InteGraal

BOREAL is committed in a team effort to develop a platform for knowledge-based data management on heterogeneous and federated data, called InteGraal. The development of the tool started towards the end of 2020 with the goal of providing a major version of the former Graal software.

The main developer of the InteGraal library is Florent Tornil (INRIA engineer), who closely collaborates with several permanent and non-permanent members of the team. Since fall 2022, the work of Florent Tornil is also supervised by the SED (Service d'Expérimentation et de Développement) of the Inria centre at Université Côte d’Azur. The role of the SED is to complement the team activity in structuring software development cycles by following standard practices and guidelines on matters such as project management, continuous integration, and software distribution.

The InteGraal tool is available online on the Inria gitlab (gitlab.inria.fr/rules/integraal) with Apache 2 licence. Overall, InteGraal is a tool aimed at accelerating the implementation and test of results issued by fundamental research, but not only. This tool is also a concrete means to structure discussions and collaborations with other academic and industrial partners.

Other Tools

In the context of the PhD of Olivier Rodriguez, we started the development of a prototype system for reasoning on NoSQL systems, notably document-oriented key-value stores (or simply, document stores). This led to the creation in 2021 and 2022 of the TreeForce library, which shall be detailed next.

6.2.1 InteGraal

• Name:
  InteGraal : Knowledge-Representation and Reasoning for Data Integration
• Keywords:
  Knowledge Bases, Data integration, Knowledge representation, Automated Reasoning, Heterogeneous Data, Knowledge Graphs
• Scientific Description:
  InteGraal is a tool for integrating and reasoning on heterogeneous and federated data. The tool embodies algorithms and techniques developed at the crossroads between the fields of knowledge representation and reasoning and data management. From the historic point of view, this tool is the result of a complete re-engineering of the Graal tool, whose API and functionalities have been completely updated. Also, with respect to Graal, the tool is very much oriented towards data integration.
• Functional Description:
  InteGraal has been designed in a modular way, in order to facilitate software reuse and extension. It should make it easy to test new scenarios and techniques, in particular by combining algorithms. The main features of Graal are currently the following: (1) internal storage to store data by using a SQL or RDF representation (Postgres, MySQL, HSQL, SQLite, Remote SPARQL endpoints, Local in-memory triplestores) as well as a native in-memory representation (2) data-integration capabilities for exploiting federated heterogeneous data-sources through mappings able to target systems such as SQL, RDF, and black-box (eg. Web-APIs) (3) algorithms for query-answering over heterogeneous and federated data based on query rewriting and/or forward chaining (or chase)
• Release Contributions:
  2022: First release, software deposit with Apache 2 licence. 2021: Functional specification, design and development of a major improved version of the tool. Started refactoring of the API, and of several modules for knowledge base representation, data storage, query answering and forward-chaining reasoning (chase). Started the development of new modules for handling heterogeneous data: mappings and federations.
• News of the Year:
  2022. Finalized novel modules, namely (1) storage and mapping, (2) forward chaining module. Started novel backward chaining module (end planned in first half 2023). Bidirectional bridge with the CORESE platform (https://project.inria.fr/corese/) and the query mediator Tatooine (https://hal.inria.fr/hal-01321201v2). Tool already used by the team for PhDs, master internship, and to build demostrator for research projects.
• URL:
  https://­gitlab.­inria.­fr/­rules/­integraal
• Authors:
  Florent Tornil, Guillaume Perution-Kihli, Clément Sipieter, Federico Ulliana, Jean-Francois Baget, Pierre Bisquert, David Carral Martinez, Michel Leclère, Marie-laure Mugnier
• Contact:
  Federico Ulliana

6.2.2 TreeForce

• Keywords:
  JSon, Databases, Knowledge Bases, Automated Reasoning, Rewriting, NoSQL, Data integration, Knowledge representation, Heterogeneous Data
• Functional Description:
  TreeForce is a java tool for reasoning on tree data. It leverages on query rewriting techniques and NoSQL document oriented key-value stores. This library can be seen as a general toolbox for implementing reasoning techniques tailored for tree-shaped data and rules. It is composed of two main modules. The first includes generic data structures and algorithms for trees and tree-automata. The second includes automata-based query rewriting techniques as well as efficient evaluation techniques for large sets of rewritings.
• Release Contributions:
  2021: First version of TreeForce. Automata for unordered tree languages. Automata-based query-rewriting algorithms. MongoDB wrapper.
• News of the Year:
  2022 Added novel instance-aware rewriting and evaluation algorithms. Introduced summarization, partitioning and parallelization techniques.
• Contact:
  Federico Ulliana

Existential Rules.

Existential rules are first-order-logic formulas representing implications of the form $\forall X\left[\mathrm{𝐵𝑜𝑑𝑦}(X,Y)\to \exists Z.\mathrm{𝐻𝑒𝑎𝑑}(X,Z)\right]$ where Body and Head are positive conjunctions of atoms without functional symbols, and Head can have existentially quantified variables. These rules allow one to model complex relationships over the domains of interest, and at the same time dispose of a value invention mechanism through existentially quantified variables. This makes them suitable for many data and knowledge tasks on both open and closed domains. As a result, existential rules are ubiquitous in many fields. They are used to model dependencies, schema mappings, and expressive queries in databases. They are used as ontological languages as a valid complement to Description Logics, and at the same time as a generalization of so-called Horn Description Logics which lay at the foundations of important Semantic Web standards.

Rule-based Query Answering

Given a query $Q$, a database $D$, and a set of rules $R$, query answering asks to determine whether $D,R\vDash Q$ (where $\vDash$ denotes standard first-order logic entailment), that is if the query $Q$ is a logical consequence of the knowledge base made by the database $D$ and the rules $R$. In the field of knowledge representation and reasoning, rule-based query answering is studied for rules expressing ontologies and referred as ontology-mediated query answering (OMQA). Formalisms such as Description Logics and Existential Rules (a.k.a, Tuple-Generating-Dependencies, or Datalog$\pm$) are typically targeted for expressing ontologies. Overall, the main emphasis of this topic is in the study of rule languages and the role they play in query answering.

Rule-based Query Answering over Heterogeneous and Federated Data

In this context, the problem formulation remains similar, however the database $D$ is replaced by a more complex notion of federation$(𝒟,ℳ,𝒮)$ where $𝒟$ is a collection of heterogeneous data sources, $𝒮$ is a global integration schema, and $ℳ$ is a set of mappings linking the datasources in $𝒟$ to the global schema $𝒮$. This framework is at the foundations of data integration (DI) in databases and of ontology-based data access (OBDA) in knowledge representation and reasoning. OBDA focuses on global integration schemes and rules built on ontologies enabling query rewriting, while DI is more concerned with rules representing data-dependencies. Overall, both give more emphasis to heterogeneous and federated data in rule-based query answering.

Reasoning Strategies for Query Answering

The two prominent strategies for rule-based query answering are materialization (also known as saturation, or forward-chaining) and virtualization (also known as query rewriting, or backward chaining). Both can be seen as ways of reducing query answering (which involves reasoning) into classical query evaluation. Materialization amounts at storing the inferences enabled by rules, thereby obtaining an extended database, on which queries are evaluated. Query rewriting amounts at compiling relevant rules into the query, thereby obtaining a rewritten query (usually a union of queries), which is evaluated on the (unaltered) database. Both approaches have their own strengths, and at the basis of this duality is the fact that while materialization is independent of queries, rewriting is independent of the database. Hence, each strategy better suits certain applicative scenarios, and both can possibly be combined thereby resulting in hybrid approaches.

Contributions

This year, we studied a number of theoretical, algorithmic, and applied questions of knowledge-based data management with existential rules. Our main contributions cover the following topics:

• foundational issues related to the termination of reasoning strategies;
• novel rule-transformation procedures leading to efficient reasoning algorithms;
• the use of rules and graphs to model and reason on complex systems (notably in agronomy).

This work led to the publications presented next.

Beside our main publications, it is worth noting that the team also supervised a number of student internship projects (Section 10.2.2) investigating other foundational and applied issues of reasoning. Finally, complementing methodological work, we also conducted an important team effort in the development of the InteGraal tool for rule-based query answering over heterogeneous and federated data (Section 6.2).

Note

Next, we do not present our IJCAI 2022 publication on the expressivity of chase terminating rule sets 10. Indeed, this is an extended abstract of a 2021 paper 21 that also received the best paper award at the international KR Conference (A*). Also, we do not present another paper on the composition of mapping rules 22 that received the best paper award at the 2022 French Database Conference (BDA), which was also published at the international KR Conference in 2021.

Chase Termination

The most widespread materialization procedure for existential rules is called the chase. There are several variants of the chase which differ in terms on their computational costs and termination capabilities. The most powerful variant is the core-chase which is known to terminate if and only if the knowledge base admits a finite universal model (a model that can be embedded into any other model of the knowledge base, hence is sufficient to answer unions of conjunctive queries). Other variants include the restricted and (semi-)oblivious chase. These are less aggressive on the suppression of redundancies produced by materialization and may not terminate even if a finite universal model of the knowledge base exists. A ruleset that enjoys the termination of the core-chase over any possible database instance, is also called a finite expansion set (FES).

Rewriting Termination

First-Order rewritability is a property enjoyed by the sets of existential rules for which every input conjunctive query (CQ) admits a finite equivalent first-order-logic formula, called its rewriting. Here, equivalent is intended in the sense of query answering, and it means that whenever there is a database that (together with the rules) entails the input query, then the same database (without the rules) directly entails the rewriting. This notion coincides with that of finite unification set (FUS), which are the sets of existential rules for which breadth-first query rewriting based on piece-unifiers terminate. Interestingly, this query-rewritability property has a dual formulation in terms of materialization, which is called the bounded-depth derivation property (BDD).

Normalisation of Rules

In the literature, it is often assumed that existential rules are in some normal form that simplifies technical developments. For instance, a common assumption is that rule heads are atomic, i.e., restricted to a single atom. Such assumptions are usually considered to be made without loss of generality as long as all sets of rules can be normalised while preserving logical entailment. However, an important question is whether the properties that ensure the decidability of reasoning are preserved as well. We carried out a systematic study of the impact of normalisation procedures on two properties that underpin most known classes of decidable rules: the termination of the chase (and, actually, of different variants of the chase) and the first-order rewritability of conjunctive queries.

• Published at KR 2022 11 with Michael Thomazo (Inria Paris, Valda Team).

Query Rewritability

The expressivity of existential rules enjoying first-order rewritability is still not fully understood. An open conjecture on this matter states that any theory that is a finite expansion set (FES) and admits finite query rewriting (FUS) must be uniformly bounded (i.e., makes the depth of reasoning independent of any input data). Starting from the FES/FUS conjecture, we showed that this holds for a large class of FUS theories, which we call “local”. Upon investigating how “non-local” FUS theories can actually get, we discovered that these can lead to rewritings containing elements that are exponentially larger than the input query. This unexpected phenomenon, we think, is at odds with prevailing intuitions on FUS rulesets.

• Published at PODS 2022 14 with Piotr Ostropolski-Nalewaja (University of Wrocław),  Jerzy Marcinkowski (University of Wrocław),  and Sebastian Rudolph (TU Dresden).

As a side topic, this year we also investigated the satisfiability problem for expressive temporal logic formalisms.

Satisfiability of Hyper-LTL

Among the most studied fragments of first-order logic, we find LTL (Linear Temporal Logic). This logic is used to specify properties of programs and reason about them, and more precisely their execution traces. The fundamental problem in this context is the satisfiability problem which asks to decide the existence of some model in which a formula holds. We studied the satisfiability problem for HyperLTL, which extends LTL with so called trace quantification, which allows one for instance to express the non-interference of two simultaneous execution traces. We characterized the complexity of the satisfiability problem for several fragments of HyperLTL thereby also showing new interesting decidable fragments.

• Published at LICS 2022 9 with Raven Beutner (CISPA Helmholtz Center for Information Security), Bernd Finkbeiner (CISPA Helmholtz Center for Information Security), Jana Hofmann (CISPA Helmholtz Center for Information Security), and Markus Krötzsch (TU Dresden).

EL Ontologies with Nominal Schemas

Nominal schemas have been proposed as an extension to Description Logics (DL), the knowledge representation paradigm underlying the Web Ontology Language (OWL). They provide for a very tight integration of DL and rules. Nominal schemas can be understood as syntactic sugar on top of OWL. However, this naive perspective leads to inefficient reasoning procedures. In order to develop an efficient reasoning procedure for the language ELV++, which results from extending the OWL profile language OWL EL with nominal schemas, we propose a transformation from ELV++ ontologies into Datalog-like rule programs that can be used for satisfiability checking and assertion retrieval. The use of this transformation enables the use of powerful Datalog engines to solve reasoning tasks over ELV++ ontologies. We implemented and evaluated our approach on several real-world, data-intensive ontologies, and found that it can outperform state-of-the-art DL reasoners such as Konclude and ELK.

• Published in the Journal of Logic and Computation 5 with Joseph Zalewski (Kansas State University) and Pascal Hitzler (Kansas State University).

Guarded Existential Rules

Guarded existential rules, also known as guarded tuple-generating dependencies (GTGDs), are a natural extension of Description Logics and referential constraints. It has long been known that queries over GTGDs can be answered by a variant of the chase. However, there has been little work on concrete algorithms and even less on implementation. To address this gap, we revisit Datalog rewriting approaches to query answering, where GTGDs are transformed into a Datalog program that entails the same base facts on each base instance. We show that the rewriting can be seen as containing "shortcut" rules that circumvent certain chase steps. We present several algorithms that compute the rewriting by simulating specific types of chase steps, and we discuss important implementation issues. Finally, we show empirically that our techniques can process complex GTGDs derived from synthetic and real benchmarks and are thus suitable for practical use.

• Published at VLDB 2022 8 with Mickael Benedikt (Oxford University), Stefano Germano (Oxford University), Kevin Kappelmann (Technical University of Munich) and Boris Motik (Oxford University).

Integrating Data and Knowledge for Decision Making in Agroecology

As part of Elie Najm's PhD thesis and in collaboration with the INRAE ABSys research lab in agroecology, we considered the issue of selecting service plant species according to their potential to provide ecosystem services. To tackle that issue, we adopted an approach based both on a formalized representation of domain knowledge as logical rules and on the exploitation of available data, which was typically collected independently from the targeted application. The architecture of our system reprises that of rule-based query answering over heterogeneous and federated data we already presented. We carried out an experimental evaluation of our system on this use case, which showed that very satisfactory results can be obtained as long as the proportion of missing data values is not too high.

• Published at RuleML & Rule Challenge 2022 13 and as part of Elie Najm's PhD Thesis 19.
• Preprint submitted for publication 20 as a joint work with Christian Gary (INRAe), Raphael Metral (INRAe) and Léo Garcia (INRAe)

Graph-based Approaches for Monitoring Power-plants Controllers

As part of Mohammed Aziz Sfar Gandoura's PhD thesis in collaboration with EDF research, we considered the issue of monitoring power-plant controllers. The function of power-plants controllers is typically described by using formal representation of functional specifications given in logical diagrams (LD), which is used for verification and test purposes. Motivated by a scenario from a real world power plant specification, our work consisted at defining a formal structure that explicitly encodes the semantics and behavior of a LD. We put in a complete transformation procedure of the non-formal LD specifications into a directed state graph such that properties like oscillatory behavior become formally verifiable on LDs.

• Published at FoIKS 2022 15 with Dina Irofiti (EDF).

Ontology-based Explanations for Planning

As part of Martin Jedwadbny's PhD thesis, we investigated the use of ontologies for the explanation and scrutability of an artificial agent's decisions in the context of planning. In a nutshell, the idea is to provide a framework allowing to select the level of precision needed for a user to understand the agent's sequence of actions: the more knowledgeable the user, the more precise the plan can be laid out by unfolding actions into several layers of complexity. We provided a method to adjust on the fly the level of detail of actions (and corresponding fluents) using the concept of "transitional description". Such a work is relevant for user-adaptable explainable AI (XAI) exploiting both knowledge of the world and user's level of expertise.

• Published at ICCS 2022 12 as part of Martin Jedwabny PhD Thesis 18.

R4Agri

Participants: Pierre Bisquert, David Carral, Marie-Laure Mugnier, Federico Ulliana.

• Title:
  “R4Agri”- Reasoning on Agricultural Data: Integrating Metrics and Qualitative Perspectives
• Partner Institution(s):
  $$

  • Inria
  • DFKI, Germany
• Date/Duration:
  42 months, started in 01/01/2022
• Additional info:

  AI tools supporting competitive and sustainable agriculture need to exploit highly diverse kinds of data and knowledge, from raw data provided by sensors to high level expertise knowledge. Taking numerical agriculture as the targeted application domain, the overall goal of the R4Agri project is to provide a framework for reasoning about knowledge based on heterogeneous data, with a focus on multi-modal and multi-scale sensor data. Main challenges include context-dependent interpretation of sensor data, which involves reasoning about prior knowledge, and query answering techniques that exploit domain knowledge and accommodate the specificities of data sources in a flexible manner. The application potential in this field of world-wide societal and ecological impact will be demonstrated in realistic use cases. In 2022, Maxime Buron has been recruited as a post-doc (from March to August) funded by this project to work on optimizations of query answering based on mappings to heterogeneous data sources as well as their implementation within the InteGraal tool developed by the team.

  project.inria.fr/r4agri/

9.2.1 Visits of international scientists

9.2.2 Visits to international teams

CQFD (ANR PRC, Jan. 2019-Dec. 2024)

Participants: Jean-François Baget, Pierre Bisquert, Nofar Carmeli, David Carral, Michel Leclère, Marie-Laure Mugnier, Guillaume Pérution-Kihli, Olivier Rodriguez, Florent Tornil, Federico Ulliana.

CQFD (Complex ontological Queries over Federated heterogeneous Data), coordinated by Federico Ulliana (BOREAL), involves participants from Inria Saclay (CEDAR team), Inria Paris (VALDA team), Inria Nord Europe (SPIRALS team), IRISA, LIG, LTCI, and LaBRI. The aim of this project is tackle two crucial challenges in OMQA (Ontology Mediated Query Answering), namely, heterogeneity, that is, the possibility to deal with multiple types of data-sources and database management systems, and federation, that is, the possibility of cross-querying a collection of heterogeneous datasources. By featuring 8 different partners in France, this project aims at consolidating a national community of researchers around the OMQA issue.

www.lirmm.fr/cqfd/

Convergence institute #DigitAg (2017-2023)

Participants: Jean-François Baget, Patrice Buche, Madalina Croitoru, Marie-Laure Mugnier, Elie Najm, Federico Ulliana.

Located in Montpellier, #DigitAg (for Digital Agriculture) gathers 17 founding members: research institutes, including Inria, the University of Montpellier and higher-education institutes in agronomy, transfer structures and companies. Its objective is to support the development of digital agriculture. BOREAL is involved in this project on the issues of designing data and knowledge management systems adapted to agricultural information systems, and of developing methods for integrating different types of information and knowledge (generated from data, experts, models). A PhD thesis (Elie Najm) investigates knowledge representation and reasoning for the design of new agroecological systems, in collaboration with the research laboratory ABSys - Biodiversified Agrosystems (formerly UMR SYSTEM).

www.hdigitag.fr/en/

10.1.1 Scientific Event : Organization

At the LIRMM level, Madalina Croitoru is co-chair of the transversal axis and workshop on Artificial Intelligence for human-robot interaction.

10.1.2 Scientific Events: Selection

10.1.3 Invited Talks

• Nofar Carmeli - Invited talk Enumeration and Related Problems in Query Answering: - WEPA 2022 (Workshop on Enumeration Problems and Applications, 22-25/11/2022
• Marie-Laure Mugnier - Invited talk Intégration de données hétérogènes dirigée par des ontologies - Journées plénières du GDR IA, 14/10/2022.
• Federico Ulliana - Invited talk An Introduction to the Boundedness Problem for Existential Rules - LaHDAK team seminar (online), LRI, 14/02/2022.
• Federico Ulliana - Invited talk Rule-based Languages for Reasoning on Data : The Virtual Approach for Key-Value Stores - SPARKS team seminar (online), I3S, 30/03/2022.
• Florent Tornil - Invited talk T-CALIS-FAIR: Un exemple d'Intégration de données hétérogènes dans l'environnement InteGraal - CATI DIISCICO (online), INRAE, UMET, Villeneuve d’Ascq, 09/11/2022.

10.1.4 Scientific expertise

• Federico Ulliana was a member of the jury for the awarding the best PhD thesis award of the National BDA 2022 conference.
• Marie-Laure Mugnier was a member of the jury for the awarding the best PhD thesis award SIF (Gilles Kahn) 2022.
• Marie-Laure Mugnier was a member of the recruitment committee for a Professorship position, Université Toulouse Capitole.

10.1.5 Research Administration

• Madalina Croitoru has been deputy member of the CNU section 27 (Computer Science) since September 2019.
• Madalina Croitoru has been deputy director of the Computer Science Department at the Faculty of Science, University of Montpellier since September 2021.
• Marie-Laure Mugnier has been president of the “Section 27 Commitee” (Computer Science) of the University of Montpellier since July 2021.
• Marie-Laure Mugnier has been a member of the Council of the Scientific Department MIPS (Mathematics Informatics Physics and Systems) of the University of Montpellier since 2016.
• Federico Ulliana is part of the Inria CDT (Commission Développement Technologique) since May 2022. This committee is in charge of reviewing and following software development projets within the Inria centre at Université Côte d’Azur.

10.2.1 Teaching

Madalina Croitoru, Michel Leclère, and Marie-Laure Mugnier, do an average of 200 teaching hours per year at the Computer Science department of the Science Faculty. They are in charge of courses in Logics (Licence), Artificial Intelligence (Master), Knowledge Representation and Reasoning (Master), Theory of Data and Knowledge Bases (Master), Social and Semantic Web (Master) and Multi-Agent Systems (Master). Concerning full-time researchers in 2022, Jean-François Baget, David Carral, and Federico Ulliana (on secondment from Montpellier University) both taught in the Computer Science Master; topics include Theory of Data and Knowledge Bases, Datawarehouses, Big-Data and NoSQL systems.

Madalina Croitoru has also been in charge of international relations for the Computer Science department of the Science Faculty since September 2019.

10.2.2 Supervision

10.2.3 Articles and contents

The BOREAL team participated to the event organized on September 2022 for the 30th anniversary of the creation of the LIRMM laboratory (with 3 stands).

Marie-Laure Mugnier and Pierre Bisquert participated to the writing of a “white-book” on digital agriculture issued from a joint work between Inria and INRAE 16.

International journals

• 4 articleC.Cedric Baudrit, P.Patrice Buche, N.Nadine Leconte, C.Christopher Fernandez, M.Maëllis Belna and G.Geneviève Gésan-Guiziou. Decision support tool for the agri-food sector using data annotated by ontology and Bayesian network: a proof of concept applied to milk microfiltration..International Journal of Agricultural and Environmental Information Systems1312022
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• 5 articleD.David Carral, P.Pascal Hitzler and J.Joseph Zalewski. An efficient algorithm for reasoning over OWL EL ontologies with nominal schemas.Journal of Logic and ComputationMay 2022, exac032
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• 6 articleM.Mélanie Munch, P.Patrice Buche, S.Stéphane Dervaux, J.Juliette Dibie, L. L.Liliana L. Ibanescu, C.Cristina Manfredotti, P.-H.Pierre-Henri Wuillemin and H.Helene Angellier-Coussy. Combining ontology and probabilistic models for the design of bio-based product transformation processes.Expert Systems with Applications203October 2022, 117406
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• 7 articleR.Rallou Thomopoulos, P.Pierre Bisquert, B. v.Bart van Der Burg and E.Erwan Engel. Good practices and ethical issues in food safety related research.Global Pediatrics2December 2022, #100016
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International peer-reviewed conferences

• 8 inproceedingsM.Michael Benedikt, M.Maxime Buron, S.Stefano Germano, K.Kevin Kappelmann and B.Boris Motik. Rewriting the Infinite Chase.VLDB 2022 - 48th International Conference on Very Large Databases1511Sydney, Australia2022, 3045-3057
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• 9 inproceedingsR.Raven Beutner, D.David Carral, B.Bernd Finkbeiner, J.Jana Hofmann and M.Markus Krötzsch. Deciding Hyperproperties Combined with Functional Specifications.LICS 2022 - 37th Annual ACM/IEEE Symposium on Logic in Computer ScienceA56Haifa, IsraelACM2022, 1-13
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• 10 inproceedingsC.Camille Bourgaux, D.David Carral, M.Markus Krötzsch, S.Sebastian Rudolph and M.Michaël Thomazo. Capturing Homomorphism-Closed Decidable Queries with Existential Rules (Extended Abstract).Proceedings of the Thirty-First International Joint Conference on Artificial IntelligenceIJCAI-ECAI 2022 - 31st International Joint Conference on Artificial Intelligence - 25th European Conference on Artificial IntelligenceVienna, AustriaJuly 2022, 5269-5273
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• 11 inproceedingsD.David Carral, L.Lucas Larroque, M.-L.Marie-Laure Mugnier and M.Michaël Thomazo. Normalisations of Existential Rules: Not so Innocuous!KR 2022 - 19th International Conference on Principles of Knowledge Representation and ReasoningHaÏfa, Israel2022, 102-111
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• 12 inproceedingsM.Martin Jedwabny, P.Pierre Bisquert and M.Madalina Croitoru. Scrutable Robot Actions Using a Hierarchical Ontological Model.Lecture Notes in Computer ScienceICCS 2022 - 27th International Conference on Conceptual StructuresLNCS-13403Graph-Based Representation and ReasoningMünster, GermanySpringer International PublishingSeptember 2022, 11-24
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• 13 inproceedingsE.Elie Najm, J.-F.Jean-François Baget and M.-L.Marie-Laure Mugnier. Rule-Based Data Access: A Use Case in Agroecology.http://ceur-ws.org/Vol-3229/RuleML+RR 2022 - 16th International Rule Challenge3229RuleML+RR-Companion 2022 International Rule Challenge and Doctoral ConsortiumBerlin, GermanyCEUR-WS.orgSeptember 2022
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• 14 inproceedingsP.Piotr Ostropolski-Nalewaja, J.Jerzy Marcinkowski, D.David Carral and S.Sebastian Rudolph. A Journey to the Frontiers of Query Rewritability.PODS 2022 - 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database SystemsPhiladelphia, United StatesJune 2022, 359–367
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• 15 inproceedingsM. A.Mohamed Aziz Sfar Gandoura, D.Dina Irofti and M.Madalina Croitoru. A graph based semantics for Logical Functional Diagrams in power plant controllers.FoIKS 2022 - 12th International Symposium on Foundations of Information and Knowledge SystemsLecture Notes in Computer ScienceHelsinki, FinlandSpringer International PublishingJuly 2022, 55-74
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Scientific book chapters

• 16 inbookN.Nathalie Mitton, L.Ludovic Brossard, T.Tassadit Bouadi, F.Frédérick Garcia, R.Romain Gautron, N.Nadine Hilgert, D.Dino Ienco, C.Christine Largouët, E.Evelyne Lutton, V.Véronique Masson, R.Roger Martin-Clouaire, M.-L.Marie-Laure Mugnier, P.Pascal Neveu, P.Philippe Preux, H.Helene Raynal, C.Catherine Roussey, A.Alexandre Termier and V.Véronique Bellon Maurel. Foundations and state of the art.Agriculture and Digital Technology: Getting the most out of digital technology to contribute to the transition to sustainable agriculture and food systemsWhite book Inrira6INRIA2022, 30-75
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Edition (books, proceedings, special issue of a journal)

• 17 proceedingsO.Offer ArieliM.Martin HomolaJ.Jean JungM.-L.Marie-Laure MugnierProceedings of the 35th International Workshop on Description Logics (DL 2022) co-located with Federated Logic Conference (FLoC 2022).3263CEUR Workshop Proceedings2022
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Doctoral dissertations and habilitation theses

• 18 thesisM.Martin Jedwabny. A preference-based approach to machine ethics for automated planning.Universite de MontpellierDecember 2022
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• 19 thesisE.Elie Najm. Reasoning on data in agroecology: application to the selection of service plant species.Université de MontpellierDecember 2022
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Reports & preprints

• 20 miscE.Elie Najm, M.-L.Marie-Laure Mugnier, C.Christian Gary, J.-F.Jean-François Baget, R.Raphael Metral and L.Léo Garcia. Integrating Data and Knowledge to Support the Selection of Service Plant Species in Agroecology.November 2022
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