{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T10:07:44Z","timestamp":1783850864272,"version":"3.55.0"},"reference-count":52,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T00:00:00Z","timestamp":1663027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The possibility offered by the current technology to collect and store data sets regarding public places located on the Earth globe is posing new challenges, as far as the integration of these data sets is concerned. Analysts usually need to perform such an integration from scratch, without performing complex and long preprocessing or data-cleaning tasks, as well as without performing training activities that require tedious and long labeling of data; furthermore, analysts now have to deal with the popular JSON format and with data sets stored within JSON document stores. This paper demonstrates that a methodology based on soft integration (i.e., data integration performed through soft computing and fuzzy sets) can now be effectively applied from scratch, through the J-CO Framework, which is a stand-alone tool devised to process JSON data sets stored within JSON document stores, possibly by performing soft querying on data sets. Specifically, the paper provides the following contributions: (1) It presents a soft-computing technique for integrating data sets describing public places, without any preliminary pre-processing, cleaning and training, which can be applied from scratch; (2) it presents current capabilities for soft integration of JSON data sets, provided by the J-CO Framework; (3) it demonstrates the effectiveness of the soft integration technique; (4) it shows how a stand-alone tool able to support soft computing (as the J-CO Framework) can be effective and efficient in performing data-integration tasks from scratch.<\/jats:p>","DOI":"10.3390\/ijgi11090484","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T21:06:52Z","timestamp":1663103212000},"page":"484","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Soft Integration of Geo-Tagged Data Sets in J-CO-QL+"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9050-7873","authenticated-orcid":false,"given":"Paolo","family":"Fosci","sequence":"first","affiliation":[{"name":"Department of Management, Information and Production Engineering, University of Bergamo, Viale Marconi 5, 24044 Dalmine, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9228-560X","authenticated-orcid":false,"given":"Giuseppe","family":"Psaila","sequence":"additional","affiliation":[{"name":"Department of Management, Information and Production Engineering, University of Bergamo, Viale Marconi 5, 24044 Dalmine, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,13]]},"reference":[{"key":"ref_1","unstructured":"Bray, T. (2022, September 01). The Javascript Object Notation (JSON) Data Interchange Format. Available online: https:\/\/www.rfc-editor.org\/rfc\/rfc7159.txt."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bordogna, G., Capelli, S., and Psaila, G. (2017, January 10\u201311). A big geo data query framework to correlate open data with social network geotagged posts. Proceedings of the Annual International Conference on Geographic Information Science, Wageningen, The Netherlands.","DOI":"10.1007\/978-3-319-56759-4_11"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bordogna, G., Ciriello, D.E., and Psaila, G. (2017, January 23\u201326). A flexible framework to cross-analyze heterogeneous multi-source geo-referenced information: The J-CO-QL proposal and its implementation. Proceedings of the International Conference on Web Intelligence, Leipzig, Germany.","DOI":"10.1145\/3106426.3106537"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1080\/10095020.2017.1374703","article-title":"A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information: The case study of volunteered personal traces analysis against transport network data","volume":"21","author":"Bordogna","year":"2018","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Psaila, G., and Fosci, P. (2021). J-CO: A Platform-Independent Framework for Managing Geo-Referenced JSON Data Sets. Electronics, 10.","DOI":"10.3390\/electronics10050621"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Psaila, G., and Toccu, M. (2019). A Fuzzy Technique for On-Line Aggregation of POIs from Social Media: Definition and Comparison with Off-Line Random-Forest Classifiers. Information, 10.","DOI":"10.3390\/info10120388"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Fosci, P., and Psaila, G. (2021). Towards flexible retrieval, integration and analysis of json data sets through fuzzy sets: A case study. Information, 12.","DOI":"10.3390\/info12070258"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Fosci, P., and Psaila, G. (2021, January 19\u201324). J-CO, a Framework for Fuzzy Querying Collections of JSON Documents. Proceedings of the International Conference on Flexible Query Answering Systems, Bratislava, Slovakia.","DOI":"10.1007\/978-3-030-86967-0_11"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Psaila, G., and Marrara, S. (2019, January 7\u20139). A First Step Towards a Fuzzy Framework for Analyzing Collections of JSON Documents. Proceedings of the IADIS AC 2019, Cagliari, Italy.","DOI":"10.33965\/ac2019_201912L003"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1002\/asi.4630300621","article-title":"Information Retrieval, 2nd ed. C.J. Van Rijsbergen. London: Butterworths; 1979: 208 pp. Price: $32.50","volume":"30","author":"Blair","year":"1979","journal-title":"J. Am. Soc. Inf. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4895977","DOI":"10.1109\/91.366566","article-title":"SQLf: A relational database language for fuzzy querying","volume":"3","author":"Bosc","year":"1995","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bosc, P., and Pivert, O. (2000). SQLf query functionality on top of a regular relational database management system. Knowledge Management in Fuzzy Databases, Springer.","DOI":"10.1007\/978-3-7908-1865-9_11"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Galindo, J., Medina, J.M., Pons, O., and Cubero, J.C. (1998, January 13\u201315). A server for fuzzy SQL queries. Proceedings of the International Conference on Flexible Query Answering Systems, Roskilde, Denmark.","DOI":"10.1007\/BFb0055999"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zadrozny, S., and Kacprzyk, J. (1996, January 17\u201319). Fquery for access: Towards human consistent querying user interface. Proceedings of the 1996 ACM Symposium on Applied Computing, Philadelphia, PA, USA.","DOI":"10.1145\/331119.331446"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Kacprzyk, J., and Zadro\u017cny, S. (1995). FQUERY for Access: Fuzzy querying for a Windows-based DBMS. Fuzziness in Database Management Systems, Springer.","DOI":"10.1007\/978-3-7908-1897-0_18"},{"key":"ref_16","unstructured":"Bordogna, G., and Psaila, G. (2008, January 22\u201327). Modeling soft conditions with unequal importance in fuzzy databases based on the vector p-norm. Proceedings of the IPMU COnference, Malaga, Spain."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Bordogna, G., and Psaila, G. (2008). Customizable flexible querying in classical relational databases. Handbook of Research on Fuzzy Information Processing in Databases, IGI Global.","DOI":"10.4018\/978-1-59904-853-6.ch008"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1142\/S0218488509006017","article-title":"Soft Aggregation in Flexible Databases Querying based on the Vector p-norm","volume":"17","author":"Bordogna","year":"2009","journal-title":"Int. J. Uncertain. Fuzziness Knowl.-Based Syst."},{"key":"ref_19","unstructured":"Kacprzyk, J., and Zadrozny, S. (2001, January 25\u201328). SQLf and FQUERY for Access. Proceedings of the Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), Vancouver, BC, Canada."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Urrutia, A., Tineo, L., and Gonzalez, C. (2008). FSQL and SQLf: Towards a standard in fuzzy databases. Handbook of Research on Fuzzy Information Processing in Databases, IGI Global.","DOI":"10.4018\/978-1-59904-853-6.ch011"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Galindo, J. (2008). Handbook of Research on Fuzzy Information Processing in Databases, IGI Global.","DOI":"10.4018\/978-1-59904-853-6"},{"key":"ref_22","unstructured":"Han, J., Haihong, E., Le, G., and Du, J. (2011, January 26\u201328). Survey on NoSQL database. Proceedings of the 2011 6th International Conference on Pervasive Computing and Applications, Port Elizabeth, South Africa."},{"key":"ref_23","unstructured":"Chodorow, K. (2013). MongoDB: The Definitive Guide: Powerful and Scalable Data Storage, O\u2019Reilly Media, Inc."},{"key":"ref_24","unstructured":"Anderson, J.C., Lehnardt, J., and Slater, N. (2010). CouchDB: The Definitive Guide: Time to Relax, O\u2019Reilly Media, Inc."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Garcia Bringas, P., Pastor, I., and Psaila, G. (2019, January 2\u20135). Can BlockChain technology provide information systems with trusted database? The case of HyperLedger Fabric. Proceedings of the International Conference on Flexible Query Answering Systems, Amantea, Italy.","DOI":"10.1007\/978-3-030-27629-4_25"},{"key":"ref_26","unstructured":"Abir, B.K., and Amel, G.T. (2015, January 24\u201329). Towards fuzzy querying of NoSQL document-oriented databases. Proceedings of the DBKDA 2015: The Seventh International Conference on Advances in Databases, Knowledge, and Data Applications, Rome, Italy."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.eswa.2018.06.051","article-title":"Fuzzy queries of social networks with FSA-SPARQL","volume":"113","author":"Moreno","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_28","unstructured":"Manola, F., Miller, E., and McBride, B. (2022, September 01). RDF Primer. W3C Recommendation (2004). Available online: http:\/\/www.w3.org\/TR\/rdf-primer."},{"key":"ref_29","unstructured":"Cheng, J., Ma, Z.M., and Yan, L. (September, January 30). f-SPARQL: A flexible extension of SPARQL. Proceedings of the International Conference on Database and Expert Systems Applications, Bilbao, Spain."},{"key":"ref_30","first-page":"16","article-title":"Semantics and complexity of SPARQL","volume":"34","author":"Arenas","year":"2009","journal-title":"ACM Trans. Database Syst. (TODS)"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1177\/0165551515590097","article-title":"An Accurate Toponym-Matching Measure Based On Approximate String Matching","volume":"42","author":"Kilinc","year":"2016","journal-title":"J. Inf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1080\/17538947.2017.1371253","article-title":"Learning to combine multiple string similarity metrics for effective toponym matching","volume":"11","author":"Santos","year":"2018","journal-title":"Int. J. Digit. Earth"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1080\/13658816.2017.1390119","article-title":"Toponym matching through deep neural networks","volume":"32","author":"Rui","year":"2018","journal-title":"Int. J. Geogr. Inf."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Li, L., Xing, X., Xia, H., and Huang, X. (2016). Entropy-Weighted Instance Matching between Different Sourcing Points of Interest. Entropy, 18.","DOI":"10.3390\/e18020045"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1080\/17538947.2017.1359688","article-title":"A Holistic Approach to Aligning Geospatial Data with Multidimensional Similarity Measuring","volume":"11","author":"Yu","year":"2018","journal-title":"Int. J. Digit. Earth"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/0020-0255(75)90036-5","article-title":"The concept of a linguistic variable and its application to approximate reasoning\u2014I","volume":"8","author":"Zadeh","year":"1975","journal-title":"Inf. Sci."},{"key":"ref_37","unstructured":"Psaila, G., and Fosci, P. (2018, January 21\u201323). Toward an Anayist-Oriented Polystore Framework for Processing JSON Geo-Data. Proceedings of the International Conferences on WWW\/Internet, ICWI 2018 and Applied Computing 2018, Budapest, Hungary."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Fosci, P., and Psaila, G. (2021, January 22\u201324). Powering Soft Querying in J-CO-QL with JavaScript Functions. Proceedings of the International Workshop on Soft Computing Models in Industrial and Environmental Applications, Bilbao, Spain.","DOI":"10.1007\/978-3-030-87869-6_20"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1145\/2601097.2601175","article-title":"Earth mover\u2019s distances on discrete surfaces","volume":"33","author":"Solomon","year":"2014","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"ref_40","unstructured":"Jaro, M.A. (1980). UNIMATCH, a Record Linkage System: Users Manual, Bureau of the Census."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1080\/01621459.1989.10478785","article-title":"Advances in record-linkage methodology as applied to matching the 1985 census of Tampa, Florida","volume":"84","author":"Jaro","year":"1989","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_42","unstructured":"Winkler, W.E. (1990). String Comparator Metrics and Enhanced Decision Rules in the Fellegi-Sunter Model of Record Linkage. Proceedings of the Section on Survey Research Methods, American Statistical Association."},{"key":"ref_43","unstructured":"Winkler, W.E. (1999). The State of Record Linkage and Current Research Problems."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S0165-0114(86)80034-3","article-title":"Intuitionistic fuzzy sets","volume":"20","author":"Atanassov","year":"1986","journal-title":"Fuzzy Sets Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/S0165-0114(98)00235-8","article-title":"An application of intuitionistic fuzzy sets in medical diagnosis","volume":"117","author":"De","year":"2001","journal-title":"Fuzzy Sets Syst."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/S0165-0114(00)00079-8","article-title":"Operations on type-2 fuzzy sets","volume":"122","author":"Karnik","year":"2001","journal-title":"Fuzzy Sets Syst."},{"key":"ref_47","first-page":"20","article-title":"Type-2 fuzzy sets and systems: An overview","volume":"2","author":"Mendel","year":"2007","journal-title":"IEEE Comput. Intell. Mag."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/91.995115","article-title":"Type-2 fuzzy sets made simple","volume":"10","author":"Mendel","year":"2002","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Butler, H., Daly, M., Doyle, A., Gillies, S., Hagen, S., and Schaub, T. (2016). The GeoJSON Format, Internet Engineering Task Force (IETF).","DOI":"10.17487\/RFC7946"},{"key":"ref_50","unstructured":"Fosci, P., Marrara, S., and Psaila, G. (2020, January 3\u20135). Soft Querying GeoJSON Documents within the J-CO Framework. Proceedings of the 16th International Conference on Web Information Systems and Technologies (WEBIST 2020), On-line."},{"key":"ref_51","first-page":"6294872","article-title":"The Urban Nexus Approach for Analyzing Mobility in the Smart City: Towards the Identification of City Users Networking","volume":"2018","author":"Burini","year":"2018","journal-title":"Mob. Inf. Syst."},{"key":"ref_52","first-page":"246","article-title":"An interoperable open data framework for discovering popular tours based on geo-tagged tweets","volume":"10","author":"Bordogna","year":"2017","journal-title":"Int. J. Intell. Inf. Database Syst."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/9\/484\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:30:36Z","timestamp":1760142636000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/9\/484"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,13]]},"references-count":52,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["ijgi11090484"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11090484","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,13]]}}}