Linked Data offers an entity-based infrastructure to resolve indirect relations between resources, expressed as chains of links. If we could benchmark how effective retrieving chains of links from these sources is, we can motivate why they are a reliable addition for exploratory search interfaces. A vast number of applications could reap the benefits from encouraging insights in this field. Especially all kinds of knowledge discovery tasks related for instance to adhoc decision support and digital assistance systems. In this paper, we explain a benchmark model for evaluating the effectiveness of associating chains of links with keyword-based queries. We illustrate the benchmark model with an example case using academic library and conference metadata where we measured precision involving targeted expert users and directed it towards search effectiveness. This kind of typical semantic search engine evaluation focusing on information retrieval metrics such as precision is typically biased towards the final result only. However, in an exploratory search scenario, the dynamics of the intermediary links that could lead to potentially relevant discoveries are not to be neglected.

In this work we introduce necessary steps and planned actions for implementation of analytical application with purpose on analyzing and visualizing information gathered by tracking user behavior and actions in our educational system called Personal Learning Environment (PLE). Furthermore we present a novel Semantic Web driven approach, for modeling of learning and activity based context using eligible domain specific ontologies, as well as for retrieving modeled data depending on the value of interests demonstrated by learner himself. We intend on closing the learning analytic cycle [Clo12] for PLE and for that purpose we are defining the requirements and implementation steps of analytic dashboard which shall give us necessary knowledge for improvement.

Enterprise search is a growing industry: A recent report from the EU states the total revenue of EU-headquartered search vendors between 100 and 200 million Euros. However, enterprise search seems to be widely ignored by the academic information systems (IS) community. Little is known about user-adoption aspects of enterprise search, as almost no academic case studies and very few user evaluations are reported, leaving the topic more or less in hand of practitioners. A preliminary literature review reveals enterprise search user-aspects and especially perceived overall helpfulness as under-investigated subjects. The following paper provides insights into a qualitative study involving ten engineers from automotive and rail industry. While observing them using a piloted enterprise search engine, the authors report qualitative findings on how engineers apply enterprise search on project-relevant documents. With this paper, the authors want to contribute to the user-centered investigation of enterprise search and intranet search behavior and highlight the importance of scientific user studies in enterprise search.

Resources for research are not always easy to explore, and rarely come with strong support for identifying, linking and selecting those that can be of interest to scholars. In this work we introduce a model that uses state-of-the-art semantic technologies to interlink structured research data and data from Web collaboration tools, social media and Linked Open Data. We use this model to build a platform that connects scholars, using their profiles as a starting point to explore novel and relevant content for their research. Scholars can easily adapt to evolving trends by synchronizing new social media accounts or collaboration tools and integrate then with new datasets. We evaluate our approach by a scenario of personalized exploration of research repositories where we analyze real world scholar profiles and compare them to a reference profile.

Fahrzeugentwicklung ist eine wissensintensive Tätigkeit, die optimale Zusammenarbeit über Disziplin-, Abteilungsund Unternehmensgrenzen erfordert. Gerade deswegen ist der möglichst effektive Zugang zu Information und Wissen ein wesentlicher Erfolgsfaktor. Der Einsatz flexibler und intelligenter Technologie für die Suche und Vernetzung von Information für Entwickler kann ein möglicher Ansatz sein, wie sich der Zugang zu Informationen verbessern lässt. Im folgenden Beitrag werden Ergebnisse aus einem gemeinsam mit drei Automobilherstellern und einem großen Zulieferer gestarteten Forschungsprojekt vorgestellt, welches ein Informationscockpit für Fahrzeugentwickler zum Ziel hat. In rund 50 Gesprächen mit Fahrzeugentwicklern wurde der Status Quo der Informationsbeschaffung in erste Anforderungen für ein Informationscockpit bei den Projektpartnern erhoben. Auf Basis vorab definierter Projektziele sowie der erhobenen, erweiterten, abgestimmten und verfeinerten Anforderungen der Fahrzeugentwickler wurde eine erste Architektur erstellt, welche gemeinsam mit den Ergebnissen der Gespräche in diesem Beitrag präsentiert wird. Aufgrund stringenter Bedingungen hinsichtlich Geheimhaltung in der Fahrzeugentwicklung bei den Projektpartnern, kann nur ein Ausschnitt in diesem Beitrag im Detail vorgestellt werden.

We report on the reflection of learning activities and revealing hidden information based on tracking user behaviors with Linked Data. Within this work we introduce a case study on usage of semantic context modelling and creation of Linked Data from logs in educational systems like a Personal Learning Environment (PLE) with focus on reflection and prediction of trends in such systems. The case study demonstrates the application of semantic modelling of the activity context, from data collected for over two years from our own developed widget based PLE at Graz University of Technology. We model learning activities using adequate domain ontologies, and query them using semantic technologies as input for visualization which serves as reflection and prediction medium as well for potential technical and functional improvements like widget recommendations. As it will be shown, this approach offers easy interfacing and extensibility on technological level and fast insight on trends in e-learning systems like PLE.

In this work we examined whether OntoWiki 1 can be used as collaborative working tool for engineers. We used a specific domain related ontology PROTARES (PROject TAsks RESources) 2 , created in our previous work on collaboration modelling (Softic et al. 2013) from a real world use case, to adapt OntoWiki for the case study. With this example we want to test to which extent, semantically driven customized applications can support monitoring, reflection and decision making in engineering collaboration scenario.

Nowadays, product development in automotive industry is a distributed process which involves a variety of participants with different roles. Intensive changes on product need a high communication effort, which is still carried out in face to face meetings and does not interact directly with engineering artifacts affected by these decisions. Our work aims to overcome this problem by offering a collaborative working tool which enables flexible management of information about collaboration and supports decision-making within collaborative working environment of the automotive product development.

Research information is widely available on the Web. Both as peer-reviewed research publications or as resources shared via (micro) blogging platforms or other Social Media. Usually the platforms supporting this information exchange have an API that allows access to the structured content. This opens a new way to search and explore research information. In this paper, we present an approach that visualizes interactively an aligned knowledge base of these resources. We show that visualizing resources, such as conferences, publications and proceedings, expose affinities between researchers and those resources. We characterize each affinity, between researchers and resources, by the amount of shared interests and other commonalities.

Stakeholders in specific disciplines, departments, companies and at different locations within the automotive production process save their results in different data management systems. Project management is currently done separately and does not interact with engineering objects. Our work aims on providing flexible data insights on collaboration tasks between participants within the product lifecycle. We applied semantic technologies RDF, OWL and SPARQL with a specific domain related ontology PROTARES (PROject TAsks RESources) to interlink, describe and query domain knowledge about the product. As proof of concept a software prototype is introduced, which resides on the domain ontology and allows knowledge based browsing and visualisation of specific aspects within the production process. With this example we want to demonstrate, how semantically driven customized views can support monitoring and reflection of engineering tasks and decision making within the early phases of the automotive product lifecycle.