Elena García-Barriocanal

Integrating descriptions of knowledge management learning activities into large ontological structures: a case study

Ontologies have been recognized as a fundamental infrastructure for advanced approaches to Knowledge Management (KM) automation, and the conceptual foundations for them have been discussed in some previous reports. Nonetheless, such conceptual structures should be properly integrated into existing ontological bases, for the practical purpose of providing the required support for the development of intelligent applications. Such applications should ideally integrate KM concepts into a framework of commonsense knowledge with clear computational semantics. In this paper, such an integration work is illustrated through a concrete case study, using the large OpenCyc knowledge base. Concretely, the main elements of the Holsapple and Joshi KM ontology and some existing work on e-learning ontologies are explicitly linked to OpenCyc definitions, providing a framework for the development of functionalities that use the built-in reasoning services of OpenCyc in KM activities. The integration can be used as the point of departure for the engineering of KM-oriented systems that account for a shared understanding of the discipline and rely on public semantics provided by one of the largest open knowledge bases available.

Evaluating collaborative filtering recommendations inside large learning object repositories

Collaborative filtering (CF) algorithms are techniques used by recommender systems to predict the utility of items for users based on the similarity among their preferences and the preferences of other users. The enormous growth of learning objects on the internet and the availability of preferences of usage by the community of users in the existing learning object repositories (LORs) have opened the possibility of testing the efficiency of CF algorithms on recommending learning materials to the users of these communities. In this paper we evaluated recommendations of learning resources generated by different well known memory-based CF algorithms using two databases (with implicit and explicit ratings) gathered from the popular MERLOT repository. We have also contrasted the results of the generated recommendations with several existing endorsement mechanisms of the repository to explore possible relations among them. Finally, the recommendations generated by the different algorithms were compared in order to evaluate whether or not they were overlapping. The results found here can be used as a starting point for future studies that account for the specific context of learning object repositories and the different aspects of preference in learning resource selection.

Applying an ontology approach to IT service management for business-IT integration

Best practice frameworks focused on the integration of business and IT, such as ITIL, help organizations create and share effective service management. However, guidelines and models are commonly specified using natural language or graphical representations, both lacking the computational semantics needed to enable their automated validation, simulation or execution. This paper presents an ontology approach, which can help service providers add semantics to their service management process models and detect semantic ambiguities, uncertainties and contradictions. The proposed ontology draws its knowledge from good practice guidance for ITSM, enabling the current business gap that exists in many IT service providers to be overcome. To do so, service management processes are formalized in terms of an ontology defined using OWL combined with SWRL and SQWRL, the latter two being used to specify constraints and infer new knowledge. Our ontology provides support for executable service models with computational semantics. SWRL rules associated with the ontology can be categorized into three groups: (1) Model consistency; (2) SLA breaches; and (3) Proactive actions. Such rules allow us to better manage actual service management processes which are delivered in line with business needs. Also, the resulting specifications can be shared, reused and interchanged by automated means using e-business frameworks such as ebXML.

Computing with competencies: Modelling organizational capacities

The notion of competency provides an observable account of concrete human capacities under specific work conditions. The fact that competencies are subject to concrete kinds of measurement entails that they are subject to some extent to comparison and even in some sense, calculus. Then, competency models and databases can be used to compute competency gaps, to aggregate competencies of individuals as part of groups, and to compare capacities. However, as of today there is not a commonly agreed model or ontology for competencies, and scattered reports use different models for computing with competencies. This paper addresses how computing with competencies can be approached from a general perspective, using a flexible and extensible ontological model that can be adapted to the particularities of concrete organizations. Then, the consideration of competencies as an organizational asset is approached from the perspective of particular issues as competency gap analysis, the definition of job positions and how learning technology can be linked with competency models. The framework presented provides a technology-based baseline for organizations dealing with competency models, enabling the management of the knowledge acquisition dynamics of employees as driven by concrete and measurable accounts of organizational needs.

Exploring user-based recommender results in large learning object repositories: the case of MERLOT

Collaborative filtering (CF) techniques have proved to be effective in their application to e-commerce and other application domains. However, their applicability to the recommendation of learning resources deserve separate attention as seeking learning resources can be hypothesized to be substantially different from selecting information resources or products for purchase. To date there are only a few scattered studies reporting on the application of well known user-based CF algorithms to learning object repositories. This paper reports an empirical study carried out by using MERLOT data and existing user-based CF algorithms. The aim of this preliminary study was that of finding evidence on accuracy measures of existing CF algorithms, and the relation of the items recommended with other elements of the repository. The results can be used as a starting point for future studies that account for the specific context of learning object repositories and the different aspects of preference in learning resource selection.

An empirical analysis of ontology-based query expansion for learning resource searches using MERLOT and the Gene ontology

This paper proposes an expansion of queries based on formal domain ontologies in the context of the search for learning resources in repositories. The expansion process uses the relation types that are represented in these models; common ontological relations, and ontological relations specific to domain and traditional terminology relations, typical of thesauri. The tests were conducted using Gene ontology as the knowledge base and MERLOT is used as the test repository. The results of this study case indicate that, at similar levels of precision, expanded queries improve levels of novelty and coverage compared to the original query (without expansion), i.e. expanded queries allow the user to retrieve relevant objects, which might not be obtained without expansion.

Applying Ontology-Based Models for Supporting Integrated Software Development and IT Service Management Processes

Ontologies have been applied in previous research in an attempt to improve software engineering (SE) tools with computational semantics. In addition, ontology models have been applied to model and build supporting tools for IT service management (ITSM) processes, including the formal modeling of service-level agreements. Both the areas of concern share a common upper layer of concepts, as certain software development activities in some cases start from ITSM design needs or tasks. This suggests that existing ontologies in both domains can be integrated, thus resulting in enhanced semantic-aware process support tools, which crosscut the two concern areas. This paper reviews existing ontology-based models in the SE and ITSM domains and describes the main elements of a mapping that enables their integration. Several concrete cases in which that integration results in adding value to the processes are reported. A case study that adopts the approach is also described.

Comparing impact factors from two different citation databases: The case of Computer Science

Journal impact factors continue to play an important role in research output assessment, in spite of the criticisms and debates around them. The impact factor rankings provided in the Journal Citation Reports (JCR™) database by Thompson Reuters have enjoyed a position of monopoly for many years. But this has recently changed with the availability of the Scopus™ database and its associated journal ranking published in the Scimago Journal Rank (SJR) Web page, as the former provides a citation database with similar inclusion criteria to those used in the JCR and the latter and openly accessible impact factor-based ranking. The availability of alternatives to the JCR impact factor listings using a different citation database raises the question of the extent to which the two rankings can be considered equally valid for research evaluation purposes. This paper reports the results of a contrast of both listings in Computer Science-related topics. It attempts to answer the validity question by comparing the impact factors of journals ranked in both listings and their relative position. The results show that impact factors for journals included in both rankings are strongly correlated, with SJR impact factors in general slightly higher, confirming previous studies related to other disciplines. Nonetheless, the consideration of tercile and quartile position of journal yields some divergences for journals appearing in both rankings that need to be accounted for in research evaluation procedures.

Semantic annotation of video fragments as learning objects: a case study with YouTube videos and the Gene Ontology

Web 2.0 technologies can be considered a loosely defined set of Web application styles that foster a kind of media consumer more engaged, and usually active in creating and maintaining Internet contents. Thus, Web 2.0 applications have resulted in increased user participation and massive user-generated (or user-published) open multimedia content, some of which is potentially useful for education. In this context, the problem from the educators perspective is selecting and annotating existing content so that software applications can filter fragments that were previously marked as useful for particular learning needs. This article discusses a solution for this problem that is non-intrusive to existing applications. This solution fits in the philosophy of multiple metadata profiles, allows for expressing fine-grained learning needs, and leverages the growing mass of contents by reusing well-established domain ontologies. A description of the technical aspects required for the infrastructure supporting such solution is first provided. Then, the solution is contextualized with a case study using a knowledge model of gene-related elements – the Gene Ontology – to semantically annotate videos in YouTube that could be used in teaching biology and bioinformatics.

Making use of upper ontologies to foster interoperability between SKOS concept schemes

The SKOS (Simple Knowledge Organization System) Core is a model for representing thesauri and similar types of knowledge organization systems as RDF graphs. Although it provides a basic framework for building concept schemes, SKOS does not carry the strictly defined semantics of formal ontology languages and thus has a number of shortcomings to fully port existing schemes to the Semantic Web. This paper introduces a mapping of SKOS metadata to an ontology-based intermediate model, whose main aim is to foster the semantic interoperability of different concept schemes. It has been achieved through the introduction of a common ground for the definition of concepts, based on the use of shared definitions already included in widely-used upper ontologies. This effort makes use of an upper ontology in particular: OpenCyc, the open source version of Cyc, which is currently one of the most complete general knowledge bases.Purpose – The purpose of this research is to introduce a mapping of the Simple Knowledge Organization Systems (SKOS) Core metadata to an ontology‐based model, whose main aim is to foster the semantic interoperability of different concept schemes.Design/methodology/approach – Research objectives have been achieved through the introduction of a common ground for the definition of concepts, based on shared definitions included in widely used upper ontologies. This effort makes use of a particular upper ontology: OpenCyc, the open source version of Cyc, which is currently one of the most complete general knowledge bases.Findings – An in‐depth study of the SKOS vocabulary has suggested its extension, with the aim of correcting the shortcomings related with SKOS schemes semantic interoperability. However, although such an extension would help avoid ambiguities and enable inter‐thesaurus interoperability, the paper is focused on using a non‐invasive contribution. Non‐invasive in that the SKOS Core should not be ...