Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge

A431c87236a21a7bebf38de6bd12a67b?s=47 andreasmartin
November 08, 2013

Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge

Full Paper Presentation @ The First International Conference on Enterprise Systems ES 2013 - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6690082

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andreasmartin

November 08, 2013
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  1. 1.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Integrating an

    Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge Andreas Martin, Sandro Emmenegger and Gwendolin Wilke Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 1
  2. 2.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Table of

    contents 1. Introduction 1. CTI founded Research Projects 2. [sic!] 3. The application partner 2. Project Goal and Application Scenario 3. The Approach 4. Implementation 5. Conclusion & Future Work Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 2
  3. 3.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Introduction CTI

    founded Research Projects / [sic!] / the application partner Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 3
  4. 4.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW CTI founded

    Research Projects  The Commission for Technology and Innovation (CTI) promotes projects in applied research and development between centres of higher education and companies.  The Swiss Confederation founds 50 % of the total costs.  The application partner must cover at least 50 % of the total costs - the cash contribution must equal at least 10% of the federal contribution.  This work was supported in part by the CTI under Grant 14575.1 PFES-ES. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 4
  5. 5.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW  This

    work is an outcome of the research project [sic!].  [sic!] stands for software integration using ontology-based case-based reasoning.  Start: September 2012  End: January 2015  CTI – founding (50%): CHF 285’000.-  Application partner: ELO Digital Office CH AG Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 5
  6. 6.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The application

    partner – ELO Digital Office CH AG  The ELO Digital Office CH AG is a subsidiary of the ELO Digital Office GmbH, which has its headquarters in Stuttgart (Germany).  ELO develops and sells software solutions in the areas of electronic document management, digital archiving and workflow management - Enterprise Content Management (ECM).  ELO Digital Office CH AG is an own legal entity and acts on the Swiss market.  ELO Digital Office CH AG has an extensive network of local partners. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 6
  7. 7.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Project Goal

    and Application Scenario Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 7
  8. 8.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Problem 

    ELO is an international company with branch offices and distribution partners all over Europe…  …project knowledge is distributed over different people…  …and also over different teams in different locations.  For a project worker, it is of vital importance to have access to other people’s historic project knowledge and experience. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 8
  9. 9.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Problem and

    Goal  Current Situation: ELO uses enterprise content management and document management systems, workflow management systems, a user forum, as well as a centralized project database.  Problem: An all-embracing management of historic project knowledge based on problem descriptions is not available.  Goal: Improving and optimizing experience management process …  … by implementing an ontology-based case-based reasoning system. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 9
  10. 10.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

     The application scenarios are elicited from our business partner ELO Digital Office CH AG.  An IT- project usually consists of the following three phases:  In every phase certain project knowledge is needed.  From other people… / about certain technical issues… / etc.  We focus on the sales phase and we derived two exemplary application scenarios:  Application Scenario 1: Answering a customer’s questionnaire.  Application Scenario 2: Searching for a module expert. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 10 Sales Implementation Operation and Maintenance
  11. 11.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    - Overview Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 11 Sales Implementation Operation and Maintenance
  12. 12.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    - Overview Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 12 Sales Implementation Operation and Maintenance
  13. 13.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    - Overview Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 13 Sales Implementation Operation and Maintenance
  14. 14.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    1 Answering a customer’s questionnaire.  In the tendering part of the sales phase of an ECM project, a detailed offer is assembled.  The offer is based on the customer’s specifications and requirements catalogue, which is usually handed out as a questionnaire. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 14
  15. 15.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    1 Answering a customer’s questionnaire. Typical question:  Is the integration of an ELO product or module possible with a customer’s system component? If the person in charge does not know the answer…  …it may be helpful to retrieve similar project experience and related documentation. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 15
  16. 16.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    1 Answering a customer’s questionnaire. The information need of a person trying to answer a question includes details of the integration such as the question  if integration is possible,  if customization is necessary (and possible),  if additional programming effort is necessary,  if there are function parameters, or  if there are functionality constraints.  Example: “Does the ECM/DSM software support archiving the MS Exchange 2007 journal?” Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 16
  17. 17.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    2 Searching for a module expert.  Software integration is often a complex process, where usually different employees are in charge of different subtasks.  In particular, employees usually specialize on different aspects of the integration process or on different ELO modules. E.g., a person with a strong SAP background might be an “ELO SAP module” specialist. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 17
  18. 18.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Application Scenario

    2 Searching for a module expert.  it may be helpful to retrieve similar historic projects in order to find an module expert.  In this scenario, the information need of the project manager is to find a module expert who has experience with integrating the customer’s system component in question. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 18
  19. 19.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach…

    …and Related Work Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 19
  20. 20.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Three basic

    underlying research topics… 1. Case-based Reasoning (CBR) 2. Enterprise Architectures 3. Enterprise Ontologies … why using them?  This work is an outcome of a «Design Science Research» instantiation: Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 20 Design science research cycles adapted from (Hevner and Chatterjee, 2010; Hevner et al., 2004)
  21. 21.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach

    1. Case-based Reasoning (CBR) Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 21
  22. 22.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW What is

    Case-based Reasoning (CBR)  CBR can be seen as “reasoning by remembering”…  and it is a technically independent methodology to humans and information systems.  “Case-based reasoning is both […] the ways people use cases to solve problems and the ways we can make machines use them”.  Two central elements: 1. the CASE 2. the CBR- CYCLE (& CASE- BASE) (a) SIMILARITY / (b) Adaptation / (c) Evaluation / (d) Learning Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 22
  23. 23.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW What is

    Case-based Reasoning (CBR) CASE  Traditional CBR terminology: a case consists of a problem space (problem items / descriptions) that is used for describing a certain solution space (solution items).  Bergmann’s CBR terminology: a case consists of a case characterization space that is used for describing a certain lessons space (derived from “lesson learned”).  Our CBR terminology: a case consists of a case characterization (sometimes called metadata) that is used for describing a certain case content (sometimes called lesson). Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 23 Characterization Content CASE That is a concession to the business needs (relevance) – familiar and domain-oriented wording.
  24. 24.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW What is

    Case-based Reasoning (CBR) CBR- CYCLE (& CASE- BASE)  Retrieve the most similar cases from the knowledge base (case-base containing previous cases) based on the problem description of the new case (problem case) using a similarity mechanism.  Reuse the knowledge in the retrieved case(s) in order to solve the current problem – adapt the historical knowledge to the new problem (adaptation).  Revise and test the suggested solution e.g. by evaluating it under the real world problem (evaluation).  Retain useful experience (past solutions and failures) for future reuse and store a new case in the knowledge base (case learning). Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 24 Based on: A. Aamodt and E. Plaza, “Case-Based Reasoning : Foundational Issues , Methodological Variations , and System Approaches,” Artificial Intelligence Communications, vol. 7, no. 1, pp. 39–59, 1994.
  25. 25.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Why Case-based

    Reasoning (CBR)? Findings  Our domain expert focus group (ELO people)  are experts in Enterprise Content Management (ECM).  They are using the latest technology on the market (their own software) for project management.  They have strong expertise in IT and business consulting.  Our main finding is: They are thinking in CASES and METADATA. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 25
  26. 26.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Why Case-based

    Reasoning (CBR)? Relevance 1. Requirements from business:  A way to gather information and lessons from project- work including metadata and data. → CASE (vocabulary)  A knowledge/data base -> Case- BASE  A way to retrieve similar cases -> SIMILARITY  A generic management process or method -> CBR- CYCLE  A prototypical implementation as IT system -> Case-based Reasoning Application Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 26
  27. 27.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Why a

    new Case-based Reasoning (CBR) Approach? Relevance 2. Requirements from business:  Focus on standardized methodology and technology.  ELO wishes to easily extend existing models and reuse existing knowledge about the enterprise. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 27
  28. 28.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach

    2. Enterprise Architectures Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 28
  29. 29.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW How to

    re-use existing knowledge? What can be used and what is available? Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 29
  30. 30.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Enterprise Architecture

    Knowledge about the Enterprise  Enterprise Architectures (AE) are a way to model the relevant aspects of an enterprise and interdependencies between business and information systems.  An Enterprise Architecture (AE) is  “[…] a coherent whole of principles, methods and models that are used in the design and realisation of an enterprise’s organisational structure, business processes, information systems, and infrastructure” (Lankhorst 2009, p. 3).  Example Enterprise Architecture Frameworks (EAF):  Zachman Framework  The Open Group Architecture Framework (TOGAF)  ArchiMate Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 30 Lankhorst, M., 2009. Enterprise Architecture at Work. Berlin, Heidelberg: Springer Berlin Heidelberg.
  31. 31.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Enterprise Architecture

    ArchiMate® Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 31 The Open Group, “ArchiMate® 1.0 Specification,” 2009. [Online]. Available: http://pubs.opengroup.org/architecture/archimate- doc/ts_archimate/. ArchiMate is a technical standard from The Open Group and is based on the concepts of the IEEE 1471 standard.
  32. 32.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Enterprise Architecture

    ArchiMate® - Example  Business layer  Application layer  Technology layer Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 32 The Open Group, “ArchiMate® 1.0 Specification,” 2009. [Online]. Available: http://pubs.opengroup.org/architecture/archimate- doc/ts_archimate/.
  33. 33.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach

    3. Enterprise Ontologies Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 33
  34. 34.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW How re-use

    existing knowledge? Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 34
  35. 35.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Enterprise Ontologies

    and Semantic Technologies  “An ontology is a formal, explicit specification of a shared conceptualisation” (Studer, 1998, p. 184)  “The main purpose of an enterprise ontology is to promote the common understanding between people across enterprises, as well as to serve as a communication medium between people and applications, and between different applications” (Leppänen, 2007, p. 273)  Semantic Technologies: Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 35 http://smiy.wordpress.com/2011/01/10/the-common-layered-semantic-web-technology-stack/
  36. 36.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW  ArchiMEO

    is an enterprise ontology based on ArchiMate and is extended with selected concepts from other enterprise ontologies.  ArchiMEO is implemented using RDF(s) and OWL.  ArchiMEO has been developed by several team members of the FHNW Information and Knowledge Management Research Group (IKM).  ArchiMEO is licensed under a Creative Commons Attribution- ShareAlike 3.0 Unported License.  ArchiMEO is available for download as TTL- files (Terse RDF Triple Language) under: ikm-group.ch/archimeo Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 36 ArchiMate is a technical standard from The Open Group. RDF(S) / OWL is a W3C standard. The enterprise ontology ArchiMEO is based on ArchiMate.
  37. 37.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach

    4. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 37
  38. 38.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach

    Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 38
  39. 39.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Why a

    new Case-based Reasoning (CBR) approach? Rigor  Our state of the art analysis has shown that there is a potential for new ontology-based CBR approach, which uses an enterprise architecture formalized in an enterprise ontology. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 39
  40. 40.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW The Approach

    applied to Application Scenario Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 40
  41. 41.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation Integrating

    an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 41
  42. 42.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation 

    [sic!] is an iterative research project.  The results presented here are the outcome of the first implementation iteration (Prototype I).  Prototype I: Case Retrieval  Case-based Reasoning Ontology  CBR- Retrieval Component  User Interface  Similarity- Functions  Prototype II: whole CBR-Cycle Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 42
  43. 43.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation -

    Ontologies  ArchiMEO: the Enterprise Ontology as basis.  Case Ontology: selected elements from the Case Management Model and Notation (CMMN).  Similarity Ontology: retrieval mechanism.  CBR Ontology: extends the Case Ontology and the Similarity Ontology for CBR specific needs.  Project Ontology : contains concepts that are specific for project related use cases.  ELO Domain Ontology: domain specific ontology that contains knowledge of ELO. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 43
  44. 44.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation -

    Similarity Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 44
  45. 45.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation -

    Similarity Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 45 What will be compared? Case Characterization Content «New case» Case Characterization Content «case 1» Case Characterization Content «case 2» Case Characterization Content «case X» Compare
  46. 46.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation Case

    characterization stored in ontology Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 46 System: Third-party systems that will be connected (e.g. ERP System) Requirement: Requirement and Solution (e.g. Archiving) Module: ELO – module (e.g. Backup) BusinessActor: Module expert
  47. 47.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation Similarity

    - Weighting Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 47 Application Scenario 1: Answering a customer’s questionnaire. • Which third-party system should be integrated? • Which requirement should be fulfilled? • Which ELO- module would be worth considering? Application Scenario 2: Searching for a module expert. • Which ELO system is relevant? • Who is an expert for a specific ELO module?
  48. 48.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation -

    Similarity - Annotations  Similarity functions: (a) levenshtein: minimal number of edit operations when transforming one string to another. (b) version: custom function for comparing versions. (c) average: average of numbers. (d) equals: is one string identical to another. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 48 cbr:Case elo:System elo:Module eo:Person hasSystem hasModule hasExpert name version name role level rdfs:label ObjectPropertySim weight: 1 simFunction: average ObjectPropertySim weight: 5 simFunction: average AnnotationPropertySim weight: 3 simFunction: equals annotationProperty: label language: en ObjectPropertySim weight: 2 simFunction: average DatatypePropertySim weight: 2 simFunction: levenshtein DatatypePropertySim weight: 1 simFunction: version DatatypePropertySim weight: 1 simFunction: equals DatatypePropertySim weight: 3 simFunction: levenshtein
  49. 49.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Implementation -

    Similarity - Query Case Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 49 cbr:Case elo:System elo:Module eo:Person hasSystem hasModule hasExpert name version name role level rdfs:label ObjectPropertySim weight: 1 simFunction: average ObjectPropertySim weight: 5 simFunction: average AnnotationPropertySim weight: 3 simFunction: equals annotationProperty: label language: en ObjectPropertySim weight: 2 simFunction: average DatatypePropertySim weight: 2 simFunction: levenshtein DatatypePropertySim weight: 1 simFunction: version DatatypePropertySim weight: 1 simFunction: equals DatatypePropertySim weight: 3 simFunction: levenshtein cbr:Case elo:System elo:Module eo:Person hasSystem hasModule hasExpert name level rdfs:label «_queryCase» «_querySystem» «mySQL» «_queryModule» «Backup» «_queryExpert» «Expert» Query Case
  50. 50.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW cbr:Case elo:System

    elo:Module eo:Person hasSystem hasModule hasExpert name version name role level rdfs:label ObjectPropertySim weight: 1 simFunction: average ObjectPropertySim weight: 5 simFunction: average AnnotationPropertySim weight: 3 simFunction: equals annotationProperty: label language: en ObjectPropertySim weight: 2 simFunction: average DatatypePropertySim weight: 2 simFunction: levenshtein DatatypePropertySim weight: 1 simFunction: version DatatypePropertySim weight: 1 simFunction: equals DatatypePropertySim weight: 3 simFunction: levenshtein cbr:Case elo:System elo:Module eo:Person hasSystem hasModule hasExpert name role level rdfs:label «Case2» «case2System» «MySQL» «case2Module» «Backup» «case2Expert» «Programmer» «Beginner» version «5.1» cbr:Case elo:System elo:Module eo:Person hasSystem hasModule hasExpert name role level rdfs:label «Case1» «case1System» «Oracle» «case1Module» «Barcode» «case1Expert» «TechConsultant» «Expert» version «11g» Implementation - Similarity - Cases Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 50 Case 1 (in Case Base) Case 2 (in Case Base)
  51. 51.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Class Instance

    Property Weight Function Sim #1 Sim #2 Sim #3 Case “_queryCase” hasSystem = ”_querySys” hasModule = ”_queryMod” “case1” hasSystem = ”case1Sys” 1 average 0.17 0.46 hasModule = ”case1Mod” 5 average 0.52 “case2” hasSystem = ”case2Sys” 1 average 1.0 0.66 hasModule = ”case2Mod” 5 average 0.6 System “_querySys” name = “MySQL” version = “” “case1Sys name = “Oracle” 2 levenshtein 0.17 0.17 version “11g” 1 levenshtein “case2Sys name = “MySQL” 2 levenshtein 1.0 1.0 version = “5.1” 1 levenshtein Module “_queryMod” label = “Backup” hasExpert “_queryExp” “case1Mod” label = “Barcode” 3 equals 0.2 0.52 hasExpert = “case1Exp” 2 average 1.0 “case2Mod” label = “Backup” 3 equals 1.0 0.6 hasExpert = “case2MExp” 2 average 0.0 Employee “_queryExp” role = “” level = “Expert” “case1Exp” role = “TechConsultant” 3 levenshtein 1.0 level = “Expert” 1 equals 1.0 “case2Exp” role = “Programmer” 3 levenshtein 0.0 level = “Beginner” 1 equals 0.0 Class Instance Property Weight Function Sim #1 Sim #2 Sim #3 Case “_queryCase” hasSystem = ”_querySys” hasModule = ”_queryMod” “case1” hasSystem = ”case1Sys” 1 average hasModule = ”case1Mod” 5 average “case2” hasSystem = ”case2Sys” 1 average hasModule = ”case2Mod” 5 average System “_querySys” name = “MySQL” version = “” “case1Sys name = “Oracle” 2 levenshtein 0.17 0.17 version “11g” 1 levenshtein “case2Sys name = “MySQL” 2 levenshtein 1.0 1.0 version = “5.1” 1 levenshtein Module “_queryMod” label = “Backup” hasExpert “_queryExp” “case1Mod” label = “Barcode” 3 equals hasExpert = “case1Exp” 2 average “case2Mod” label = “Backup” 3 equals hasExpert = “case2MExp” 2 average Employee “_queryExp” role = “” level = “Expert” “case1Exp” role = “TechConsultant” 3 levenshtein 1.0 level = “Expert” 1 equals 1.0 “case2Exp” role = “Programmer” 3 levenshtein 0.0 level = “Beginner” 1 equals 0.0 Class Instance Property Weight Function Sim #1 Sim #2 Sim #3 Case “_queryCase” hasSystem = ”_querySys” hasModule = ”_queryMod” “case1” hasSystem = ”case1Sys” 1 average hasModule = ”case1Mod” 5 average “case2” hasSystem = ”case2Sys” 1 average hasModule = ”case2Mod” 5 average System “_querySys” name = “MySQL” version = “” “case1Sys name = “Oracle” 2 levenshtein 0.17 0.17 version “11g” 1 levenshtein “case2Sys name = “MySQL” 2 levenshtein 1.0 1.0 version = “5.1” 1 levenshtein Module “_queryMod” label = “Backup” hasExpert “_queryExp” “case1Mod” label = “Barcode” 3 equals 0.2 0.52 hasExpert = “case1Exp” 2 average 1.0 “case2Mod” label = “Backup” 3 equals 1.0 0.6 hasExpert = “case2MExp” 2 average 0.0 Employee “_queryExp” role = “” level = “Expert” “case1Exp” role = “TechConsultant” 3 levenshtein 1.0 level = “Expert” 1 equals 1.0 “case2Exp” role = “Programmer” 3 levenshtein 0.0 level = “Beginner” 1 equals 0.0 Class Instance Property Weight Function Sim #1 Sim #2 Sim #3 Case “_queryCase” hasSystem = ”_querySys” hasModule = ”_queryMod” “case1” hasSystem = ”case1Sys” 1 average 0.17 0.46 hasModule = ”case1Mod” 5 average 0.52 “case2” hasSystem = ”case2Sys” 1 average 1.0 0.66 hasModule = ”case2Mod” 5 average 0.6 System “_querySys” name = “MySQL” version = “” “case1Sys name = “Oracle” 2 levenshtein 0.17 0.17 version “11g” 1 levenshtein “case2Sys name = “MySQL” 2 levenshtein 1.0 1.0 version = “5.1” 1 levenshtein Module “_queryMod” label = “Backup” hasExpert “_queryExp” “case1Mod” label = “Barcode” 3 equals 0.2 0.52 hasExpert = “case1Exp” 2 average 1.0 “case2Mod” label = “Backup” 3 equals 1.0 0.6 hasExpert = “case2MExp” 2 average 0.0 Employee “_queryExp” role = “” level = “Expert” “case1Exp” role = “TechConsultant” 3 levenshtein 1.0 level = “Expert” 1 equals 1.0 “case2Exp” role = “Programmer” 3 levenshtein 0.0 level = “Beginner” 1 equals 0.0 Implementation Similarity - Computation Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 51 cbr:Case elo:System elo:Module eo:Person hasSystem hasModule hasExpert name version name role level rdfs:label ObjectPropertySim weight: 1 simFunction: average ObjectPropertySim weight: 5 simFunction: average AnnotationPropertySim weight: 3 simFunction: equals annotationProperty: label language: en ObjectPropertySim weight: 2 simFunction: average DatatypePropertySim weight: 2 simFunction: levenshtein DatatypePropertySim weight: 1 simFunction: version DatatypePropertySim weight: 1 simFunction: equals DatatypePropertySim weight: 3 simFunction: levenshtein elo:System eo:Person name version name role level elo:Module rdfs:label cbr:Case elo:System elo:Module hasSystem hasModule 46% 66%
  52. 52.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW System architecture

     Technology:  Apache Jena: open source Java framework for building Semantic Web applications  OpenDolphin: open-source library for a lightweight remote model-view- controller separation.  JavaFX: GUI framework  TopBraid Composer: an ontology engineering software (paid) Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 52
  53. 53.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Conclusion &

    Future Work Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 53
  54. 54.

    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Conclusion I

    Research perspective:  It is possible to retrieve historic project knowledge from a knowledge base using case based reasoning.  The novelty is the in-ontology approach that embeds the knowledge of the enterprise architecture ArchiMate in the CBR system using the W3C conform formalization ArchiMEO.  The similarity mechanism uses relations in the ontology in order to calculate the overall similarity of a query case to a historical case. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 54
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    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Conclusion II

    Business perspective  Standardized methodologies and technologies:  Enterprise concepts and relations are based on ArchiMate.  «ArchiMate is a technical standard from The Open Group and is based on the concepts of the IEEE 1471 standard»  ArchiMate is documented and not proprietary.  ArchiMEO is a RDF(S)/OWL ontology.  «RDF(S) / OWL is a W3C Semantic Web standard»  No proprietary database technology.  CBR- Similarity uses the SPARQL Inferencing Notation (SPIN) on persistence layer  «SPIN is a SPARQL-based rule and constraint language for the W3C Semantic Web. SPIN is W3C Member Submission and open specification»  No proprietary code on persistence layer and inference support on business logic layer. Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 55
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    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Future work:

     Implementation perspective:  Current - Prototype 1: Case Retrieval  Automatic Retrieve (Similarity)  Prototype 2: CBR- Cycle  Automatic Retrieve (Similarity),  Manual Reuse (Adaptation), Revision (Evaluation),  Automatic Retain (Case Learning - adding to case-base)  Prototype 3: Case Adaptation & Learning  Automatic Retrieve (Similarity),  Semi-automatically Reuse (Adaptation - OWL/Rule Reasoning & ML) ,  Manual Revision (Evaluation),  Automatic Retain (Case Learning & Ontology Learning - adding to elements to domain ontology, OWL/Rule Reasoning)  Research perspective:  Enhance usability and retrieval in Ontology-based CBR using NLP- technology  Adaptation algorithms for the Ontology-based CBR [sic!] approach  Further sophisticated similarity algorithms for the Ontology-based CBR [sic!] approach Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 56
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    CTI # 14575.1 PFES-ES Andreas Martin - FHNW Integrating an

    Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 57  Knowledge Work and Case-based Reasoning  Agile Business Process Management and Workflow Systems  Enterprise Software Engineering, Architectures & Development  Semantic Technologies  Enterprise Architectures / Ontologies  Information & Knowledge Management  Computational Linguistics and Natural Language Processing You can find me on:  linkedin.com/in/andreasmartinch  andreasmartin.ch Team member of the FHNW «Information and Knowledge Management Research Group» IKM. Project lead of the CTI- project «Software Integration using Ontology- based Case-Based Reasoning» [sic!]. Contributor to the ArchiMate based enterprise ontology ArchiMEO. Always interested in a research collaboration in the following fields: