Data Quality in Object-Centric Event Data: IssuesClassification and Evaluation

Data Quality in Object-Centric Event Data: IssuesClassification and Evaluation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Data Quality in Object-Centric Event Data: IssuesClassification and Evaluation Martin Kabierski, Maike Basmer, Agnieszka Patecka, Kristina Sahling, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6941537/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Process analysis is concerned with analyzing recorded process executions to validate, monitor, or improve the underlying processes according to business goals. In this context, the paradigm of object-centric event data (OCED) has recently emerged, which relates activity executions to multiple objects instead of a single, pre-determined case. Since OCED can integrate various process perspectives simultaneously, it represents real-life activities more accurately than traditional event logs. Being the input of Object-Centric Process Mining (OCPM), the quality of the data recorded in OCED logs directly influences the results of the process analysis.To ensure reliable outcomes, it is imperative to assess potential quality problems manifesting in the data. While frameworks for such an assessment are available for classic event data, equivalent approaches for assessing quality issues in OCED do not yet exist. This paper provides an analysis and classification of data quality issues in OCED, and compares them to the issues in traditional event data. The classification is both evaluated in terms of its applicability to real-world event logs and through semi-structured interviews with practitioners. Our findings help researchers and practitioners as a road-map for detecting or avoiding data quality problems that hinder the effectiveness of process mining initiatives. event log data quality object-centric event data process mining Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 25 Oct, 2025 Reviews received at journal 17 Oct, 2025 Reviews received at journal 25 Jul, 2025 Reviewers agreed at journal 09 Jul, 2025 Reviewers agreed at journal 27 Jun, 2025 Reviewers invited by journal 26 Jun, 2025 Editor assigned by journal 23 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 20 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6941537","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":479822446,"identity":"25cb07f4-11f6-4469-a8f1-76afd6e2b282","order_by":0,"name":"Martin Kabierski","email":"data:image/png;base64,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","orcid":"","institution":"University of Vienna","correspondingAuthor":true,"prefix":"","firstName":"Martin","middleName":"","lastName":"Kabierski","suffix":""},{"id":479822447,"identity":"50529241-5022-4456-88c5-4a53a8a73ca0","order_by":1,"name":"Maike Basmer","email":"","orcid":"","institution":"Humboldt-Universität zu Berlin","correspondingAuthor":false,"prefix":"","firstName":"Maike","middleName":"","lastName":"Basmer","suffix":""},{"id":479822448,"identity":"50dcfa96-3881-4ae8-a655-93f937246d29","order_by":2,"name":"Agnieszka Patecka","email":"","orcid":"","institution":"European University Viadrina","correspondingAuthor":false,"prefix":"","firstName":"Agnieszka","middleName":"","lastName":"Patecka","suffix":""},{"id":479822449,"identity":"bfddf414-6b08-4b5f-9289-354a4b56be56","order_by":3,"name":"Kristina Sahling","email":"","orcid":"","institution":"Weizenbaum Institute for the Networked Society","correspondingAuthor":false,"prefix":"","firstName":"Kristina","middleName":"","lastName":"Sahling","suffix":""},{"id":479822450,"identity":"27f9b1b7-e83d-41db-997e-3390efbc5062","order_by":4,"name":"Saimir Bala","email":"","orcid":"","institution":"Humboldt-Universität zu Berlin","correspondingAuthor":false,"prefix":"","firstName":"Saimir","middleName":"","lastName":"Bala","suffix":""}],"badges":[],"createdAt":"2025-06-20 21:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6941537/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6941537/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85926993,"identity":"2d65cf1a-1680-4792-969d-b1c0477176ba","added_by":"auto","created_at":"2025-07-03 08:47:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":631831,"visible":true,"origin":"","legend":"","description":"","filename":"Archive.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6941537/v1_covered_842f8890-817c-4068-936b-ace6a76b76bf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Data Quality in Object-Centric Event Data: IssuesClassification and Evaluation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"process-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Process Science](https://link.springer.com/journal/44311)","snPcode":"44311","submissionUrl":"https://submission.springernature.com/new-submission/44311","title":"Process Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"event log, data quality, object-centric event data, process mining","lastPublishedDoi":"10.21203/rs.3.rs-6941537/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6941537/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Process analysis is concerned with analyzing recorded process executions to validate, monitor, or improve the underlying processes according to business goals. In this context, the paradigm of object-centric event data (OCED) has recently emerged, which relates activity executions to multiple objects instead of a single, pre-determined case. Since OCED can integrate various process perspectives simultaneously, it represents real-life activities more accurately than traditional event logs. Being the input of Object-Centric Process Mining (OCPM), the quality of the data recorded in OCED logs directly influences the results of the process analysis.To ensure reliable outcomes, it is imperative to assess potential quality problems manifesting in the data. While frameworks for such an assessment are available for classic event data, equivalent approaches for assessing quality issues in OCED do not yet exist. This paper provides an analysis and classification of data quality issues in OCED, and compares them to the issues in traditional event data. The classification is both evaluated in terms of its applicability to real-world event logs and through semi-structured interviews with practitioners. Our findings help researchers and practitioners as a road-map for detecting or avoiding data quality problems that hinder the effectiveness of process mining initiatives.","manuscriptTitle":"Data Quality in Object-Centric Event Data: IssuesClassification and Evaluation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-03 08:39:11","doi":"10.21203/rs.3.rs-6941537/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-25T10:28:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T16:17:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-25T12:38:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"98358022236206348196431729184069282958","date":"2025-07-09T11:06:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255366229368323033645269080380871541570","date":"2025-06-27T11:08:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-26T08:38:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-24T01:40:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-24T01:38:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Process Science","date":"2025-06-20T21:06:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"process-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Process Science](https://link.springer.com/journal/44311)","snPcode":"44311","submissionUrl":"https://submission.springernature.com/new-submission/44311","title":"Process Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"992fd517-2bd1-48e3-b225-1a3ebb1a2108","owner":[],"postedDate":"July 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T13:54:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-03 08:39:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6941537","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6941537","identity":"rs-6941537","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}