Model driven validation approach for enterprise architecture and motivation extensions

As the endorsement of Enterprise Architecture (EA) modelling continues to grow in diversity and complexity, management of its schema, artefacts, semantics and relationships has become an important business concern. To maintain agility and flexibility within competitive markets, organizations have also been compelled to explore ways of adjusting proactively to innovations, changes and complex events also by use of EA concepts to model business processes and strategies. Thus the need to ensure appropriate validation of EA taxonomies has been considered severally as an essential requirement for these processes in order to exert business motivation; relate information systems to technological infrastructure. However, since many taxonomies deployed today use widespread and disparate modelling methodologies, the possibility to adopt a generic validation approach remains a challenge. The proliferation of EA methodologies and perspectives has also led to intricacies in the formalization and validation of EA constructs as models often times have variant schematic interpretations. Thus, disparate implementations and inconsistent simulation of alignment between business architectures and heterogeneous application systems is common within the EA domain (Jonkers et al., 2003). In this research, the Model Driven Validation Approach (MDVA) is introduced. MDVA allows modelling of EA with validation attributes, formalization of the validation concepts and transformation of model artefacts to ontologies. The transformation simplifies querying based on motivation and constraints. As the extended methodology is grounded on the semiotics of existing tools, validation is executed using ubiquitous query language. The major contributions of this work are the extension of a metamodel of Business Layer of an EAF with Validation Element and the development of EAF model to ontology transformation Approach. With this innovation, domain-driven design and object-oriented analysis concepts are applied to achieve EAF model’s validation using ontology querying methodology. Additionally, the MDVA facilitates the traceability of EA artefacts using ontology graph patterns

A Validation & Verification Driven Ontology: An Iterative Process

Enterprise Ireland (project MF20180009); European Union’s Horizon 2020 research and innovation program, Marie Skłodowska-Curie grant agreement No. 713654; The Royal Academy of Engineering (NRCP1516/1/39); The Royal Society (NI150203) Newton Fund scheme

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

Experiment and bias: the case of parsimony in comparative cognition

Comparative cognition is the interdisciplinary field of animal cognition and behavior studies, which includes comparative psychology and branches of ethology, biology, and neuroscience. My dissertation shows that the quasi-epistemic value of parsimony plays a problematic role in the experimental setting of comparative cognition. More specifically, I argue that an idiosyncratic interpretation of the statistical hypothesis-testing method, known as the Neyman-Pearson Method (NPM), embeds an Occamist parsimony preference into experimental methodology in comparative cognition, which results in an underattribution bias, or a bias in favor of allegedly simple cognitive ontologies. I trace this parsimony preference to the content of the null hypothesis within the NPM, and defend a strategy for modifying the NPM to guard against the underattribution bias. I recommend adopting an evidence-driven strategy for choosing the null hypothesis. Further, I suggest a role for non-empirical values, such as ethical concerns, in the weighting of Type I and Type II error-rates. I contend that statistical models are deeply embedded in experimental practice and are not value-free. These models provide an often overlooked door through which values, both epistemic and non-epistemic, can enter scientific research. Since statistical models generally, and the NPM in particular, play a role in a wide variety of scientific disciplines, this dissertation can also be seen as a case study illustrating the importance of attending to the choice a particular statistical model. This conclusion suggests that various philosophical investigations of scientific practice - from inquiry into the nature of scientific evidence to analysis of the role of values in science - would be greatly enriched by increased attention to experimental methodology, including the choice and interpretation of statistical models

Knowledge modelling of emerging technologies for sustainable building development

In the quest for improved performance of buildings and mitigation of climate change, governments are encouraging the use of innovative sustainable building technologies. Consequently, there is now a large amount of information and knowledge on sustainable building technologies over the web. However, internet searches often overwhelm practitioners with millions of pages that they browse to identify suitable innovations to use on their projects. It has been widely acknowledged that the solution to this problem is the use of a machine-understandable language with rich semantics - the semantic web technology. This research investigates the extent to which semantic web technologies can be exploited to represent knowledge about sustainable building technologies, and to facilitate system decision-making in recommending appropriate choices for use in different situations. To achieve this aim, an exploratory study on sustainable building and semantic web technologies was conducted. This led to the use of two most popular knowledge engineering methodologies - the CommonKADS and "Ontology Development 101" in modelling knowledge about sustainable building technology and PV -system domains. A prototype system - Photo Voltaic Technology ONtology System (PV -TONS) - that employed sustainable building technology and PV -system domain knowledge models was developed and validated with a case study. While the sustainable building technology ontology and PV -TONS can both be used as generic knowledge models, PV -TONS is extended to include applications for the design and selection of PV -systems and components. Although its focus was on PV -systems, the application of semantic web technologies can be extended to cover other areas of sustainable building technologies. The major challenges encountered in this study are two-fold. First, many semantic web technologies are still under development and very unstable, thus hindering their full exploitation. Second, the lack of learning resources in this field steepen the learning curve and is a potential set-back in using semantic web technologies