Claudia Marinica - Supporting Semantic Interoperability in Conservation-Restoration Domain: The...
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Transcript of Claudia Marinica - Supporting Semantic Interoperability in Conservation-Restoration Domain: The...
Supporting Semantic Interoperability in Conservation-Restoration Domain: The PARCOURS project (2013-now)
Claudia Marinica1 and Cheikh Niang1, 2
1ETIS Lab - ENSEA / University of Cergy-Pontoise / CNRS 8051 2Research Laboratory for Historical Monuments / LRMH - CRC - USR 3224
Ø C2RMF (French Museum’s Research and Restoration Center) § Research, restoration and archiving for museums’ artifacts
Ø ETIS Lab – ENSEA/University of Cergy-Pontoise/CNRS 8051 (Equipes Traitement de l'Information et Systèmes) § Computer Science research in:
§ Data Integration (Semantic Web, Linked Open Data, etc.) § Data Analysis (Data Mining e.g. visitors’ trajectories, Online Social
Networks Analysis, etc.)
Ø LRMH (Research Laboratory for Historical Monuments) § Conservation-restoration of monuments
Ø CRCC (Research Center of the Conservation of Collections) § Conservation of books, photos, leather objects, etc.
The project was funded for 3 years by the French Heritage Science Foundation, Excellence Laboratory PATRIMA, and for the 4th year it will be funded by the French Ministry of Culture.
E Provide an unified global access to data related to techniques and practices in conservation-restoration processes
E Facilitate the knowledge exchange in conservation-restoration domain, without moving the data held by the conservation-restoration actors in a more centralized location, nor by merging the internal schemas of involved data in a uniform common one
Ø Conservation-restoration process v Achievement of scientific studies
(examination, diagnosis, observation, analysis, etc.);
v Cooperation between different actors operating in different domains (conservators/restorers, scientific researchers, archivists, etc.);
v Clear understanding of the cultural object and its intrinsic properties (typology, shape, dimensions, material constitution, etc.);
v Careful study of the context (location, environment conditions, conservation state or degradation, etc.) and history (origin, phenomena and experienced events, etc.) of the cultural object;
v An ability to detect interactions that rise among these elements.
Ø Databases Heterogeneity o Cultural Heritage laboratories with different specificities o Databases developed with different requirements o Conservation-restoration data recorded with different formats as well as
different conceptual and structural methods
Ø Lack of semantic power o Database structures focusing mainly at the syntactical level: relational, semi-
structured (XML annotated documents) or unstructured (texts or images)
Ø Terminology heterogeneity o Difficult to reach an agreement on a “clear and consistent” terminology o Difficult to connect databases while avoiding ambiguity, since terms used for
describing the recorded conservation-restoration data may have different meanings and different lexical values in different databases
Building a ontological model intended to capture the existing data semantics, and to provide a unified understanding of conservation- restoration data
Anchoring the involved sources to the ontological model
Building a query-answering process allowing to get information from the different conservation-restoration semantic databases, through the ontological model
PARCOURS ontological model is composed of a triple Op=⟨(Ot,Oc),Ter⟩ where:
– The couple (Ot,Oc)is composed by, respectively, a top-level ontology Ot (CIDOC-CRM), and a core ontology Oc (PARCOURS core). PARCOURS core ontology is connected to the CRM_sci for representing at a very fine level of granularity the specificities of scientific observations.
– Ter consists of a set of domain-specific thesauri (controlled vocabulary terms) intended to provide an unambiguous conservation-restoration terminology.
PARCOURS Ontological Model
Ø Thank you, Achille, for so well presenting CIDOC-CRM yesterday! J
Ø CRM_sci (“Scien&ficObserva)onModel”) integratesmetadataaboutscien)ficobserva)on,measurementsandprocesseddataindescrip)veandempiricalsciences
Ø Snapshot from the ontological model
Concept from CIDOC-CRM
Concept from CRM SCIENCE
Concept from PARCOURS
Ø Anchoring the sources to the global ontology Ø Each participating source is autonomous and stores its data
without changing its internal formatsØ Each participating source must build a conceptual representation
of its data, at least for the part that should contribute to the integration process
Ø Each source is free to choose the method to bring its data to its local semantic database – Whether possible by using suitable existing tools: e.g. Ontop [Bagosi et al.
2014] – Otherwise by implementing its own ad hoc algorithm according to its
database format – Regardless the solution chosen by a source, the generated repository must
be updated and conceptually sound with respect to the PARCOURS global ontology
Different Actors and/or applications
R2ML Mappings A
P I
Json
ad hoc algorithm
ONTOP ETL
Query Processing Engine
Sparql EndPoint Sparql EndPoint
Relationnal Database
Sesame
RDF Repository
….
Source1 Sourcen
PARCOURS global Ontology
Request
RDF Repository
Response