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Forschungs- und Lehrbericht 2013/2014 Fachbereich 4: Informatik Universität Koblenz-Landau (2015)

Der Fachbereich 4 (Informatik) besteht aus fünfundzwanzig Arbeitsgruppen unter der Leitung von Professorinnen und Professoren, die für die Forschung und Lehre in sechs Instituten zusammenarbeiten. In jedem Jahresbericht stellen sich die Arbeitsgruppen nach einem einheitlichen Muster dar, welche personelle Zusammensetzung sie haben, welche Projekte in den Berichtszeitraum fallen und welche wissenschaftlichen Leistungen erbracht wurden. In den folgenden Kapiteln werden einzelne Parameter aufgeführt, die den Fachbereich in quantitativer Hinsicht, was Drittmitteleinwerbungen, Abdeckung der Lehre, Absolventen oder Veröffentlichungen angeht, beschreiben.

Categorising Social Media Business Risks (2014)

Hausmann, Verena ; Williams, Susan P.

The aim of this paper is to identify and understand the risks and issues companies are experiencing from the business use of social media and to develop a framework for describing and categorising those social media risks. The goal is to contribute to the evolving theorisation of social media risk and to provide a foundation for the further development of social media risk management strategies and processes. The study findings identify thirty risk types organised into five categories (technical, human, content, compliance and reputational). A risk-chain is used to illustrate the complex interrelated, multi-stakeholder nature of these risks and directions for future work are identified.

Entwicklung eines ganzheitlichen Modells der Absorptive Capacity (2014)

Meininger, Christian ; Zerwas, Dorothée ; Korflesch, Harald F. O. von ; Bertram, Matthias

Im Laufe der letzten Jahre hat sich der typische Komplex an kritischen Erfolgsfaktoren für Unternehmen verändert, infolgedessen der Faktor Wissen eine wachsende Bedeutung erlangt hat. Insofern kann man zum heutigen Zeitpunkt von Wissen als viertem Produktionsfaktor sprechen, welcher die Faktoren Arbeit, Kapital und Boden als wichtigste Faktoren eines Unternehmens ablöst (vgl. Keller & Yeaple 2013, S. 2; Kogut & Zander 1993, S. 631). Dies liegt darin begründet, dass aktive Maßnahmen zur Unterstützung von Wissenstransfer in Unternehmen höhere Profite und Marktanteile sowie bessere Überlebensfähigkeit gegenüber Wettbewerbern ohne derartige Maßnahmen nach sich ziehen (vgl. Argote 1999, S. 28; Szulanski 1996, S. 27; Osterloh & Frey 2000, S. 538). Der hauptsächliche Vorteil von wissensbasierten Entwicklungen liegt dabei in deren Nachhaltigkeit, da aufgrund der immateriellen Struktur (vgl. Inkpen & Dinur 1998, S. 456; Spender 1996a, S. 65 f.; Spender 1996b, S. 49; Nelson & Winter 1982, S. 76 ff.) eine Nachahmung durch Wettbewerber erschwert wird (vgl. Wernerfelt 1984, S. 173; Barney 1991, S. 102).

Micro Modelling of User Perception and Generation Processes for Macro Level Predictions in Online Communities (2014)

Schwagereit, Felix ; Gottron, Thomas ; Staab, Steffen

The way information is presented to users in online community platforms has an influence on the way the users create new information. This is the case, for instance, in question-answering fora, crowdsourcing platforms or other social computation settings. To better understand the effects of presentation policies on user activity, we introduce a generative model of user behaviour in this paper. Running simulations based on this user behaviour we demonstrate the ability of the model to evoke macro phenomena comparable to the ones observed on real world data.

Extended Description of the Survey on Common Strategies of Vocabulary Reuse in Linked Open Data Modeling (2014)

Schaible, Johann ; Gottron, Thomas ; Scherp, Ansgar

Modeling and publishing Linked Open Data (LOD) involves the choice of which vocabulary to use. This choice is far from trivial and poses a challenge to a Linked Data engineer. It covers the search for appropriate vocabulary terms, making decisions regarding the number of vocabularies to consider in the design process, as well as the way of selecting and combining vocabularies. Until today, there is no study that investigates the different strategies of reusing vocabularies for LOD modeling and publishing. In this paper, we present the results of a survey with 79 participants that examines the most preferred vocabulary reuse strategies of LOD modeling. Participants of our survey are LOD publishers and practitioners. Their task was to assess different vocabulary reuse strategies and explain their ranking decision. We found significant differences between the modeling strategies that range from reusing popular vocabularies, minimizing the number of vocabularies, and staying within one domain vocabulary. A very interesting insight is that the popularity in the meaning of how frequent a vocabulary is used in a data source is more important than how often individual classes and properties arernused in the LOD cloud. Overall, the results of this survey help in understanding the strategies how data engineers reuse vocabularies, and theyrnmay also be used to develop future vocabulary engineering tools.

Forschungs- und Lehrbericht 2012/2013 Fachbereich 4: Informatik Universität Koblenz-Landau (2014)

Forschungs- und Lehrbericht 2012/2013, Fachbereich 4: Informatik, Universität Koblenz-Landau

Semantically Guided Evolution of SHI ABoxes (2013)

Furbach, Ulrich ; Schon, Claudia

This paper presents a method for the evolution of SHI ABoxes which is based on a compilation technique of the knowledge base. For this the ABox is regarded as an interpretation of the TBox which is close to a model. It is shown, that the ABox can be used for a semantically guided transformation resulting in an equisatisfiable knowledge base. We use the result of this transformation to effciently delete assertions from the ABox. Furthermore, insertion of assertions as well as repair of inconsistent ABoxes is addressed. For the computation of the necessary actions for deletion, insertion and repair, the E-KRHyper theorem prover is used.

Forschungs- und Lehrbericht 2011/2012 Fachbereich 4: Informatik Universität Koblenz-Landau (2013)

Forschungs- und Lehrbericht 2011/2012, Fachbereich 4: Informatik, Universität Koblenz-Landau

Iterative Signing of RDF(S) Graphs, Named Graphs, and OWL Graphs: Formalization and Application (2013)

Kasten, Andreas ; Scherp, Ansgar

When publishing graph data on the web such as vocabulariesrnusing RDF(S) or OWL, one has only limited means to verify the authenticity and integrity of the graph data. Today's approaches require a high signature overhead and do not allow for an iterative signing of graph data. This paper presents a formally defined framework for signing arbitrary graph data provided in RDF(S), Named Graphs, or OWL. Our framework supports signing graph data at different levels of granularity: minimum self-contained graphs (MSG), sets of MSGs, and entire graphs. It supports for an iterative signing of graph data, e. g., when different parties provide different parts of a common graph, and allows for signing multiple graphs. Both can be done with a constant, low overhead for the signature graph, even when iteratively signing graph data.

LOVER: Support for Modeling Data Using Linked Open Vocabularies (2013)

Gottron, Thomas ; Schaible, Johann ; Scheglmann, Stefan ; Scherp, Ansgar

Various best practices and principles guide an ontology engineer when modeling Linked Data. The choice of appropriate vocabularies is one essential aspect in the guidelines, as it leads to better interpretation, querying, and consumption of the data by Linked Data applications and users. In this paper, we present the various types of support features for an ontology engineer to model a Linked Data dataset, discuss existing tools and services with respect to these support features, and propose LOVER: a novel approach to support the ontology engineer in modeling a Linked Data dataset. We demonstrate that none of the existing tools and services incorporate all types of supporting features and illustrate the concept of LOVER, which supports the engineer by recommending appropriate classes and properties from existing and actively used vocabularies. Hereby, the recommendations are made on the basis of an iterative multimodal search. LOVER uses different, orthogonal information sources for finding terms, e.g. based on a best string match or schema information on other datasets published in the Linked Open Data cloud. We describe LOVER's recommendation mechanism in general and illustrate it alongrna real-life example from the social sciences domain.

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