Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review

Semantic Web (SW) techniques, such as ontologies, are used in Information Systems (IS) to cope with the growing need for sharing and reusing data and knowledge in various research areas. Despite the increasing emphasis on unstructured data analysis in IS, structured data and its analysis remain critical for organizational performance management. This systematic literature review aims at analyzing the incorporation and impact of ontologies in Data Warehouse/Business Intelligence (DW/BI) systems, contributing to the current literature by providing a classification of works based on the field of each case study, SW techniques used, and the authors’ motivations for using them, with a focus on DW/BI design, development and exploration tasks. A search strategy was developed, including the definition of keywords, inclusion and exclusion criteria, and the selection of search engines. Ontologies are mainly defined using the Ontology Web Language standard to support multiple DW/BI tasks, such as Dimensional Modeling, Requirement Analysis, Extract-Transform-Load, and BI Application Design. Reviewed authors present a variety of motivations for ontology-driven solutions in DW/BI, such as eliminating or solving data heterogeneity/semantics problems, increasing interoperability, facilitating integration, or providing semantic content for requirements and data analysis. Further, implications for practice and research agenda are indicated.info:eu-repo/semantics/publishedVersio

Pattern-based design applied to cultural heritage knowledge graphs

Ontology Design Patterns (ODPs) have become an established and recognised practice for guaranteeing good quality ontology engineering. There are several ODP repositories where ODPs are shared as well as ontology design methodologies recommending their reuse. Performing rigorous testing is recommended as well for supporting ontology maintenance and validating the resulting resource against its motivating requirements. Nevertheless, it is less than straightforward to find guidelines on how to apply such methodologies for developing domain-specific knowledge graphs. ArCo is the knowledge graph of Italian Cultural Heritage and has been developed by using eXtreme Design (XD), an ODP- and test-driven methodology. During its development, XD has been adapted to the need of the CH domain e.g. gathering requirements from an open, diverse community of consumers, a new ODP has been defined and many have been specialised to address specific CH requirements. This paper presents ArCo and describes how to apply XD to the development and validation of a CH knowledge graph, also detailing the (intellectual) process implemented for matching the encountered modelling problems to ODPs. Relevant contributions also include a novel web tool for supporting unit-testing of knowledge graphs, a rigorous evaluation of ArCo, and a discussion of methodological lessons learned during ArCo development

A Method to Screen, Assess, and Prepare Open Data for Use

Open data's value-creating capabilities and innovation potential are widely recognized, resulting in a notable increase in the number of published open data sources. A crucial challenge for companies intending to leverage open data is to identify suitable open datasets that support specific business scenarios and prepare these datasets for use. Researchers have developed several open data assessment techniques, but those are restricted in scope, do not consider the use context, and are not embedded in the complete set of activities required for open data consumption in enterprises. Therefore, our research aims to develop prescriptive knowledge in the form of a meaningful method to screen, assess, and prepare open data for use in an enterprise setting. Our findings complement existing open data assessment techniques by providing methodological guidance to prepare open data of uncertain quality for use in a value-adding and demand-oriented manner, enabled by knowledge graphs and linked data concepts. From an academic perspective, our research conceptualizes open data preparation as a purposeful and value-creating process

Implementation of a knowledge discovery and enhancement module from structured information gained from unstructured sources of information

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Prijedlog ontološki utemeljenog metodološkog okvira za razvoj više-platformskih mobilnih aplikacija

Software development teams are faced with the lack of interoperability during the development of mobile applications for two or more target platforms. The development for second and every other platform means a new project with a need to repeat almost all the phases defined by the chosen methodology but with a narrow possibility of reuse of the already defined artifacts. The existing efforts of professional and scientific community to solve this problem have a similar approach (code once, run everywhere) with similar advantages and drawbacks. Thus, this dissertation aims to propose a different solution and is concerned with: (1) analyzing the methodologies suitable for mobile applications development, (2) observing the implementation of prototype application in order to define artifacts that are created during the development process for two target platforms, (3) semantic description of artifacts and their meaning, and (4) defining unique ontological definition as a base for methodological interoperability. The results of a systematic literature review performed on 6761 primary studies, show that current state-of-the-art literature brings only 22 development methodologies and 7 development approaches which can be identified as eligible for multi-platform mobile applications development. Among these, Mobile-D methodology accompanied with Test Driven Development was chosen and used in the observed development processes for Android and Windows Phone platforms. Total of 71 artifacts were identified and the artifacts reusability level when developing for second target platform was 66.00%. In the last research phase, the artifacts for both platforms were semantically described into a single ontological description comprising 213 classes, 14 object properties and 2213 axioms defined in ALCRIF DL expression sub-language. Having this ontology proved as correct and valid, flexible, reusable and extensible we created the basis for development of an information system to guide the development teams in a more efficient and interoperable process of multiplatform mobile applications development.Razvojni timovi susreću se s problemom neinteroperabilnosti prilikom razvoja aplikacija za dvije ili više mobilnih platformi. Razvoj aplikacije za drugu i svaku sljedeću platformu znači novi projekt u kojem je potrebno ponovno provesti većinu faza definiranih odabranom metodikom razvoja, pri čemu se kreirani artefakti teško ili uopće ponovno ne koriste. Napori profesionalne i znanstvene zajednice za rješenjem ovog problema imaju sličan pristup (kodiraj jednom, koristi svugdje), slične prednosti, ali i zajedničke nedostatke. Stoga ova disertacija navedenom problemu pristupa na nov način i bavi se: (1) analiziranjem metodika pogodnih za razvoj mobilnih aplikacija, (2) promatranjem razvoja prototipne aplikacije u svrhu definiranja artefakata koji nastaju pri razvoju mobilne aplikacije za dvije ciljane platforme, (3) semantičkim opisivanjem definiranih artefakata i njihovih značenja, te (4) definiranjem jedinstvene ontološke definicije kao osnove za metodološku interoperabilnost. Rezultati sustavnog pregleda literature provedenog nad 6761 radom pokazali su da se trenutno u literaturi spominju 22 metodike i 7 pristupa koji su pogodni za razvoj više-platformskih mobilnih aplikacija. Između identificiranih metodika odabrani su Mobile-D metodika i pristup razvoju vođen testiranjem, koji su korišteni pri implementaciji prototipnog rješenja za Android i Windows Phone platformu. Ukupno je identificiran 71 artefakt pri čemu je ponovna iskoristivost artefakata pri razvoju za drugu platformu bila 66.00%. U posljednjoj su fazi istraživanja artefakti semantički opisani u zajedničku ontološku definiciju koja u konačnici sadrži 213 klasa, 14 objektnih svojstava i 2213 aksioma definiranih pomodu ALCRIF-DL jezika izraza. U radu je dokazano da je ontologija valjana, fleksibilna, ponovno iskoristiva i nadogradiva, čime je kreirana osnova za razvoj informacijskog sustava koji bi vodio razvojne timove u efikasnijem i bolje interoperabilnom procesu razvoja više-platformskih mobilnih aplikacija