{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T23:06:50Z","timestamp":1746313610085,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030658465"},{"type":"electronic","value":"9783030658472"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-65847-2_16","type":"book-chapter","created":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T18:04:23Z","timestamp":1608573863000},"page":"173-183","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["JSON Schema Inference Approaches"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3332-3503","authenticated-orcid":false,"given":"Pavel","family":"\u010conto\u0161","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4694-6806","authenticated-orcid":false,"given":"Martin","family":"Svoboda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","unstructured":"Baazizi, M.A., Colazzo, D., Ghelli, G., Sartiani, C.: A type system for interactive JSON schema inference. In: ICALP 2019. LIPIcs, vol. 132, pp. 101:1\u2013101:13 (2019). https:\/\/doi.org\/10.4230\/LIPIcs.ICALP.2019.101","DOI":"10.4230\/LIPIcs.ICALP.2019.101"},{"issue":"4","key":"16_CR2","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1007\/s00778-018-0532-7","volume":"28","author":"M-A Baazizi","year":"2019","unstructured":"Baazizi, M.-A., Colazzo, D., Ghelli, G., Sartiani, C.: Parametric schema inference for massive JSON datasets. VLDB J. 28(4), 497\u2013521 (2019). https:\/\/doi.org\/10.1007\/s00778-018-0532-7","journal-title":"VLDB J."},{"issue":"2","key":"16_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1735886.1735890","volume":"35","author":"GJ Bex","year":"2010","unstructured":"Bex, G.J., Neven, F., Schwentick, T., Vansummeren, S.: Inference of concise regular expressions and DTDs. ACM Trans. Database Syst. 35(2), 1\u201347 (2010). https:\/\/doi.org\/10.1145\/1735886.1735890","journal-title":"ACM Trans. Database Syst."},{"key":"16_CR4","doi-asserted-by":"publisher","unstructured":"Bouhamoum, R., Kellou-Menouer, K., Lopes, S., Kedad, Z.: Scaling up schema discovery for RDF datasets. In: ICDEW 2018, pp. 84\u201389. IEEE (2018). https:\/\/doi.org\/10.1109\/ICDEW.2018.00021","DOI":"10.1109\/ICDEW.2018.00021"},{"key":"16_CR5","unstructured":"BSON: Binary JSON (2012). http:\/\/bsonspec.org\/spec.html"},{"key":"16_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1007\/978-3-642-39200-9_8","volume-title":"Web Engineering","author":"JL C\u00e1novas Izquierdo","year":"2013","unstructured":"C\u00e1novas Izquierdo, J.L., Cabot, J.: Discovering implicit schemas in JSON data. In: Daniel, F., Dolog, P., Li, Q. (eds.) ICWE 2013. LNCS, vol. 7977, pp. 68\u201383. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-39200-9_8"},{"issue":"1","key":"16_CR7","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1145\/1327452.1327492","volume":"51","author":"J Dean","year":"2008","unstructured":"Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107\u2013113 (2008). https:\/\/doi.org\/10.1145\/1327452.1327492","journal-title":"Commun. ACM"},{"key":"16_CR8","doi-asserted-by":"publisher","unstructured":"DiScala, M., Abadi, D.J.: Automatic generation of normalized relational schemas from nested key-value data. In: SIGMOD 2016, pp. 295\u2013310. ACM (2016). https:\/\/doi.org\/10.1145\/2882903.2882924","DOI":"10.1145\/2882903.2882924"},{"key":"16_CR9","unstructured":"Feliciano Morales, S.: Inferring NoSQL data schemas with model-driven engineering techniques. Ph.D. thesis, Universidad de Murcia (2017)"},{"key":"16_CR10","doi-asserted-by":"publisher","unstructured":"Frozza, A.A., dos Santos Mello, R., da Costa, F.d.S.: An approach for schema extraction of JSON and extended JSON document collections. In: IRI 2018, pp. 356\u2013363 (2018). https:\/\/doi.org\/10.1109\/IRI.2018.00060","DOI":"10.1109\/IRI.2018.00060"},{"key":"16_CR11","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.is.2018.06.004","volume":"77","author":"E Gallinucci","year":"2018","unstructured":"Gallinucci, E., Golfarelli, M., Rizzi, S., Abell\u00f3, A., Romero, O.: Interactive multidimensional modeling of linked data for exploratory OLAP. Inf. Syst. 77, 86\u2013104 (2018). https:\/\/doi.org\/10.1016\/j.is.2018.06.004","journal-title":"Inf. Syst."},{"key":"16_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1007\/978-3-030-33223-5_36","volume-title":"Conceptual Modeling","author":"I Holubov\u00e1","year":"2019","unstructured":"Holubov\u00e1, I., Svoboda, M., Lu, J.: Unified management of multi-model data. In: Laender, A.H.F., Pernici, B., Lim, E.-P., de Oliveira, J.P.M. (eds.) ER 2019. LNCS, vol. 11788, pp. 439\u2013447. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-33223-5_36"},{"key":"16_CR13","unstructured":"JavaScript Object Notation (JSON) (2013). http:\/\/www.json.org\/"},{"key":"16_CR14","unstructured":"JSON Schema (2019). https:\/\/json-schema.org\/"},{"key":"16_CR15","unstructured":"Klettke, M., St\u00f6rl, U., Scherzinger, S.: Schema extraction and structural outlier detection for JSON-based NoSQL data stores. In: Datenbanksysteme f\u00fcr Business, Technologie und Web (BTW 2015), pp. 425\u2013444 (2015)"},{"issue":"4","key":"16_CR16","doi-asserted-by":"publisher","first-page":"577","DOI":"10.15388\/Informatica.2013.05","volume":"24","author":"I Ml\u00fdnkov\u00e1","year":"2013","unstructured":"Ml\u00fdnkov\u00e1, I., Ne\u010dask\u00fd, M.: Heuristic methods for inference of XML schemas: lessons learned and open issues. Informatica 24(4), 577\u2013602 (2013)","journal-title":"Informatica"},{"key":"16_CR17","doi-asserted-by":"publisher","unstructured":"Pezoa, F., Reutter, J.L., Suarez, F., Ugarte, M., Vrgo\u010d, D.: Foundations of JSON schema. In: Proceedings of the 25th International Conference on World Wide Web, pp. 263\u2013273 (2016). https:\/\/doi.org\/10.1145\/2872427.2883029","DOI":"10.1145\/2872427.2883029"},{"key":"16_CR18","unstructured":"Rumbaugh, J., Jacobson, I., Booch, G.: The Unified Modeling Language Reference Manual. Pearson Higher Education (2004)"},{"key":"16_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1007\/978-3-319-25264-3_35","volume-title":"Conceptual Modeling","author":"D Sevilla Ruiz","year":"2015","unstructured":"Sevilla Ruiz, D., Morales, S.F., Garc\u00eda Molina, J.: Inferring versioned schemas from NoSQL databases and its applications. In: Johannesson, P., Lee, M.L., Liddle, S.W., Opdahl, A.L., L\u00f3pez, \u00d3.P. (eds.) ER 2015. LNCS, vol. 9381, pp. 467\u2013480. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-25264-3_35"},{"issue":"9","key":"16_CR20","doi-asserted-by":"publisher","first-page":"922","DOI":"10.14778\/2777598.2777601","volume":"8","author":"L Wang","year":"2015","unstructured":"Wang, L.: Schema management for document stores. Proc. VLDB Endow. 8(9), 922\u2013933 (2015). https:\/\/doi.org\/10.14778\/2777598.2777601","journal-title":"Proc. VLDB Endow."},{"key":"16_CR21","unstructured":"Extensible Markup Language (XML) 1.0 (Fifth Edition) (2013). https:\/\/www.w3.org\/TR\/REC-xml\/"}],"container-title":["Lecture Notes in Computer Science","Advances in Conceptual Modeling"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-65847-2_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,23]],"date-time":"2020-12-23T00:07:14Z","timestamp":1608682034000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-65847-2_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030658465","9783030658472"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-65847-2_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"22 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ER","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Conceptual Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"39","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"er2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/er2020.big.tuwien.ac.at\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"143","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}