ICCS 2016, 22nd International Conferences on Conceptual Structures
- SI&IA 2015, Systèmes d'Information et Intelligence Artificielle 2015
I was/am a member of the organizing committees for the following conferences and/or workshops:
- Ontology Alignment Evaluation Initiative 2022: ontology provider for the complex alignment and biodiversity tracks
- Ontology Alignment Evaluation Initiative 2021: ontology provider for the complex alignment and biodiversity tracks
Wild ideas
Large Language Models as the components of a conscious AI?
AIs, and LLMs in particular, are not conscious. They are reactive systems, they respond to an input by producing an output. By contrast, consciousness can be defined as the ability to form thoughts for oneself, without the need for external stimulus.
What if we fine-tuned several LLMs to collaborate together, following the model of human psyche.
- The “conscious” model would be fine-tuned to remain in the realm of values, morality, norms, and logical thinking. This is the one that would interact with the “outside” world and provide material to the “unconscious” model.
- The “unconscious” model (or “subconscious” depending on the definitions) would be fine-tuned to phrase drive, desires, regardless of any norms nor value system.
- The “preconscious” model would be fine-tuned to filter/rewrite outputs of the “unconscious” to let only acceptable outputs make their way to the “conscious”, while also providing it with material in a feed-back loop.
This way, we could imagine being able to design some sort of a conscious AI system. But this raises multiple questions: How would it be bootstrapped? Individually, each of the 3 LLMs remains a question-answering system, it does not take the initiative of producing an output. So how to start this, and once this starts, how to control the flow? If we skip the conscious model (to try and simulate sleep) and leave the unconscious model talk with itself, could it come up with dreams?
Frugality by design: less is good
Multiple tools of the daily life consume energy and/or resource even though that's not the intend of the user. These tools must be redesigned with a specific bias towards frugality.
This can be implemented as a default behavior, as a nudge etc. Examples:
- Mixer tap delivers heated water by default: In the middle position, most mixer taps mix half ambient temperature water and half heated water. Although users may not need heated water. These should be redesigned with a middle position that only delivers ambient temperature water, so that getting heated water will require a deliberate action from the user.
- Public space fountain water delivers cooled by default: Fountains in public spaces usually deliver cooled water by default although users may not want that. These should be redesigned with a default ambient temperature water, so that getting cooled water will require a deliberate action from the user.