{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T14:17:55Z","timestamp":1762957075673,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031278143"},{"type":"electronic","value":"9783031278150"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,3,26]],"date-time":"2023-03-26T00:00:00Z","timestamp":1679788800000},"content-version":"vor","delay-in-days":84,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Process discovery is a family of techniques that helps to comprehend processes from their data footprints. Yet, as processes change over time so should their corresponding models, and failure to do so will lead to models that under- or over-approximate behaviour. We present a discovery algorithm that extracts declarative processes as Dynamic Condition Response (DCR) graphs from event streams. Streams are monitored to generate temporal representations of the process, later processed to create declarative models. We validated the technique by identifying drifts in a publicly available dataset of event streams. The metrics extend the Jaccard similarity measure to account for process change in a declarative setting. The technique and the data used for testing are available online.<\/jats:p>","DOI":"10.1007\/978-3-031-27815-0_12","type":"book-chapter","created":{"date-parts":[[2023,3,25]],"date-time":"2023-03-25T10:03:04Z","timestamp":1679738584000},"page":"158-170","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Uncovering Change: A Streaming Approach for\u00a0Declarative Processes"],"prefix":"10.1007","author":[{"given":"Andrea","family":"Burattin","sequence":"first","affiliation":[]},{"given":"Hugo A.","family":"L\u00f3pez","sequence":"additional","affiliation":[]},{"given":"Lasse","family":"Starklit","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,26]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-49851-4","volume-title":"Process Mining","author":"W van der Aalst","year":"2016","unstructured":"van der Aalst, W.: Process Mining. Springer, Berlin Heidelberg (2016)"},{"key":"12_CR2","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/978-3-642-28108-2_13","volume-title":"Business Process Management Workshops","author":"F Aiolli","year":"2012","unstructured":"Aiolli, F., Burattin, A., Sperduti, A.: A business process metric based on the alpha algorithm relations. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 141\u2013146. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-28108-2_13"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Akidau, T., et al.: Watermarks in stream processing systems: semantics and comparative analysis of apache Fink and google cloud dataflow. VLDB (2021)","DOI":"10.14778\/3476311.3476389"},{"key":"12_CR4","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s10009-021-00616-0","volume":"24","author":"CO Back","year":"2021","unstructured":"Back, C.O., Slaats, T., Hildebrandt, T.T., Marquard, M.: DisCoveR: accurate and efficient discovery of declarative process models. Int. J. Softw. Tools Technol. Transfer 24, 563\u2013587 (2021). https:\/\/doi.org\/10.1007\/s10009-021-00616-0","journal-title":"Int. J. Softw. Tools Technol. Transfer"},{"key":"12_CR5","doi-asserted-by":"crossref","unstructured":"Burattin, A.: Streaming process discovery and conformance checking. In: Encyclopedia of Big Data Technologies. Springer, Cham (2019)","DOI":"10.1007\/978-3-319-77525-8_103"},{"key":"12_CR6","doi-asserted-by":"crossref","unstructured":"Burattin, A.: Streaming process mining with beamline. In: ICPM Demos (2022)","DOI":"10.1007\/978-3-031-08848-3_11"},{"issue":"6","key":"12_CR7","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1109\/TSC.2015.2459703","volume":"8","author":"A Burattin","year":"2015","unstructured":"Burattin, A., Cimitile, M., Maggi, F.M., Sperduti, A.: Online discovery of declarative process models from event streams. IEEE Trans. Serv. Comput. 8(6), 833\u2013846 (2015)","journal-title":"IEEE Trans. Serv. Comput."},{"key":"12_CR8","doi-asserted-by":"publisher","unstructured":"Burattin, A., L\u00f3pez, H.A., Starklit, L.: A monitoring and discovery approach for declarative processes based on streams (2022). https:\/\/doi.org\/10.48550\/arXiv.2208.05364","DOI":"10.48550\/arXiv.2208.05364"},{"key":"12_CR9","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.eswa.2016.08.040","volume":"65","author":"A Burattin","year":"2016","unstructured":"Burattin, A., Maggi, F.M., Sperduti, A.: Conformance checking based on multi-perspective declarative process models. Expert Syst. Appl. 65, 194\u2013211 (2016)","journal-title":"Expert Syst. Appl."},{"key":"12_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-99414-7","volume-title":"Conformance Checking","author":"J Carmona","year":"2018","unstructured":"Carmona, J., van Dongen, B., Solti, A., Weidlich, M.: Conformance Checking. Springer, Cham (2018)"},{"key":"12_CR11","doi-asserted-by":"publisher","first-page":"2473","DOI":"10.1109\/TSC.2020.3004532","volume":"15","author":"P Ceravolo","year":"2020","unstructured":"Ceravolo, P., Tavares, G.M., Junior, S.B., Damiani, E.: Evaluation goals for online process mining: a concept drift perspective. IEEE Trans. Serv. Comput. 15, 2473\u20132489 (2020)","journal-title":"IEEE Trans. Serv. Comput."},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"De Giacomo, G., De Masellis, R., Montali, M.: Reasoning on LTL on finite traces: insensitivity to infiniteness. In: AAAI Conference on Artificial Intelligence (2014)","DOI":"10.1609\/aaai.v28i1.8872"},{"issue":"6","key":"12_CR13","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1007\/s00236-017-0303-8","volume":"55","author":"S Debois","year":"2018","unstructured":"Debois, S., Hildebrandt, T.T., Slaats, T.: Replication, refinement & reachability: complexity in dynamic condition-response graphs. Acta Informatica 55(6), 489\u2013520 (2018). https:\/\/doi.org\/10.1007\/s00236-017-0303-8","journal-title":"Acta Informatica"},{"key":"12_CR14","doi-asserted-by":"crossref","unstructured":"Hildebrandt, T., Mukkamala, R.R.: Declarative event-based workflow as distributed dynamic condition response graphs. In: PLACES, vol. 69 (2010)","DOI":"10.4204\/EPTCS.69.5"},{"issue":"5\u20137","key":"12_CR15","first-page":"164","volume":"82","author":"TT Hildebrandt","year":"2013","unstructured":"Hildebrandt, T.T., Mukkamala, R.R., Slaats, T., Zanitti, F.: Contracts for cross-organizational workflows as timed dynamic condition response graphs. JLAMP 82(5\u20137), 164\u2013185 (2013)","journal-title":"JLAMP"},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Hunkeler, U., Truong, H.L., Stanford-Clark, A.: MQTT-S-a publish\/subscribe protocol for wireless sensor networks. In: Proceedings of COMSWARE. IEEE (2008)","DOI":"10.1109\/COMSWA.2008.4554519"},{"issue":"2","key":"12_CR17","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1111\/j.1469-8137.1912.tb05611.x","volume":"11","author":"P Jaccard","year":"1912","unstructured":"Jaccard, P.: The distribution of the flora of the alpine zone. New Phytol. 11(2), 37\u201350 (1912)","journal-title":"New Phytol."},{"key":"12_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1007\/978-3-030-45234-6_19","volume-title":"Fundamental Approaches to Software Engineering","author":"HA L\u00f3pez","year":"2020","unstructured":"L\u00f3pez, H.A., Debois, S., Slaats, T., Hildebrandt, T.T.: Business process compliance using reference models of law. In: FASE 2020. LNCS, vol. 12076, pp. 378\u2013399. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-45234-6_19"},{"key":"12_CR19","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/978-3-030-79108-7_13","volume-title":"Intelligent Information Systems","author":"HA L\u00f3pez","year":"2021","unstructured":"L\u00f3pez, H.A., Str\u00f8msted, R., Niyodusenga, J.-M., Marquard, M.: Declarative process discovery: linking process and textual views. In: Nurcan, S., Korthaus, A. (eds.) CAiSE 2021. LNBIP, vol. 424, pp. 109\u2013117. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-79108-7_13"},{"key":"12_CR20","doi-asserted-by":"crossref","unstructured":"Navarin, N., Cambiaso, M., Burattin, A., Maggi, F.M., Oneto, L., Sperduti, A.: Towards online discovery of data-aware declarative process models from event streams. In: IJCNN (2020)","DOI":"10.1109\/IJCNN48605.2020.9207500"},{"key":"12_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1007\/978-3-030-21290-2_37","volume-title":"Advanced Information Systems Engineering","author":"V Nekrasaite","year":"2019","unstructured":"Nekrasaite, V., Parli, A.T., Back, C.O., Slaats, T.: Discovering responsibilities with dynamic condition response graphs. In: Giorgini, P., Weber, B. (eds.) CAiSE 2019. LNCS, vol. 11483, pp. 595\u2013610. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-21290-2_37"},{"key":"12_CR22","unstructured":"Norgaard, L.H., et al.: Declarative process models in government centric case and document management. In: BPM (Industry Track). CEUR, vol. 1985, pp. 38\u201351. CEUR-WS.org (2017)"},{"key":"12_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/11837862_18","volume-title":"Business Process Management Workshops","author":"M Pesic","year":"2006","unstructured":"Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM 2006. LNCS, vol. 4103, pp. 169\u2013180. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11837862_18"},{"key":"12_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/978-3-030-85469-0_6","volume-title":"Business Process Management","author":"T Slaats","year":"2021","unstructured":"Slaats, T., Debois, S., Back, C.O.: Weighing the pros and cons: process discovery with negative examples. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds.) BPM 2021. LNCS, vol. 12875, pp. 47\u201364. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-85469-0_6"},{"key":"12_CR25","unstructured":"Starklit, L.: Online Discovery and Comparison of DCR models from Event Streams using Beamline. Master\u2019s thesis, DTU (2021)"},{"key":"12_CR26","unstructured":"Str\u00f8msted, R., L\u00f3pez, H.A., Debois, S., Marquard, M.: Dynamic evaluation forms using declarative modeling. In: BPM (Demos\/Industry), pp. 172\u2013179 (2018)"},{"key":"12_CR27","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.procs.2019.12.189","volume":"164","author":"WM van der Aalst","year":"2019","unstructured":"van der Aalst, W.M.: A practitioner\u2019s guide to process mining: limitations of the directly-follows graph. Procedia Comput. Sci. 164, 321\u2013328 (2019)","journal-title":"Procedia Comput. Sci."},{"issue":"3","key":"12_CR28","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.datak.2008.05.001","volume":"66","author":"B Weber","year":"2008","unstructured":"Weber, B., Reichert, M., Rinderle-Ma, S.: Change patterns and change support features-enhancing flexibility in process-aware information systems. Data Knowl. Eng. 66(3), 438\u2013466 (2008)","journal-title":"Data Knowl. Eng."},{"key":"12_CR29","unstructured":"van Zelst, S.J.: Process mining with streaming data. Ph.D. thesis, Technische Universiteit Eindhoven (2019)"}],"container-title":["Lecture Notes in Business Information Processing","Process Mining Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-27815-0_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T13:06:22Z","timestamp":1693832782000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-27815-0_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031278143","9783031278150"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-27815-0_12","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"type":"print","value":"1865-1348"},{"type":"electronic","value":"1865-1356"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"26 March 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Process Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bozen-Bolzano","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpm2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpmconference.org\/2022\/","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":"89","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":"42","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":"0","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":"47% - 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":"2.93","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":"2","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}