This paper has presented a semantic framework for the specification and management of constraints on a geographical domain. Our framework supports the validation of conditions on a geographic area, the composition of land patches into broader areas having homogeneous properties and the identification of paths satisfying given sets of constraints for connecting land patches. We represent both the domain knowledge and the constraints as OWL ontologies based on standard languages for knowledge rep-resentation and reasoning. This approach has several advantages: first of all, it does not introduce any special language for the management of constraints. Second, it fully exploits the knowledge representation and reasoning interoperability provided by Se-mantic Web languages. Third, it opens the avenue to the classification of constraints for their automated management within reasoners that can adapt to solve a possibly large range of reasoning problems.
As a test-bed we use the Ecological Networks domain. In this context, we aim at supporting both the compliance verification with respect to a pre-defined Ecological Network and the generation of a new one by suggesting suitable aggregations of land patches into EN elements. Moreover, our approach is designed to support full-fledged implementations of creation and modification tasks in order to enable the automated suggestion of modifications to existing EN elements through suitable interventions.
Whereas we implemented reasoning about ENs as a stand-alone model, the main mo-tivation and application of our work lies in its possible integration within Participatory Geographical Information Systems (PGIS, [47]), in order to support online interaction with stakeholders in inclusive urban planning and design processes aimed at collecting feedback and EN project proposals from stakeholders.
Our work can be extended in several directions to provide a suitable decision sup-port system . For instance, we plan to:
– Extend the EN ontology to model finer-grained concepts. For instance, we currently describe a land patch by exclusively considering its use; e.g., wetland and wooden land. In our future work we may consider the association of more specific informa-tion with patches by exploiting existing ontologies to model further environment and ecology concepts, e.g., ENVO [10] and EcoCore [9].
– Extend the Constraint ontology to specify more types of constraints, such as soft constraints for guiding the automated reasoners offered by the framework to com-pute solutions that maximize some preference criteria, and geometric constraints about the shape, size, and other properties of given areas.
– Extend our reasoning framework with the ability to handle soft constraints, and with additional reasoners; e.g., for proposing maintenance and modification inter-ventions on an EN.
7 Acknowledgements
We thank Adriano Savoca and Marco Corona for their contributions to this work.
References
1. Abrahao, E., Hirakawa, A.: Complex task ontology conceptual modelling: Towards the de-velopment of the agriculture operations task ontology. In: Proc. of 10th Int. Joint Conf.
on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KEOD 2018). SCITEPRESS, Seville, Spain (2018)
2. Ahuja, R.K., Mehlhorn, K., Orlin, J., Tarjan, R.E.: Faster algorithms for the shortest path problem. Journal of the ACM (JACM) 37(2), 213–223 (1990)
3. Apache: Apache jena. https://jena.apache.org/ (2019)
4. Battle, R., Kolas, D.: Enabling the geospatial Semantic Web with Parliament and GeoSPARQL. Semantic Web 3(4), 355–370 (2012)
5. Benedict, M., McMahon, E.: Green Infrastructure: smart conservation for the 21st century.
Watch Clearinghouse Monograph Series, Sprawl (2002)
6. Bennett, G., Mulongoy, K.: Review of experience with ecological networks, corridors and buffer zones. Technical Series 23 (2006)
7. Bennett, G., Wit, P.: The development and application of ecological networks: a review of proposals, plans and programmes. AIDEnvironment (2001)
8. Boley, H., Tabet, S., Wagner, G.: Design rationale of ruleml: A markup language for semantic web rules. In: Proceedings of the First Int. Conf. on Semantic Web Working. pp. 381–401.
CEUR-WS. org (2001)
9. Buttigieg, P.L.: Ecology Core Ontology. https://github.com/EcologicalSemantics/
ecocore(2018), accessed: 2018-07-28
10. Buttigieg, P.L., Pafilis, E., Lewis, S.E., Schildhauer, M.P., Walls, R.L., Mungall, C.J.: The environment ontology in 2016: bridging domains with increased scope, semantic density, and interoperation. Journal of biomedical semantics 7(1), 57 (2016)
11. Citt`a Metropolitana di Torino: Misura 323 del PSR 2007-2013. http://www.
cittametropolitana.torino.it/cms/territorio-urbanistica/misura-323/misura-323-sperimentale(2014)
12. Citt`a Metropolitana di Torino: Torino Metropoli - Citt`a Metropolitana di Torino. http://
www.cittametropolitana.torino.it(2019)
13. Council of Europe: General guidelines for the development of the pan-european ecological network. Nature and environment 107 (2000)
14. ENEA: Agenzia nazionale per le nuove tecnologie, l’energia e lo sviluppo economico sostenibile. http://www.enea.it/it (2019)
15. Fath, B., Sharler, U., Ulanowicz, R., Hannon, B.: Ecological network analysis: network con-struction. Trends in Ecology & Evolution 208, 49–55 (2007)
16. Felfernig, A., Friedrich, G., Jannach, D., Zanker, M.: Configuration knowledge representa-tion using UML/OCL. In: Internarepresenta-tional Conference on the Unified Modeling Language. pp.
49–62. Springer (2002)
17. Fonseca, F., Egenhofer, M., Agouris, P., Cˆamara, G.: Using ontologies for geographic infor-mation systems. Transactions in GIS 3, 231–257 (2002)
18. Fonseca, F., Egenhofer, M., C.A. Davis, Cˆamara, G.: Semantic granularity in ontology-driven geographic information systems. Annals of Mathematics and Artificial Intelligence 36(1-2), 121–151 (2002)
19. GeoNames.org: Geonames mappings ontology. http://www.geonames.org/ontology/
mappings\_v3.01.rdf(2018)
20. GeoNames.org: Geonames. http://www.geonames.org/ (2019)
21. Gobluski, A., Westlund, E., Vandermeer, J., Pascual, M.: Ecological networks over the edge:
Hypergraph trait-mediated indirect interaction (TMII) structure. Trends in Ecology & Evo-lution 31(5), 344354 (2016)
22. Gray, P., Hui, K., Preece, A.: An expressive constraint language for semantic web appli-cations. In: E-Business and the Intelligent Web: Papers from the IJCAI-01 Workshop. pp.
46–53 (2001)
23. Object Management Group, O.: Unified Modeling Language (UML. http://www.uml.org (2008)
24. Gruber, T.: Towards principles for the design of ontologies used for knowledge sharing. Int.
Journal of Human-Computer Studies 43(5-6), 907–928 (1995)
25. Guarino, N., Oberle, D., Staab, S.: What is an ontology? In: Staab, S., Studer, R. (eds.) Handbook of Ontologies, pp. 1–17. Springer (2009)
26. Hall, M., Mandl, P.: Spatially extended ontologies for a semantic model of harmonised lan-duse and landcover information (04 2006)
27. Horrocks, I., Patel-Schneider, P., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A semantic web rule language combining OWL and RuleML. W3C Member submission 21 (2004)
28. Ingaramo, R., Salizzoni, E., Voghera, A.: La valutazione dei servizi ecosistemici forestali per la pianificazione e il progetto del territorio e del paesaggio. Valori e valutazioni 19, 65–78 (2018)
29. Janowicz, K., Scheider, S., Pehle, T., Ha, G.: Geospatial semantics and linked spatiotem-poral data past, present, and future. Semantic Web - On linked spatiotemspatiotem-poral data and geo-ontologies 3(4), 321–332 (2012)
30. Janowicz, K., Scheider, S., Pehle, T., Ha, G.: LinkedGeoData: A core for a web of spatial open data. Semantic Web Interoperability, Usability, Applicability 3(4), 333–354 (2012) 31. Jongman, R.: Nature conservation planning in Europe: developing ecological networks.
Landscape and urban planning 32(3), 169–183 (1995)
32. Lazoglou, M., Angelides, D.C.: Development of an ontology for modeling spatial planning systems. Current Urban Studies 4(02), 241 (2016)
33. Louwsma, J., Zlatanova, S., van Lammeren, R., van Oosterom, P.: Specifying and imple-menting constraints in GIS - with examples from a geo-virtual reality system. GeoInformat-ica 10(4), 531–550 (2006)
34. Lurgi, M., Robertson, D.: Automated experimentation in ecological networks. Automated Experimentation 3(1) (2011)
35. Macke, S.: Dia diagram editor. http://dia-installer.de/ (2019)
36. Mauro, N., Di Rocco, L., Ardissono, L., Bertolotto, M., Guerrini, G.: Impact of semantic granularity on geographic information search support. In: Proc. of 2018 IEEE/WIC/ACM Int. Conf. on Web Intelligence (WI). pp. 323–328. IEEE, Santiago, Chile (2019)
37. Montenegro, N., Gomes, J., Urbano, P., Duarte, J.: An OWL2 land use ontology: LBCS.
In: International Conference on Computational Science and its Applications. pp. 185–198.
Springer (2011)
38. OGC: Geosparql vocabulary. http://schemas.opengis.net/geosparql/1.0/
geosparql\_vocab\_all.rdf(2012)
39. Open Geospatial Consortium, et al.: OpenGIS Implementation Standard for Geographic information-Simple feature access-Part 1: Common architecture (2011)
40. Palacio, D., Derungs, C., Purves, R.: Development and evaluation of a geographic informa-tion retrieval system using fine grained toponyms. Journal of Spatial Informainforma-tion Science JoSIS 11, 1–29 (2015)
41. Pilosof, S., Porter, M., Pascual, M., Kefi, S.: The mulutilayer nature of ecological networks.
Nature ecology&evolution 1, article 101 (2017)
42. Provincia di Torino: Linee guida per le reti ecologiche (in italian). http:
//www.provincia.torino.gov.it/territorio/file-storage/download/pdf/
pian_territoriale/rete_ecologica/lgsv_lgre.pdf(2014)
43. Quercia, D., Schifanella, R., Aiello, L.: The shortest path to happiness: Recommending beau-tiful, quiet, and happy routes in the city. In: Proc. of the 25th ACM Conference on Hypertext and Social Media. pp. 116–125. HT ’14, ACM, New York, NY, USA (2014)
44. SDS Consortium: Spatial decision support ontology. http://sdsportal.sdsconsortium.
org/ontology/(2017)
45. Soininen, T., Tiihonen, J., M¨annist¨o, T., Sulonen, R.: Towards a general ontology of config-uration. Ai Edam 12(4), 357–372 (1998)
46. Stumptner, M., Friedrich, G.E., Haselb¨ock, A.: Generative constraint-based configuration of large technical systems. AI EDAM 12(4), 307–320 (1998)
47. Sun, Y., Li, S.: Real-time collaborative GIS: a technological review. ISPRS Journal of Pho-togrammetry and remote sensing 115, 143–152 (2016)
48. Torta, G., Ardissono, L., Savoca, A., Voghera, A., La Riccia, L.: Representing ecological net-work specifications with semantic web techniques. In: Proc. of 9th Int. Joint Conf. on Knowl-edge Discovery, KnowlKnowl-edge Engineering and KnowlKnowl-edge Management (KEOD 2017). pp.
86–97. SCITEPRESS, Funchal, Madeira, Portugal (2017)
49. Torta, G., andM. Corona, L.A., La Riccia, L., Voghera, A.: Ontological representation of constraints for geographic reasoning. In: Proc. of 10th Int. Joint Conf. on Knowledge Dis-covery, Knowledge Engineering and Knowledge Management (KEOD 2018). pp. 136–147.
SCITEPRESS, Seville, Spain (2018)
50. Torta, G., Ardissono, L., Corona, M., La Riccia, L., Savoca, A., Voghera, A.: GeCoLan: A constraint language for reasoning about ecological networks in the semantic web. In: Fred, A., Aveiro, Davidand Dietz, J.L.G., Liu, K., Bernardino, J., Salgado, A., Filipe, J. (eds.) Knowledge Discovery, Knowledge Engineering and Knowledge Management. pp. 268–293.
Springer International Publishing, Cham (2019)
51. Ulanowicz, R.: Quantitative methods for ecological network analysis. Computational biol-ogy and chemistry 28, 321339 (2004)
52. Van Hage, W.R., Malais´e, V., Segers, R., Hollink, L., Schreiber, G.: Design and use of the simple event model (sem). Web Semantics: Science, Services and Agents on the World Wide Web 9(2), 128–136 (2011)
53. Voghera, A., La Riccia, L.: Ecological networks in urban planning: Between theoreti-cal approaches and operational measures. In: Calabr`o, F., Della Spina, L., Bevilacqua, C.
(eds.) New Metropolitan Perspectives. pp. 672–680. Springer International Publishing, Cham (2019)
54. Voghera, A., La Riccia, L.: Ecological networks in urban planning: Between theoretical ap-proaches and operational measures. In: Calabr`o, F., Della Spina, L., Bevilacqua, C. (eds.) New Metropolitan Perspectives. Local Knowledge and Innovation Dynamics Towards Ter-ritory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030, pp. 672–
680. Smart Innovation, Systemsa and Technologies, Springer (2019)
55. W3C: Representing classes as property values on the semantic web. https://www.w3.org/
TR/2005/NOTE-swbp-classes-as-values-20050405/(2017)
56. W3C: Resource description framework (RDF). https://www.w3.org/RDF/ (2017) 57. W3C: SPARQL query language for RDF. https://www.w3.org/TR/rdf-sparql-query/
(2017)
58. W3C: Web ontology language (OWL). https://www.w3.org/OWL/ (2017)