Towards a unified vision of business process and organizational data

被引:7
|
作者
Delgado, Andrea [1 ]
Calegari, Daniel [1 ]
机构
[1] Univ Republica, Fac Ingn, Inst Computac, Montevideo 11300, Uruguay
关键词
Business processes; process mining; data mining; process and organizational data; organizational improvement; business intelligence; model-driven; FRAMEWORK; EXECUTION;
D O I
10.1109/CLEI52000.2020.00020
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Business processes are usually enacted within a complex technological environment. Business processes data (e.g., cases, activity instances, variables, resources, etc.) is usually implicit in information systems and coupled with organizational data (e.g., clients, orders, payments, etc.). Even if processes are managed by a Business Process Management System, the link between both kinds of data is not easy to discover. In this context, a compartmentalized vision of process data on the one hand, and organizational data on the other, is not adequate to provide the organization with the evidence-based business intelligence necessary to improve their daily operation. In this paper, we deal with the integration of business process and organizational data as a basis for providing organizations with elements to allow a complete evaluation of the business process execution. We provide an analysis of scenarios for data integration and data matching problems, and we propose a model-driven approach for providing a unified view capturing all the pieces of data consistently for applying both process mining and data mining techniques.
引用
收藏
页码:108 / 117
页数:10
相关论文
共 50 条
  • [1] Integrated Process Data and Organizational Data Analysis for Business Process Improvement
    Artus, Alexis
    Borges, Andres
    Calegari, Daniel
    Delgado, Andrea
    BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY (DAWAK 2021), 2021, 12925 : 207 - 215
  • [2] Towards Intelligent Supply Chains: A Unified Framework for Business Process Design
    Siurdyban, Artur
    Moller, Charles
    INTERNATIONAL JOURNAL OF INFORMATION SYSTEMS AND SUPPLY CHAIN MANAGEMENT, 2012, 5 (01) : 1 - 19
  • [3] Semantic Business Process Management: A vision towards using semantic Web services for business process management
    Hepp, M
    Leymann, F
    Domingue, J
    Wahler, A
    Fensel, D
    ICEBE 2005: IEEE INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING, PROCEEDINGS, 2005, : 535 - 540
  • [4] Business process approach towards an inter-organizational enterprise system
    Vathanophas, Vichita
    BUSINESS PROCESS MANAGEMENT JOURNAL, 2007, 13 (03) : 433 - 450
  • [5] Towards Cross-Organizational Innovative Business Process Interoperability Services
    Karacan, Oemer
    Del Grosso, Enrico
    Carrez, Cyril
    Taglino, Francesco
    ENTERPRISE INTEROPERABILITY, PROCEEDINGS, 2009, 38 : 1 - +
  • [6] Towards a unified vision on animal navigation
    Menti, Giulio Maria
    Meda, Nicola
    Zordan, Mauro A.
    Megighian, Aram
    EUROPEAN JOURNAL OF NEUROSCIENCE, 2023, 57 (12) : 1980 - 1997
  • [7] Towards formalization and verification of unified business process model based on Pi calculus
    Ma, Shuailiang
    Zhang, Li
    He, Jimei
    SERA 2008: 6TH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS, PROCEEDINGS, 2008, : 93 - 101
  • [8] Towards a Common Understanding of Business Process Instance Data
    Moghadam, Nima
    Paik, Hye-young
    PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON MODEL-DRIVEN ENGINEERING AND SOFTWARE DEVELOPMENT (MODELSWARD 2016), 2016, : 193 - 200
  • [9] Towards a Data Science Framework Integrating Process and Data Mining for Organizational Improvement
    Delgado, Andrea
    Marotta, Adriana
    Gonzalez, Laura
    Tansini, Libertad
    Calegari, Daniel
    ICSOFT: PROCEEDINGS OF THE 15TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGIES, 2020, : 492 - 500
  • [10] A Method Towards Cross-Organizational Business Process Modeling from Event Logs
    Fang, Xi
    Tan, Wenan
    Zhao, Lu
    12TH CHINESE CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING (CHINESECSCW 2017), 2017, : 193 - 196