{"title":"Process-related user interaction logs: State of the art, reference model, and object-centric implementation","authors":"Luka Abb, Jana-Rebecca Rehse","doi":"10.1016/j.is.2024.102386","DOIUrl":null,"url":null,"abstract":"<div><p>User interaction (UI) logs are high-resolution event logs that record low-level activities performed by a user during the execution of a task in an information system. Each event in such a log represents an interaction between the user and the interface, such as clicking a button, ticking a checkbox, or typing into a text field. UI logs are used in many different application contexts for purposes such as usability analysis, task mining, or robotic process automation (RPA). However, UI logs suffer from a lack of standardization. Each research study and processing tool relies on a different conceptualization and implementation of the elements and attributes of user interactions. This exacerbates or even prohibits the integration of UI logs from different sources or the combination of UI data collection tools with downstream analytics or automation solutions. In this paper, our objective is to address this issue and facilitate the exchange and analysis of UI logs in research and practice. Therefore, we first review process-related UI logs in scientific publications and industry tools to determine commonalities and differences between them. Based on our findings, we propose a universally applicable reference data model for process-related UI logs, which includes all core attributes but remains flexible regarding the scope, level of abstraction, and case notion. Finally, we provide exemplary implementations of the reference model in XES and OCED.</p></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"124 ","pages":"Article 102386"},"PeriodicalIF":3.0000,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0306437924000449/pdfft?md5=99fcafdb33deb5f863a548bbb4740fc9&pid=1-s2.0-S0306437924000449-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306437924000449","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
User interaction (UI) logs are high-resolution event logs that record low-level activities performed by a user during the execution of a task in an information system. Each event in such a log represents an interaction between the user and the interface, such as clicking a button, ticking a checkbox, or typing into a text field. UI logs are used in many different application contexts for purposes such as usability analysis, task mining, or robotic process automation (RPA). However, UI logs suffer from a lack of standardization. Each research study and processing tool relies on a different conceptualization and implementation of the elements and attributes of user interactions. This exacerbates or even prohibits the integration of UI logs from different sources or the combination of UI data collection tools with downstream analytics or automation solutions. In this paper, our objective is to address this issue and facilitate the exchange and analysis of UI logs in research and practice. Therefore, we first review process-related UI logs in scientific publications and industry tools to determine commonalities and differences between them. Based on our findings, we propose a universally applicable reference data model for process-related UI logs, which includes all core attributes but remains flexible regarding the scope, level of abstraction, and case notion. Finally, we provide exemplary implementations of the reference model in XES and OCED.
期刊介绍:
Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems.
Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.