Validating Enterprise Architecture Principles Using Derivation Rules and Domain Knowledge

被引:0
|
作者
Montecchiari, Devid [1 ,2 ]
Hinkelmann, Knut [1 ,3 ]
机构
[1] FHNW Univ Appl Sci & Arts Northwestern Switzerlan, Sch Business, Olten, Switzerland
[2] UNICAM Univ Camerino, Sch Sci & Technol, Camerino, Italy
[3] Univ Pretoria, Dept Informat, Pretoria, South Africa
关键词
Conceptual Modeling; Ontology-based Modeling; Enterprise Architecture Modeling; Ontology Engineering; Semantic Lifting; ArchiMate;
D O I
10.1007/978-3-031-43126-5_18
中图分类号
F [经济];
学科分类号
02 ;
摘要
In Enterprise Architecture Management (EAM), rules, constraints, and principles guide and govern the Enterprise Architecture (EA). These can be formulated and verified in ontology-based enterprise architecture models. The automatic validation of EA principles relies on the knowledge available in the EA models. However, there is knowledge implicit in models that humans may understand but machines cannot. For example, relationships between model elements may be derived using derivation rules and domain knowledge. Formalizing derivation rules in an enterprise ontology, we can infer this implicit knowledge and make it available to the machine for reasoning. This research demonstrates the feasibility of using derivation rules to extract implicit knowledge from enterprise models allowing EA principles validation and supporting EAM. The research contribution is presented using a concrete real-world use case and implementing the derivation rules for the EA modeling standard ArchiMate.
引用
收藏
页码:244 / 259
页数:16
相关论文
共 50 条
  • [21] Enterprise integration using enterprise architecture
    Finkelstein, C
    CONSTRUCTING THE INFRASTRUCTURE FOR THE KNOWLEGE ECONOMY: METHODS AND TOOLS, THEORY AND STRUCTURE, 2004, : 43 - 82
  • [22] Using Domain Knowledge in Coevolution and Reinforcement Learning to Simulate a Logistics Enterprise
    Zhao, Ying
    Hemberg, Erik
    Derbinsky, Nate
    Mata, Gabino
    O'Reilly, Una-May
    PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2022, 2022, : 514 - 517
  • [23] Validating Enterprise Architecture Using Ontology-Based Approach A Case Study of Student Internship Programme
    Oussena, Samia
    Essien, Joe
    2013 3RD INTERNATIONAL SYMPOSIUM ISKO-MAGHREB, 2013,
  • [24] Domain Architectures as an Instrument to Refine Enterprise Architecture
    Bruls, Wiel A. G.
    van Steenbergen, M.
    Foorthuis, R. M.
    Bos, R.
    Brinkkemper, S.
    COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 2010, 27 : 517 - 540
  • [25] Domain architectures as an instrument to refine enterprise architecture
    Bruls W.A.G.
    van Steenbergen M.
    Foorthuis R.M.
    Bos R.
    Brinkkemper S.
    Communications of the Association for Information Systems, 2010, 27 (01): : 517 - 540
  • [26] MineAr: Using Crowd Knowledge for Mining Association Rules in the Health Domain
    Someswar, Milan
    Bhattacharya, Arnab
    PROCEEDINGS OF THE ACM INDIA JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE AND MANAGEMENT OF DATA (CODS-COMAD'18), 2018, : 108 - 117
  • [27] Research on the Architecture of Enterprise Knowledge Network Construction
    Liu, Bingfeng
    He, Guojing
    PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON SOCIAL NETWORK, COMMUNICATION AND EDUCATION (SNCE 2017), 2017, 82 : 775 - 779
  • [28] A Design Method for the Enterprise Knowledge Management Architecture
    Kanbe, Masakazu
    Yamamoto, Shuichiro
    KNOWLEDGE-BASED SOFTWARE ENGINEERING, 2008, 180 : 433 - 442
  • [29] Enterprise knowledge security architecture for military experimentation
    Maule, RW
    INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOL 1-4, PROCEEDINGS, 2005, : 3409 - 3414
  • [30] TACFIRE: Enterprise knowledge in service oriented architecture
    Maule, R. William
    Gallup, Shelley P.
    MILCOM 2006, VOLS 1-7, 2006, : 1280 - +