Research Article
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Year 2023, Volume: 13 Issue: 2, 130 - 141, 31.12.2023
https://doi.org/10.36222/ejt.1402149

Abstract

References

  • [1] C. Bizer, T. Heath, T. Berners-Lee “Linked data: the story so far”, Linking the World’s Information: Essays on Tim Berners- Lee’s Invention of the World Wide Web, Association for Computing Machinery (ACM), New York, NY, United States, pp. 115-143, September 2023.
  • [2] E. Curry, S. Scerri, T. Tuikka (ed.), Data Spaces: Design, Deployment and Future Directions. Springer Nature, 2022.
  • [3] E. Curry, Real-time Linked Dataspaces: Enabling Data Ecosystems for Intelligent Systems. Springer Nature, 2020.
  • [4] T. Heath, C. Bizer, Linked Data: Evolving the Web into a Global Data Space. Springer Nature, 2022.
  • [5] M. Franklin, A. Halevy, D. Maier. “From databases to dataspaces: a new abstraction for information management,” ACM Sigmod Record, vol 34, no. 4, pp. 27-33, 2005.
  • [6] A. Halevy, M. Franklin, D. Maier. “Principles of dataspace systems,” Twenty-fifth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 1-9, 2006.
  • [7] M. Herschel, R. Diestelkämper, H. Ben Lahmar, “A survey on provenance: what for? what form? what from?,” The VLDB Journal, vol. 26, pp. 881-906, 2017.
  • [8] L.Moreau, P. Groth, Provenance: An Introduction to PROV. Springer Nature, 2022.
  • [9] L. Moreau, B. Clifford, J. Freire, J. Futrelle, Y. Gil, P. Groth, N. Kwasnikowska, S. Miles, P. Missier, J. Myers, B. Plale, Y. Simmhan, E. Stephan, J. V. den Bussche, “The open provenance model core specification (v1.1),” Future Generation Computer Systems, vol. 27, no. 6, pp. 743-756, 2011.
  • [10] Internet: O. Hartig, J. Zhao, Provenance Vocabulary Core Ontology Specification, https://trdf.sourceforge.net/provenance/ns.html, 02.12.2023.
  • [11] Internet: K. Belhajjame, J. Cheney, D. Corsar, D. Garijo, S. Soiland-Reyes, S. Zednik, J. Zhao. T.Lebo, S. Sahoo, D. McGuinness (eds.), PROV-O: The PROV Ontology, https://www.w3.org/TR/prov-o/, 02.12.2023.
  • [12] P. Missier, K. Belhajjame, J. Cheney, “The w3c prov family of specifications for modelling provenance metadata,” Proceedings of the 16th International Conference on Extending Database Technology (EDBT’13), Genoa, Italy, pp. 773-776, 18-22 March 2013.
  • [13] C. Baillie, P. Edwards, E. Pignotti, D. Corsar, “Short paper: assessing the quality of semantic sensor data,” Proceedings of the Sixth International Workshop on Semantic Sensor Networks (SSN’13), 1063, pp. 71-76, 22 October 2013.
  • [14] M. Markovic, P. Edwards, D. Corsar, “Utilising provenance to enhance social computation,” 12th International Semantic Web Conference (ISWC 2013), Sydney, NSW, Australia, Springer Berlin Heidelberg, pp. 440-447, October 21-25, 2013.
  • [15] P. Missier, S. Dey, K. Belhajjame, V. Cuevas-Vicenttín, B. Ludäscher, “{D-prov}: extending the {prov} provenance model with {workflow} structure,” 5th USENIX Workshop on the Theory and Practice of Provenance (TaPP 13), pp. 1-7, 2013.
  • [16] K. Belhajjame, J. Zhao, D. Garijo, M. Gamble, K. Hettne, R. Palma, E. Mina, O. Corcho, j. M. Gomez-Perez, S. Bechhofer, G. Klyne, C. Goble, “Using a suite of ontologies for preserving workflow-centric research objects,” Journal of Web Semantics, vol. 32, pp. 16-42, May 2015.
  • [17] L. McKenna, C. Debruyne, D. O'Sullivan, “Modelling the provenance of linked data interlinks for the library domain”, Companion Proceedings of the 2019 World Wide Web Conference (WWW’19), pp. 954-958, May 2019.
  • [18] Internet: P. Ciccarese, S. Soiland-Reyes, PAV - Provenance, Authoring and Versioning, http://pav-ontology.github.io/pav/, 04.12.2023
  • [19] P. Ciccarese, S. Soiland-Reyes, K. Belhajjame, A. J. Gray, C. Goble, T. Clark, “PAV ontology: provenance, authoring and versioning,” Journal of Biomedical Semantics, vol. 4, pp. 1-22, 2013.
  • [20] L. Rietveld, W. Beek, R. Hoekstra, S. Schlobach, “Meta-data for a lot of lod,” Semantic Web, vol. 8, no. 6, pp. 1067-1080, 2017.
  • [21] K. Alexander, R. Cyganiak, M. Hausenblas, J. Zhao, “Describing linked datasets-on the design and usage of void, the vocabulary of interlinked datasets,” Proceedings of the Linked Data Workshop at WWW09 (LDOW’09), Madrid, Spain, 2009.
  • [22] Internet: J. Zhao, K. Alexander, M. Hausenblas, R. Cyganiak, Digital Enterprise Research Institute, Vocabulary of Interlinked Datasets (VoID), http://vocab.deri.ie/void, 02.12.2023.
  • [23] T. Omitola, L. Zuo, C. Gutteridge, I. C. Millard, H. Glaser, N. Gibbins, N. Shadbolt, “Tracing the provenance of linked data using void,” Proceedings of the International Conference on Web Intelligence, Mining and Semantics (WIMS’11), pp. 1-7, 2011.
  • [24] A. Vercruysse, S. Min Oo, P. Colpaert, “Describing a network of live datasets with the sds vocabulary,” Managing the Evolution and Preservation of the Data Web (MEPDaW2022), pp. 1-6, 2022.
  • [25] Z. Gu, F. Corcoglioniti, D. Lanti, A. Mosca, G. Xiao, J. Xiong, D. Calvanese, “A systematic overview of data federation systems,” Semantic Web, pp. 1-59, 2022.
  • [26] O. Görlitz, S. Staab, “Splendid: sparql endpoint federation exploiting void descriptions,” Second International Workshop on Consuming Linked Data (COLD’11), 782, 2011.
  • [27] Z. Akar, T. G. Halaç, E. E. Ekinci, O. Dikenelli, “Querying the web of interlinked datasets using void descriptions,” Workshop on Linked Data on the Web (LDOW’12), 937, 2012.
  • [28] L. Heling, M. Acosta, “Federated sparql query processing over heterogeneous linked data fragments,” Proceedings of the ACM Web Conference, pp. 1047-1057, Virtual, 25-29 April 2022.
  • [29] R. C. Erdur, O. Alatli, T. G. Halaç, O. Dikenelli, “Monitoring the dynamism of the linked data space through environment abstraction,” 9th International Conference on Semantic Systems (I-SEMANTICS’13), New York, NY, USA, ACM, pp. 81-88, September 2013.
  • [30] L. F. Sikos, D. Philp, “Provenance-aware knowledge representation: a survey of data models and contextualized knowledge graphs,” Data Science and Engineering, vol. 5, pp. 293-316, 2020.
  • [31] C. Böhm, J. Lorey, F. Naumann, “Creating void descriptions for web-scale data,” Journal of Web Semantics, vol. 9, no. 3, pp. 339-345, 2011.
  • [32] M. Mountantonakis, C. Allocca, P. Fafalios, N. Minadakis, Y. Marketakis, C. Lantzaki, Y. Tzitzikas. “Extending void for expressing connectivity metrics of a semantic warehouse,” Proceedings of the PROFILES@ ESWC, Anissaras, Greece, 26 May 2014.
  • [33] A. Hogan, “Web of data,” The Web of Data, Springer International Publishing, pp. 15-57, 2020.
  • [34] Internet: S. Weibel, J. Kunze, C. Lagoze, M. Wolf, Dublin Core Metadata for Resource Discovery, https://www.rfc-editor.org/rfc/rfc2413, 05.12.2023.
  • [35] P. Groth, Y. Gil, J. Cheney, S. Miles, “Requirements for provenance on the web,” International Journal of Digital Curation, vol. 7, no. 1, pp. 39-56, 2012.
  • [36] Internet: D. Reynolds (ed.), The Organization Ontology, https://www.w3.org/TR/vocab-org/, 06.12.2023.
  • [37] C. Bizer, “Semantic web publishing vocabulary (swp) user manual,” Freie Universitat Berlin, November 2006.
  • [38] R. Dividino, G. Gröner, S. Scheglmann, M. Thimm, “Ranking rdf with provenance via preference aggregation,” 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2012), Galway City, Ireland, Springer Berlin Heidelberg, pp. 154-163, October 8-12, 2012.
  • [39] A. Toniolo, F. Cerutti, N. Oren, T. J. Norman, K. Sycara, “Making informed decisions with provenance and argumentation schemes,” Proceedings of the Eleventh International Workshop on Argumentation in Multi-Agent Systems (ArgMAS’14), 2014.
  • [40] A. Kale, T. Nguyen, F. C. Harris Jr, C. Li, J. Zhang, X. Ma, “Provenance documentation to enable explainable and trustworthy ai: a literature review,” Data Intelligence, vol. 5, no. 1, pp. 139-162, 2023.
  • [41] R. Das, M. Soylu, “A key review on graph data science: The power of graphs in scientific studies,” Chemometrics and Intelligent Laboratory Systems, vol.240, 104896, 15 September 2023.
  • [42] K. Mukherjee, J. Wiedemeier, T. Wang, M. Kim, F. Chen, M. Kantarcioglu, K. Jee, “Interpreting gnn-based ids detections using provenance graph structural features,” arXiv preprint arXiv:2306.00934, 2023.
  • [43] M. Soylu, A. Soylu, R. Das, “A new approach to recognizing the use of attitude markers by authors of academic journal articles,”, Expert Systems with Applications, vol. 230, 120538, 15 November 2023.
  • [44] F. Tekbacak, “Açık bağlı veri sistemlerinde köken bazlı erişi, m gerçekleştirimi,” Doctoral dissertation, Computer Engineering Department, Ege University, Izmir, Turkey, 2015.

Data Management and Ontology Development for Provenance-Aware Organizations in Linked Data Space

Year 2023, Volume: 13 Issue: 2, 130 - 141, 31.12.2023
https://doi.org/10.36222/ejt.1402149

Abstract

The need to track the origin of shared data/datasets has become apparent, highlighting the necessity of monitoring factors such as trust related to the data/datasets with the widespread use of social media. The concept of Linked Data Space needs to be considered in conjunction with organizations and their provenance with respect to their origin assuming that the shared data is semantic and considering organizations' access to relevant semantic data. In this context, this study elaborates on the concept of Linked Data Space, introducing the terms Internal Data and External Data to the literature. An architecture for Linked Data Space and data management for organizations is defined in addition to these concepts. Furthermore, the study explains how organizations can access External Data in the Linked Data Space and how provenance metadata and ontologies will be created. These developed methods are illustrated in the News Aggregator Scenario, a main scenario for provenance, demonstrating how it can work in a use case.

References

  • [1] C. Bizer, T. Heath, T. Berners-Lee “Linked data: the story so far”, Linking the World’s Information: Essays on Tim Berners- Lee’s Invention of the World Wide Web, Association for Computing Machinery (ACM), New York, NY, United States, pp. 115-143, September 2023.
  • [2] E. Curry, S. Scerri, T. Tuikka (ed.), Data Spaces: Design, Deployment and Future Directions. Springer Nature, 2022.
  • [3] E. Curry, Real-time Linked Dataspaces: Enabling Data Ecosystems for Intelligent Systems. Springer Nature, 2020.
  • [4] T. Heath, C. Bizer, Linked Data: Evolving the Web into a Global Data Space. Springer Nature, 2022.
  • [5] M. Franklin, A. Halevy, D. Maier. “From databases to dataspaces: a new abstraction for information management,” ACM Sigmod Record, vol 34, no. 4, pp. 27-33, 2005.
  • [6] A. Halevy, M. Franklin, D. Maier. “Principles of dataspace systems,” Twenty-fifth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 1-9, 2006.
  • [7] M. Herschel, R. Diestelkämper, H. Ben Lahmar, “A survey on provenance: what for? what form? what from?,” The VLDB Journal, vol. 26, pp. 881-906, 2017.
  • [8] L.Moreau, P. Groth, Provenance: An Introduction to PROV. Springer Nature, 2022.
  • [9] L. Moreau, B. Clifford, J. Freire, J. Futrelle, Y. Gil, P. Groth, N. Kwasnikowska, S. Miles, P. Missier, J. Myers, B. Plale, Y. Simmhan, E. Stephan, J. V. den Bussche, “The open provenance model core specification (v1.1),” Future Generation Computer Systems, vol. 27, no. 6, pp. 743-756, 2011.
  • [10] Internet: O. Hartig, J. Zhao, Provenance Vocabulary Core Ontology Specification, https://trdf.sourceforge.net/provenance/ns.html, 02.12.2023.
  • [11] Internet: K. Belhajjame, J. Cheney, D. Corsar, D. Garijo, S. Soiland-Reyes, S. Zednik, J. Zhao. T.Lebo, S. Sahoo, D. McGuinness (eds.), PROV-O: The PROV Ontology, https://www.w3.org/TR/prov-o/, 02.12.2023.
  • [12] P. Missier, K. Belhajjame, J. Cheney, “The w3c prov family of specifications for modelling provenance metadata,” Proceedings of the 16th International Conference on Extending Database Technology (EDBT’13), Genoa, Italy, pp. 773-776, 18-22 March 2013.
  • [13] C. Baillie, P. Edwards, E. Pignotti, D. Corsar, “Short paper: assessing the quality of semantic sensor data,” Proceedings of the Sixth International Workshop on Semantic Sensor Networks (SSN’13), 1063, pp. 71-76, 22 October 2013.
  • [14] M. Markovic, P. Edwards, D. Corsar, “Utilising provenance to enhance social computation,” 12th International Semantic Web Conference (ISWC 2013), Sydney, NSW, Australia, Springer Berlin Heidelberg, pp. 440-447, October 21-25, 2013.
  • [15] P. Missier, S. Dey, K. Belhajjame, V. Cuevas-Vicenttín, B. Ludäscher, “{D-prov}: extending the {prov} provenance model with {workflow} structure,” 5th USENIX Workshop on the Theory and Practice of Provenance (TaPP 13), pp. 1-7, 2013.
  • [16] K. Belhajjame, J. Zhao, D. Garijo, M. Gamble, K. Hettne, R. Palma, E. Mina, O. Corcho, j. M. Gomez-Perez, S. Bechhofer, G. Klyne, C. Goble, “Using a suite of ontologies for preserving workflow-centric research objects,” Journal of Web Semantics, vol. 32, pp. 16-42, May 2015.
  • [17] L. McKenna, C. Debruyne, D. O'Sullivan, “Modelling the provenance of linked data interlinks for the library domain”, Companion Proceedings of the 2019 World Wide Web Conference (WWW’19), pp. 954-958, May 2019.
  • [18] Internet: P. Ciccarese, S. Soiland-Reyes, PAV - Provenance, Authoring and Versioning, http://pav-ontology.github.io/pav/, 04.12.2023
  • [19] P. Ciccarese, S. Soiland-Reyes, K. Belhajjame, A. J. Gray, C. Goble, T. Clark, “PAV ontology: provenance, authoring and versioning,” Journal of Biomedical Semantics, vol. 4, pp. 1-22, 2013.
  • [20] L. Rietveld, W. Beek, R. Hoekstra, S. Schlobach, “Meta-data for a lot of lod,” Semantic Web, vol. 8, no. 6, pp. 1067-1080, 2017.
  • [21] K. Alexander, R. Cyganiak, M. Hausenblas, J. Zhao, “Describing linked datasets-on the design and usage of void, the vocabulary of interlinked datasets,” Proceedings of the Linked Data Workshop at WWW09 (LDOW’09), Madrid, Spain, 2009.
  • [22] Internet: J. Zhao, K. Alexander, M. Hausenblas, R. Cyganiak, Digital Enterprise Research Institute, Vocabulary of Interlinked Datasets (VoID), http://vocab.deri.ie/void, 02.12.2023.
  • [23] T. Omitola, L. Zuo, C. Gutteridge, I. C. Millard, H. Glaser, N. Gibbins, N. Shadbolt, “Tracing the provenance of linked data using void,” Proceedings of the International Conference on Web Intelligence, Mining and Semantics (WIMS’11), pp. 1-7, 2011.
  • [24] A. Vercruysse, S. Min Oo, P. Colpaert, “Describing a network of live datasets with the sds vocabulary,” Managing the Evolution and Preservation of the Data Web (MEPDaW2022), pp. 1-6, 2022.
  • [25] Z. Gu, F. Corcoglioniti, D. Lanti, A. Mosca, G. Xiao, J. Xiong, D. Calvanese, “A systematic overview of data federation systems,” Semantic Web, pp. 1-59, 2022.
  • [26] O. Görlitz, S. Staab, “Splendid: sparql endpoint federation exploiting void descriptions,” Second International Workshop on Consuming Linked Data (COLD’11), 782, 2011.
  • [27] Z. Akar, T. G. Halaç, E. E. Ekinci, O. Dikenelli, “Querying the web of interlinked datasets using void descriptions,” Workshop on Linked Data on the Web (LDOW’12), 937, 2012.
  • [28] L. Heling, M. Acosta, “Federated sparql query processing over heterogeneous linked data fragments,” Proceedings of the ACM Web Conference, pp. 1047-1057, Virtual, 25-29 April 2022.
  • [29] R. C. Erdur, O. Alatli, T. G. Halaç, O. Dikenelli, “Monitoring the dynamism of the linked data space through environment abstraction,” 9th International Conference on Semantic Systems (I-SEMANTICS’13), New York, NY, USA, ACM, pp. 81-88, September 2013.
  • [30] L. F. Sikos, D. Philp, “Provenance-aware knowledge representation: a survey of data models and contextualized knowledge graphs,” Data Science and Engineering, vol. 5, pp. 293-316, 2020.
  • [31] C. Böhm, J. Lorey, F. Naumann, “Creating void descriptions for web-scale data,” Journal of Web Semantics, vol. 9, no. 3, pp. 339-345, 2011.
  • [32] M. Mountantonakis, C. Allocca, P. Fafalios, N. Minadakis, Y. Marketakis, C. Lantzaki, Y. Tzitzikas. “Extending void for expressing connectivity metrics of a semantic warehouse,” Proceedings of the PROFILES@ ESWC, Anissaras, Greece, 26 May 2014.
  • [33] A. Hogan, “Web of data,” The Web of Data, Springer International Publishing, pp. 15-57, 2020.
  • [34] Internet: S. Weibel, J. Kunze, C. Lagoze, M. Wolf, Dublin Core Metadata for Resource Discovery, https://www.rfc-editor.org/rfc/rfc2413, 05.12.2023.
  • [35] P. Groth, Y. Gil, J. Cheney, S. Miles, “Requirements for provenance on the web,” International Journal of Digital Curation, vol. 7, no. 1, pp. 39-56, 2012.
  • [36] Internet: D. Reynolds (ed.), The Organization Ontology, https://www.w3.org/TR/vocab-org/, 06.12.2023.
  • [37] C. Bizer, “Semantic web publishing vocabulary (swp) user manual,” Freie Universitat Berlin, November 2006.
  • [38] R. Dividino, G. Gröner, S. Scheglmann, M. Thimm, “Ranking rdf with provenance via preference aggregation,” 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2012), Galway City, Ireland, Springer Berlin Heidelberg, pp. 154-163, October 8-12, 2012.
  • [39] A. Toniolo, F. Cerutti, N. Oren, T. J. Norman, K. Sycara, “Making informed decisions with provenance and argumentation schemes,” Proceedings of the Eleventh International Workshop on Argumentation in Multi-Agent Systems (ArgMAS’14), 2014.
  • [40] A. Kale, T. Nguyen, F. C. Harris Jr, C. Li, J. Zhang, X. Ma, “Provenance documentation to enable explainable and trustworthy ai: a literature review,” Data Intelligence, vol. 5, no. 1, pp. 139-162, 2023.
  • [41] R. Das, M. Soylu, “A key review on graph data science: The power of graphs in scientific studies,” Chemometrics and Intelligent Laboratory Systems, vol.240, 104896, 15 September 2023.
  • [42] K. Mukherjee, J. Wiedemeier, T. Wang, M. Kim, F. Chen, M. Kantarcioglu, K. Jee, “Interpreting gnn-based ids detections using provenance graph structural features,” arXiv preprint arXiv:2306.00934, 2023.
  • [43] M. Soylu, A. Soylu, R. Das, “A new approach to recognizing the use of attitude markers by authors of academic journal articles,”, Expert Systems with Applications, vol. 230, 120538, 15 November 2023.
  • [44] F. Tekbacak, “Açık bağlı veri sistemlerinde köken bazlı erişi, m gerçekleştirimi,” Doctoral dissertation, Computer Engineering Department, Ege University, Izmir, Turkey, 2015.
There are 44 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other)
Journal Section Research Article
Authors

Fatih Soygazi 0000-0001-8426-2283

Tuğkan Tuğlular 0000-0001-6797-3913

Oğuz Dikenelli 0000-0001-7948-7453

Publication Date December 31, 2023
Submission Date December 8, 2023
Acceptance Date December 26, 2023
Published in Issue Year 2023 Volume: 13 Issue: 2

Cite

APA Soygazi, F., Tuğlular, T., & Dikenelli, O. (2023). Data Management and Ontology Development for Provenance-Aware Organizations in Linked Data Space. European Journal of Technique (EJT), 13(2), 130-141. https://doi.org/10.36222/ejt.1402149

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