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Gu, Z., Corcoglioniti, F., Lanti, D., Mosca, A., Xiao, G., Xiong, J. & Calvanese, D. (2024). A systematic overview of data federation systems. Semantic Web, 15(1), 107-165
Open this publication in new window or tab >>A systematic overview of data federation systems
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2024 (English)In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 15, no 1, p. 107-165Article in journal (Refereed) Published
Abstract [en]

Data federation addresses the problem of uniformly accessing multiple, possibly heterogeneous data sources, by mapping them into a unified schema, such as an RDF(S)/OWL ontology or a relational schema, and by supporting the execution of queries, like SPARQL or SQL queries, over that unified schema. Data explosion in volume and variety has made data federation increasingly popular in many application domains. Hence, many data federation systems have been developed in industry and academia, and it has become challenging for users to select suitable systems to achieve their objectives. In order to systematically analyze and compare these systems, we propose an evaluation framework comprising four dimensions: (i) federation capabilities, i.e., query language, data source, and federation techniques; (ii) data security, i.e., authentication, authorization, auditing, encryption, and data masking; (iii) interface, i.e., graphical interface, command line interface, and application programming interface; and (iv) development, i.e., main development language, deployment, commercial support, open source, and release. Using this framework, we thoroughly studied 51 data federation systems from the Semantic Web and Database communities. This paper shares the results of our investigation and aims to provide reference material and insights for users, developers and researchers selecting or further developing data federation systems.

Place, publisher, year, edition, pages
IOS Press, 2024
Keywords
Data federation systems, data virtualization, federated query answering, heterogeneous data integration, system evaluation framework
National Category
Computer Sciences Information Systems
Identifiers
urn:nbn:se:umu:diva-220145 (URN)10.3233/SW-223201 (DOI)001168380700004 ()2-s2.0-85182719352 (Scopus ID)
Funder
EU, Horizon 2020, 863410European Regional Development Fund (ERDF), FESR1133The Research Council of Norway, 237898Wallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2024-02-13 Created: 2024-02-13 Last updated: 2025-04-24Bibliographically approved
Calvanese, D. & Lanti, D. (2024). Designing Virtual Knowledge Graphs. In: Guizzardi, G Santoro, F Mouratidis, H Soffer, P (Ed.), Advanced Information Systems Engineering, CAISE 2024: . Paper presented at 36th International Conference on Advanced Information Systems Engineering (CAiSE), JUN 03-07, 2024, Limassol, CYPRUS (pp. 633-634). Springer, 14663
Open this publication in new window or tab >>Designing Virtual Knowledge Graphs
2024 (English)In: Advanced Information Systems Engineering, CAISE 2024 / [ed] Guizzardi, G Santoro, F Mouratidis, H Soffer, P, Springer, 2024, Vol. 14663, p. 633-634Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
Springer, 2024
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:umu:diva-232438 (URN)001284635700038 ()978-3-031-61056-1 (ISBN)978-3-031-61057-8 (ISBN)
Conference
36th International Conference on Advanced Information Systems Engineering (CAiSE), JUN 03-07, 2024, Limassol, CYPRUS
Available from: 2024-12-02 Created: 2024-12-02 Last updated: 2024-12-02Bibliographically approved
Romanenko, E., Calvanese, D. & Guizzardi, G. (2024). Evaluating quality of ontology-driven conceptual models abstractions. Data & Knowledge Engineering, 153, Article ID 102342.
Open this publication in new window or tab >>Evaluating quality of ontology-driven conceptual models abstractions
2024 (English)In: Data & Knowledge Engineering, ISSN 0169-023X, E-ISSN 1872-6933, Vol. 153, article id 102342Article in journal (Refereed) Published
Abstract [en]

The complexity of an (ontology-driven) conceptual model highly correlates with the complexity of the domain and software for which it is designed. With that in mind, an algorithm for producing ontology-driven conceptual model abstractions was previously proposed. In this paper, we empirically evaluate the quality of the abstractions produced by it. First, we have implemented and tested the last version of the algorithm over a FAIR catalog of models represented in the ontology-driven conceptual modeling language OntoUML. Second, we performed three user studies to evaluate the usefulness of the resulting abstractions as perceived by modelers. This paper reports on the findings of these experiments and reflects on how they can be exploited to improve the existing algorithm.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Conceptual model abstraction, FAIR model catalog, Ontology-driven conceptual models, Quality evaluation of abstractions, Unified foundational ontology (UFO), User studies in conceptual modeling
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-228110 (URN)10.1016/j.datak.2024.102342 (DOI)001281253100001 ()2-s2.0-85199337976 (Scopus ID)
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2024-08-02 Created: 2024-08-02 Last updated: 2025-04-24Bibliographically approved
Romanenko, E., Calvanese, D. & Guizzardi, G. (2024). ExpO: towards explaining ontology-driven conceptual models. In: João Araújo; Jose Luis de la Vara; Maribel Yasmina Santos; Saïd Assar (Ed.), Research Challenges in Information Science: 18th International Conference, RCIS 2024, Guimarães, Portugal, May 14–17, 2024, Proceedings, Part II. Paper presented at 18th International Conference, RCIS 2024, Guimarães, Portugal, May 14–17, 2024 (pp. 20-28). Springer Nature
Open this publication in new window or tab >>ExpO: towards explaining ontology-driven conceptual models
2024 (English)In: Research Challenges in Information Science: 18th International Conference, RCIS 2024, Guimarães, Portugal, May 14–17, 2024, Proceedings, Part II / [ed] João Araújo; Jose Luis de la Vara; Maribel Yasmina Santos; Saïd Assar, Springer Nature, 2024, p. 20-28Conference paper, Published paper (Refereed)
Abstract [en]

Ontology-driven conceptual models play an explanatory role in complex and critical domains. However, since those models may consist of a large number of elements, including concepts, relations and sub-diagrams, their reuse or adaptation requires significant efforts. While conceptual model engineers tend to be biased against the removal of information from the models, general users struggle to fully understand them. The paper describes ExpO—a prototype that addresses this trade-off by providing three components: (1) an API that implements model transformations, (2) a software plugin aimed at modelers working with the language OntoUML, and (3) a web application for model exploration mostly designed for domain experts. We describe characteristics of every component and specify scenarios of possible usages.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Business Information Processing (LNBIP), ISSN 1865-1348, E-ISSN 1865-1356 ; 514
Keywords
Ontology-Driven Conceptual Models, OntoUML, Pragmatic explanation, Software Tools
National Category
Computer Sciences Computer Systems
Identifiers
urn:nbn:se:umu:diva-225021 (URN)10.1007/978-3-031-59468-7_3 (DOI)001267235100003 ()2-s2.0-85193607972 (Scopus ID)9783031594670 (ISBN)9783031594687 (ISBN)
Conference
18th International Conference, RCIS 2024, Guimarães, Portugal, May 14–17, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)German Research Foundation (DFG), 500249124
Available from: 2024-06-07 Created: 2024-06-07 Last updated: 2025-04-24Bibliographically approved
Baura, D., Calvanese, D. & Marconi, L. (2024). Implementing controlled query evaluation in OBDA. In: JOWO 2024. The Joint Ontology Workshops: Proceedings of the Joint Ontology Workshops (JOWO) - Episode X: The Tukker Zomer of Ontology, and satellite events co-located with the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024). Paper presented at 2024 Joint Ontology Workshops (JOWO) - Episode X: The Tukker Zomer of Ontology, and satellite events co-located with the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024), Enschede, The Netherlands, July 15-19, 2024. CEUR-WS, Article ID st4cm-1.
Open this publication in new window or tab >>Implementing controlled query evaluation in OBDA
2024 (English)In: JOWO 2024. The Joint Ontology Workshops: Proceedings of the Joint Ontology Workshops (JOWO) - Episode X: The Tukker Zomer of Ontology, and satellite events co-located with the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024), CEUR-WS , 2024, article id st4cm-1Conference paper, Published paper (Refereed)
Abstract [en]

In the Ontology Based Data Access (OBDA) framework, users access a relational data source by querying a domain ontology, whose classes and properties are connected to the data via declarative mappings. OBDA is adopted for data management in various sectors, notably healthcare, where confidentiality of information is a key concern that requires data to be properly protected from unauthorized accesses. Controlled Query Evaluation (CQE) is a framework for privacy-preserving query answering in the presence of an ontology. In CQE, policies are used to represent the information that should be kept confidential, and the aim is to devise from policy specifications suitable censors that enforce data protection. Therefore, it is desirable to integrate CQE in OBDA to obtain a robust privacy-aware data management framework. This has been done in the recently proposed Policy-Protected OBDA (PPOBDA) framework, which ensures the integration of CQE within OBDA by embedding policies into mappings. In this paper, we present an open-source solution that implements PPOBDA and a simplified algorithm for policy embedding, compared to previously proposed ones. This facilitates the adoption of PPOBDA using any OBDA query engine capable of translating SPARQL queries into SQL. In our implementation, we rely on Ontop, a state-of-the-art open-source OBDA tool.

Place, publisher, year, edition, pages
CEUR-WS, 2024
Series
CEUR workshop proceedings, ISSN 1613-0073 ; 3882
Keywords
Controlled Query Evaluation, Ontology Based Data Access, Ontop, Policy-Protected OBDA, Privacy
National Category
Computer Sciences Computer Systems
Identifiers
urn:nbn:se:umu:diva-234314 (URN)2-s2.0-85214567303 (Scopus ID)
Conference
2024 Joint Ontology Workshops (JOWO) - Episode X: The Tukker Zomer of Ontology, and satellite events co-located with the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024), Enschede, The Netherlands, July 15-19, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)German Research Foundation (DFG)
Available from: 2025-01-23 Created: 2025-01-23 Last updated: 2025-01-23Bibliographically approved
Wandji, R. E. & Calvanese, D. (2024). Improving the cost of updates in virtual knowledge graphs. In: Ítalo Oliveira; Pedro Paulo F. Barcelos; Rodrigo Calhau; Claudenir M. Fonseca; Guendalina Righetti (Ed.), JOWO 2024The Joint Ontology Workshops: Proceedings of the Joint Ontology Workshops (JOWO) - Episode X: The Tukker Zomer of Ontology, and satellite events co-located with the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024). Paper presented at 2024 Joint Ontology Workshops - Episode X: The Tukker Zomer of Ontology, and Satellite Events, JOWO 2024, Enschede, The Netherlands, July 15-19, 2024. CEUR-WS, Article ID ST4DM-2.
Open this publication in new window or tab >>Improving the cost of updates in virtual knowledge graphs
2024 (English)In: JOWO 2024The Joint Ontology Workshops: Proceedings of the Joint Ontology Workshops (JOWO) - Episode X: The Tukker Zomer of Ontology, and satellite events co-located with the 14th International Conference on Formal Ontology in Information Systems (FOIS 2024) / [ed] Ítalo Oliveira; Pedro Paulo F. Barcelos; Rodrigo Calhau; Claudenir M. Fonseca; Guendalina Righetti, CEUR-WS , 2024, article id ST4DM-2Conference paper, Published paper (Refereed)
Abstract [en]

Virtual Knowledge Graph (VKG) is known as a data integration paradigm used to efficiently manage the heterogeneity of richly structured data that is common inside several organizations, in inter-organizational settings, and more openly on the Web. Although such a paradigm continues to gain importance in both foundational and applied research, updates in VKG systems remain an open challenge that has received less attention. Yet, a solution to such a problem would be of great importance, as it would allow VKG systems to be full-fledged, thus allowing end-users to fully manage source data through the lens of the ontology they are exposed to. This research aims to propose a comprehensive framework for instance-level updates in VKGs, where updates posed over the ontology have to be translated into source-level updates and, more importantly, how the side effects related to the propagation of ontology-based updates to the underlying data source can be minimized.

Place, publisher, year, edition, pages
CEUR-WS, 2024
Series
CEUR workshop proceedings, ISSN 1613-0073 ; 3882
Keywords
Knowledge Representation, Ontology-based Data Access, View Updates, Virtual Knowledge Graph (VKG)
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-234330 (URN)2-s2.0-85214562956 (Scopus ID)
Conference
2024 Joint Ontology Workshops - Episode X: The Tukker Zomer of Ontology, and Satellite Events, JOWO 2024, Enschede, The Netherlands, July 15-19, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)German Research Foundation (DFG)
Available from: 2025-01-21 Created: 2025-01-21 Last updated: 2025-01-21Bibliographically approved
Ding, L., Xiao, G., Pano, A., Fumagalli, M., Chen, D., Feng, Y., . . . Meng, L. (2024). Integrating 3D city data through knowledge graphs. Geo-spatial Information Science
Open this publication in new window or tab >>Integrating 3D city data through knowledge graphs
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2024 (English)In: Geo-spatial Information Science, ISSN 1009-5020, E-ISSN 1993-5153Article in journal (Refereed) Epub ahead of print
Abstract [en]

CityGML is a widely adopted standard for representing and exchanging 3D city models. The representation of semantic and topological properties in CityGML makes it possible to query such 3D city data for analysis in various applications. Nevertheless, the potential of querying CityGML data has not been fully exploited. The official GML encoding of CityGML is mainly an information model used for data storage and exchange, but not suitable for performing complex queries. The most common way of dealing with CityGML data is to store them as tables in the 3DCityDB system. However, it remains a challenging task for end users to formulate SQL queries over 3DCityDB directly for their ad-hoc analytical tasks because of the gap between the semantics of CityGML and the relational schema adopted in 3DCityDB. The technology of Knowledge Graphs (KGs), where an ontology is at the core, is a good solution to bridge such a gap. Moreover, embracing KGs makes it easier to integrate with other spatial data sources, e.g. OpenStreetMap, and to perform queries combining information from multiple data sources. In this work, we describe a CityGML-KG framework to expose the CityGML data in 3DCityDB as a KG. To evaluate our approach, we use CityGML data from the city of Munich as a test area and integrate OpenStreetMap data.

Place, publisher, year, edition, pages
Taylor & Francis, 2024
Keywords
CityGML, data integration, geospatial knowledge graph, ontology, OpenStreetMap, query answering
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-225275 (URN)10.1080/10095020.2024.2337360 (DOI)001207981700001 ()2-s2.0-85191075877 (Scopus ID)
Available from: 2024-06-10 Created: 2024-06-10 Last updated: 2025-04-24
Gu, Z., Calvanese, D., Panfilo, M. D., Lanti, D., Mosca, A. & Xiao, G. (2024). OBDF: OBDA + data federation - extended abstract. In: 2024 IEEE 40th international conference on data engineering workshops (ICDEW): . Paper presented at 40th IEEE International Conference on Data Engineering Workshops, ICDEW 2024, Utrecht, Netherlands, May 13-16, 2024 (pp. 381-383). IEEE
Open this publication in new window or tab >>OBDF: OBDA + data federation - extended abstract
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2024 (English)In: 2024 IEEE 40th international conference on data engineering workshops (ICDEW), IEEE, 2024, p. 381-383Conference paper, Published paper (Refereed)
Abstract [en]

Ontology-Based Data Access (OBDA) has emerged as a well-established approach to information management, facilitating access to a sole relational relational database via a high-level ontology and declarative mappings. In response to the challenges posed by Big Data, we propose the Ontology-Based Data Federation (OBDF) framework, which merges OBDA with Data Federation. This merging allows for the integration of numerous, distributed, and heterogeneous data sources in a virtual, uniform, and semantically coherent fashion.

Place, publisher, year, edition, pages
IEEE, 2024
Series
IEEE International Conference on Data Engineering workshop, ISSN 1943-2895, E-ISSN 2473-3490
Keywords
Data Federation, OBDA, OBDF, Query Optimization, VKG
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-227843 (URN)10.1109/ICDEW61823.2024.00060 (DOI)001259407300040 ()2-s2.0-85197355040 (Scopus ID)9798350384031 (ISBN)9798350384048 (ISBN)
Conference
40th IEEE International Conference on Data Engineering Workshops, ICDEW 2024, Utrecht, Netherlands, May 13-16, 2024
Funder
EU, European Research Council, 101135513
Available from: 2024-07-11 Created: 2024-07-11 Last updated: 2025-04-24Bibliographically approved
Wandji, R. E. & Calvanese, D. (2024). Ontology-based update in virtual knowledge graphs via schema mapping recovery. In: Rules and Reasoning: 8th International Joint Conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024, Proceedings. Paper presented at 8th International Joint Conference on Rules and Reasoning, RuleML+RR 2024, Bucharest, Romania, September 16-18, 2024 (pp. 59-74). Springer Nature
Open this publication in new window or tab >>Ontology-based update in virtual knowledge graphs via schema mapping recovery
2024 (English)In: Rules and Reasoning: 8th International Joint Conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024, Proceedings, Springer Nature, 2024, p. 59-74Conference paper, Published paper (Refereed)
Abstract [en]

In Virtual Knowledge Graphs (VKGs), access to a relational data source is provided through an ontology, which is linked to the data source via declarative mappings. VKGs stand as a predominant paradigm for the access to (and integration of) heterogeneous data sources. However, little attention has been paid so far to the issue of updates in VKGs expressed over the ontology, which represents a crucial feature for fully managing data sources through the lens of an ontology. In this paper, we consider the problem of updating a VKG instance by specifying a set of insertions and deletions of ontology instances and propagating these updates to the underlying data source through the VKG mapping. We consider ontologies specified in the DL-LiteR lightweight ontology language and study the problem for the case where source queries in mappings are unions of conjunctive queries. We rely on the notion of maximum recovery of VKG mappings, borrowed from the data exchange setting, and propose methods to compute the set of source updates that translate an ontology update with a minimal side-effect, considering both insertions and deletions of multiple ABox assertions.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Computer Science, ISSN 03029743, E-ISSN 16113349 ; 15183
Keywords
Knowledge Representation, Ontology-based Data Access, View Updates, Virtual Knowledge Graph (VKG)
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-230585 (URN)10.1007/978-3-031-72407-7_6 (DOI)001329984900006 ()2-s2.0-85205112822 (Scopus ID)978-3-031-72406-0 (ISBN)978-3-031-72407-7 (ISBN)
Conference
8th International Joint Conference on Rules and Reasoning, RuleML+RR 2024, Bucharest, Romania, September 16-18, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

Included in the following conference series:

International Joint Conference on Rules and Reasoning.

Available from: 2024-10-08 Created: 2024-10-08 Last updated: 2025-04-24Bibliographically approved
Ghosh, A., Pano, A., Xiao, G. & Calvanese, D. (2024). OntoRaster: extending VKGs with raster data. In: Rules and reasoning: 8th International Joint Conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024, Proceedings. Paper presented at International Joint Conference on Rules and Reasoning (RuleML+RR 2024), Bucharest, Romania, September 16-18, 2024 (pp. 108-123). Springer Nature
Open this publication in new window or tab >>OntoRaster: extending VKGs with raster data
2024 (English)In: Rules and reasoning: 8th International Joint Conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024, Proceedings, Springer Nature, 2024, p. 108-123Conference paper, Published paper (Refereed)
Abstract [en]

The Virtual Knowledge Graph (VKG) paradigm facilitates access to large heterogeneous data sources by leveraging an OWL 2 QL ontology representing the domain knowledge and a set of declarative R2RML mapping assertions. We are interested in heterogeneous data sources consisting of relational data together with spatial geometrical data (a.k.a. vector data) and large multidimensional raster data. The latter forms of data pose a significant challenge for traditional DBMSs to manage effectively and are instead efficiently processed by tailored array database management systems (ArrayDBMSs). To query such data within the VKG paradigm, we propose a novel framework, called OntoRaster, that allows for integrated query processing of relational, raster, and vector data, by keeping each type of data in the system tailored for their efficient processing, while minimising costly data-transfer operations. In OntoRaster, we devised custom raster functions extending SPARQL to query raster data efficiently and developed mechanisms for delegating their computation to the ArrayDBMS. We have implemented the whole framework as an extension of the state-of-the-art VKG system Ontop and have demonstrated its effectiveness and efficiency through a curated case study.

Place, publisher, year, edition, pages
Springer Nature, 2024
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 15183
Keywords
Virtual Knowledge Graphs, Spatial-Temporal Reasoning, Raster Data, Vector Data, Multidimensional Arrays, Query Answering
National Category
Computer Sciences
Identifiers
urn:nbn:se:umu:diva-230514 (URN)10.1007/978-3-031-72407-7_9 (DOI)001329984900009 ()2-s2.0-85205118775 (Scopus ID)978-3-031-72406-0 (ISBN)978-3-031-72407-7 (ISBN)
Conference
International Joint Conference on Rules and Reasoning (RuleML+RR 2024), Bucharest, Romania, September 16-18, 2024
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2024-10-04 Created: 2024-10-04 Last updated: 2025-04-24Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5174-9693

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