Towards an ontology for process monitoring and mining

Business Process Analysis (BPA) aims at monitoring, diagnosing, simulating and mining enacted processes in order to support the analysis and enhancement of process models. An effective BPA solution must provide the means for analysing existing e-businesses at three levels of abstraction: the Business Level, the Process Level and the IT Level. BPA requires semantic information that spans these layers of abstraction and which should be easily retrieved from audit trails. To cater for this, we describe the Process Mining Ontology and the Events Ontology which aim to support the analysis of enacted processes at different levels of abstraction spanning from fine grain technical details to coarse grain aspects at the Business Level

An Analysis of Service Ontologies

Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work

An Integrated View of Data: Application of Knowledge Modeling to Data Management

Data management has become an important challenge. Good data management requires an effective approach to collecting, storing, and accessing data across the enterprise. In this paper, a knowledge modeling approach to data management is introduced with an emphasis on data requirements analysis. A knowledge model can provide a high-level view of organizational data by specifying the structure and relationships of the knowledge contents used in business processes. The proposed knowledge modeling approach is business process oriented and decision oriented. The description of the knowledge contents in the model is based on ontological specification. The model is comprised of five elements: work product, work unit, producer, stage, and modeling language. The elements of the model and the modeling process are elaborated. The proposed modeling approach is applied to the vessel chartering process in a shipping company to demonstrate its application in real-world practices

An ontology-based model management architecture for service innovation

Organizations have indicated renewed interest in service innovation, design and management, given the growth of service sector. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as data and models. Given the global nature of service value chains, there have been ever increasing demands on managing, sharing, and reusing these heterogeneous and distributed resources, both within and across organizational boundaries, through DSS consisting of database management systems (DBMS) and model management systems (MMS). Analogous to DBMS, model management systems focus on the management of decision models, dealing with representation, storage, and retrieval of models as well as a variety of applications such as analysis, reuse, sharing, and composition of models. Recent developments in the areas of semantic web and ontologies have provided a rich tool set for computational reasoning about these resources in an intelligent manner. In this chapter, we leverage these advances and apply service-oriented design principles to propose an ontology-based model management architecture supporting service innovation. The architecture is illustrated with case study scenarios and current state of implementation. The role of potential information technologies in supporting the architecture is also discussed. We then provide a roadmap to make advancements in research in this direction

Käsitteellinen lähestymistapa organisatoristen verkostojen tutkimukseen

Tutkimusympäristöt joissa eri tieteenalojen tutkijat toimivat yhdessä ratkaistakseen verkostoissa toimivien kumppaniyritysten ongelmia ovat haasteellisia tiedonvaihdon ja tutkimustiedon keräämisen kannalta. Vaikka tutkimuskohde on yhteinen, tutkijat lähestyvät sitä omien tieteidensä näkökulmasta käyttäen siihen teorioita ja menetelmiä jotka eivät ole yhteensopiva muiden kanssa. Lapin yliopistossa tehdyn tutkimustyön aikana nämä ongelmat tulivat esiin, kun useissa monialaisissa projekteissa tarkasteltiin liiketoimintaverkostoja sekä teollisuusliiketoiminnan että matkailun alalta. Projektien kohteina olevissa verkostoissa yritykset pyrkivät tyypillisesti hakemaan verkostotoiminnasta hyötyjä informaatioteknologian avulla tehostaakseen liiketoimintasuhteitaan ja siten edesauttamaan johtamiseen ja operatiiviseen toimintaan liittyvää tiedonkulkua. Pääasiallinen ongelma näissä ympäristöissä tapahtuvassa tutkimuksessa on, että uudet projektit eivät helposti pysty hyödyntämään edellisten projektien tuotoksia, koska aikaisemmin kerättyä tutkimustietoa, analyysejä tai luotuja ratkaisumalleja ei ole saatavilla siinä muodossa että ne voitaisiin ottaa uuden tutkimuksen pohjaksi. Tässä työssä on tarkasteltu ja kehitetty käsitteellisiä malleja ja niihin liittyviä menetelmiä, jotka tukevat monitieteistä liiketoimintaverkostojen tutkimusta, ja samalla tekevät mahdolliseksi hyödyntää jo olemassa olevaa tutkimustietoa. Tässä diplomityössä kehitetty ratkaisu perustuu liiketoimintaverkostojen analysointiin käsitemallintamisen avulla. Tämän tuloksena on luotu organisatoristen ympäristöjen käsitemalli, joka keskittyy integraatiota edistäviin yhteistoimintasuhteisiin, ja kuvattu siihen liittyvä tutkimuksellinen prosessi joka mahdollistaa projektin aikana syntyvän tutkimusaineiston käsitteellistämisen ja lisätiedon liitämisen niihin. Tämä helpottaa tutkimustiedon jäsentämistä ja sen jakamista tutkijoiden ja kohdealueen toimijoiden välillä. Lisäksi työssä määritellään metatietokuvauksia ja rajattuja sanastoja jotka perustuvat semanttisen webin tekniikoihin, joilla voidaan luokitella eri projektien aikana syntyviä tutkimusartefakteja ja hallinnoida tutkimustietoa.The research settings, where project teams consisting of researchers from different scientific fields, and working together to provide solutions to the issues of networked partner organizations, are challenging in terms of communicating and accumulating research knowledge. Although the focus of the research is shared, difficulties emerge because it is explored from different scientific perspectives, relying on theories and methods that do not match with others. This observation was made during research work conducted at the University of Lapland in projects that concentrated on business networks in the manufacturing and tourism industries. The organizations in these commercial environments typically seek benefits from information technology to intensify the network-wide business relationships and to improve knowledge-intensive operations and management. The main problem is that new projects cannot easily benefit from the results of past projects because the collected research materials, analyses and models are not easily found and they are difficult to align with the objectives of new projects. In this work, to resolve theses issues, conceptual models and related approaches have been analyzed and elaborated to support cross disciplinary research on business networks, and at the same time enable the re-use and sharing of research knowledge. The solution presented in this Master's thesis has been developed by relying on conceptual modelling approaches to analyze business networks. As a result, general concept model of inter-organizational environments has been built that focuses on the integrative relationships in them. Further, accompanying research process that enabies the conceptualization and annotating of the project research outcomes has been constructed. This helps in organizing and sharing research information between researchers and stakeholders. Additionally, metadata descriptions and controlled vocabularies based on semantic web technologies are defined to align research constructs originating from different projects and to support research knowledge management