DLP: a Web-based Facility for Exploration and Basic Modification of Ontologies by Domain Experts

DLP: a Web-based Facility for

Exploration and Basic Modification of

Ontologies by Domain Experts

Luca Mazzola and Patrick Kapahnke

German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany

iiWAS conference 2017– Salzburg

05/Dec/2017iiWAS 2017 , Luca Mazzola

• Context

• Needs

• Functions offered

• DLP architecture

• Examples and Limits

• Conclusions

Agenda


• SOA

• Ontology editing

• WebApp RESTful

• Industry 4.0 Manufacturing Domain

Context


• Support Domain experts for:

• conceiving

• analyzing

• extending

• merging

ontologies, even if not familiar with semantic

technologies

• Integrated environment for these tasks

• Not a general solution: specific tool for the needs

of a H2020 research project (CREMA)…

Needs for DLP


Functions offered by DLP


• Creation of profile by sub-setting the public semantic

data sources (set of ontologies)

• Addition and removal of concepts/instances into a

domain expert profile

• Navigation of the semantic concept context with an

iterative exploration limited to a selectable radius,

without relying on any semantic format expertise

• Intuitive representation of similarity for given

concept/instance, by structural information, weighted

by their meaning

Architecture - Infrastructure


D

Apache Jena

Fuseki2

CDM-Core

DOCKER container

9001

3030

9002

80

Architecture – RESTful APIs


• Includes sparse CRUD

(Create, Read, Update,

Delete) operations at

the level of :

• ontology

• user profile and its

metadata,

• operations to

provide search

functionality over

concepts and

instances

Delocalized ontology development process, run directly

by domain experts; ontology engineer intervention

required only for consolidation or in case of problems.

DLP usage in CREMA


Screenshots: navigation

• Graphical exploration of an ontology extract (named

graph -> center concept -> radius)

• Concept “similarity” for the representation center05/Dec/2017iiWAS 2017 , Luca Mazzola

Screenshots: similarity


• Limited to owl:equivalentClass, rdfs:subClassOf,

rdfs:type, and owl:restriction

• Predefined weights: equivalent [1.0], children [0.9],

parents [0.8], instances [0.7] and connection with

complex concepts in the concept taxonomy [0.5]

Screenshots: profile

• Based on metadata (Dublin Core initiative), useful also

to maintain track of the contributor and the provided

contribution.

• Provide a working space for the domain experts, to

test modifications in a isolated environment.

• Allows local modification, affecting the public semantic

data source only for the relevant part, when released.05/Dec/2017iiWAS 2017 , Luca Mazzola

Representational capabilities


Limits


• DLP is not a distributed environment and does not

support session management and versioning

• DLP does not prevent dirty writes, if a user

overrides the public ontology starting from an

outdated local profile.

• DLP does not automatically support a merge of the

local contribution into the new ontology version, if a

user modified its local profile without committing it

back.

Conclusions


• DLP is a demonstrator tool to partially solve the

issue of semantic data source editing by non-experts

• DLP allows to work on a selected subpart of the

source relying on a user copy (profile), useful for

supporting the evolution, adaptation or extension of

a partially defined ontology

• DLP supports a simple but still informative and

immediate graphical view of an ontology part

• DLP supports the computation of an initial similarity

function with user-selected weights

• DLP uses a simplified metadata-based approach for

minimal collaborative distributed ontology evolution

ResourcesMazzola, L., Kapahnke, P., Vujic, M., & Klusch, M. (2016). CDM-Core: A Manufacturing

Domain Ontology in OWL2 for Production and Maintenance. In KEOD (pp. 136-143).

Mazzola, L., Kapahnke, P., Waibel, P., Hochreiner, C., & Klusch, M. (2017). FCE4BPMN: On-

demand QoS-based optimised process model execution in the cloud. In Proceedings of

the 23rd ICE/IEEE ITMC Conference. IEEE.

Mazzola L., Kapahnke P., Klusch M. (2017) ODERU: Optimisation of Semantic Service-

Based Processes in Manufacturing. In: Różewski P., Lange C. (eds) Knowledge Engineering

and Semantic Web. KESW 2017. Communications in Computer and Information Science, vol.

786. Springer, Cham

Mazzola L., Kapahnke P., Klusch M. (2017). Pattern-Based Semantic Composition of

Optimal Process Service Plans with ODERU. In Proceedings of The 19th Int. Conference on

Information Integration and Web-based Applications & Services, Salzburg, Austria, December

4–6, 2017 (iiWAS ’17), 10 pages. DOI: https://doi.org/10.1145/3151759.3151773

Mazzola L., and Kapahnke P. (2017). DLP: a Web-based Facility for Exploration and Basic

Modification of Ontologies by Domain Experts. In Proceedings of The 19th Int. Conference

on Information Integration and Web-based Applications & Services, Salzburg, Austria,

December 4–6, 2017 (iiWAS ’17), 5 pages. DOI: https://doi.org/10.1145/3151759.3151816


https://doi.org/10.1145/3151759.3151773

https://doi.org/10.1145/3151759.3151816

THANKS FOR THE ATTENTION

[email protected]

[email protected]

http://www.crema-project.eu

H2020-RIA agreement 637066

https://www.linkedin.com/in/mazzolaluca/

The ODERU code can be found at:

https://sw-dlp.sourceforge.io/


http://www.crema-project.eu/

https://oderu.sourceforge.io/

DLP: a Web-based Facility for Exploration and Basic Modification of Ontologies by Domain Experts

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