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
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
founded Research Projects / [sic!] / the application partner Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 3
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
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
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
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
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
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
- Overview Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 11 Sales Implementation Operation and Maintenance
- Overview Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 12 Sales Implementation Operation and Maintenance
- Overview Integrating an Enterprise Architecture Ontology in a Case-based Reasoning Approach for Project Knowledge 13 Sales Implementation Operation and Maintenance
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
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
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
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
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
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)
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
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.
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.
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
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
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
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
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.
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.
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/.
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/
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.
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
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
[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
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
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
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
- 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?
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
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
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
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
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:
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