Tobias Bürger

Measuring the Benefits of Ontologies

The technical challenges associated with the development and deployment of ontologies have been subject to a number of research initiatives since the beginning of the nineties. By comparison the economics of ontology engineering remains a poorly exploited field, this underdevelopment having an impact on the adoption of ontology-driven technologies beyond the boundaries of the academic community. The work presented in this paper aims at the alleviation of this situation. We introduce a method for measuring the benefits of ontologies based on a multiple gap model for user information satisfaction analysis. Together with cost models such as ONTOCOM, it can be used to give an account of the economic value of ontologies.

ONTOCOM Revisited: Towards Accurate Cost Predictions for Ontology Development Projects

Reliable methods to assess the costs and benefits of ontologies are an important instrument to demonstrate the tangible business value of semantic technologies within enterprises, as an argument to encourage their wide-scale adoption. The economic aspects of ontologies have been investigated in previous work of ours. With ONTOCOM we proposed a cost estimation model for ontologies and ontology development projects. This paper revisits this model and presents its latest achievements. We report on a comprehensive calibration of ONTOCOM based on a considerably larger data set of 148 ontology development projects. The calibration used a combination of statistical methods, ranging from preliminary data analysis to regression and Bayes analysis, and resulted a significant improvement of the prediction quality of up to 50%. In addition, the availability of a representative data set allowed us to identify meaningful directions for customizing the generic cost model along particular types of ontologies, and ontology-like structures as those specific to the emerging Web 3.0. Last but not least, we developed a software tool that allows ontology development project managers to easily use and adapt and to systematically calibrate the model, thus facilitating its adoption in real-world projects.

LMF: A Framework for Linked Media

Multimedia is currently underrepresented in the Web of Data. This is due to the lack of integrated means to describe, publish, and interlink multimedia content. This paper presents a framework for the publication of media content and its metadata as Linked Data, the Linked Media Framework (LMF). The LMF enables to store and retrieve content and metadata for media resources and resource fragments in a unified way.

Combining human and computation intelligence: the case of data interlinking tools

Interlinking is without doubt one of the most active and mature areas of research and development in semantic technologies. Over the last decade or more a multitude of approaches to match, merge and integrate ontologies, both at the schema and instance levels have been proposed and successfully applied to resolve heterogeneity issues and, more recently, to interlink RDF data sets exposed over the Web as part of the Linked Open Data Cloud. The strengths and weaknesses of existing interlinking solutions, as well as their natural limitations and principled combinations have been intensively studied, not least through community projects such as the Ontology Alignment Evaluation Initiative. Human input remains a key ingredient of the process, either as a source of domain knowledge used to train matching algorithms and to build the underlying knowledge base, or to validate automatically computed results. In this paper we describe how such human input could be acquired and used to enhance the results of existing data interlinking technology via crowdsourcing. In a survey of data interlinking tools we identify several aspects of the interlinking process that crucially rely on human contributions and explain how these aspects could be subject to a semantically enabled human computation architecture that can be set-up by extending interlinking platforms such as Silk with direct interfaces to popular microtask platforms such as Amazons Mechanical Turk.

Linked Data and multimedia: the state of affairs

Linked Data is a way of exposing and sharing data as resources on the Web and interlinking them with semantically related resources. In the last three years significant amounts of data have been generated, increasingly forming a globally connected, distributed data space. For multimedia content, metadata are a key factor for efficient management, organization, and retrieval. However, the relationship between multimedia and Linked Data has been rarely studied, leading to a lack of mutual awareness and, as a consequence thereof, technological deficiencies. This article introduces the basic concepts of Linked Data in the context of multimedia metadata, and discusses techniques to generate, expose, discover, and consume Linked Data. It shows that a large amount of data sources exist, which are ready to be exploited by multimedia applications. The benefit of Linked Data in two multimedia-related applications is discussed and open research issues are outlined with the goal of bringing the research fields of multimedia and Linked Data closer together in order to facilitate mutual benefit.

ONTOCOM: A reliable cost estimation method for ontology development projects

We present ONTOCOM, a method to estimate the costs of ontology engineering, as well as project management tools that support the application of the method. ONTOCOM is part of a broader framework we have developed over the five years, whose aim is to assess the business value of semantic technologies through a suite of methods, estimation models and project management tools, by which the costs and benefits of the corresponding projects are defined, measured and analyzed. The framework supports the engineering of different types of knowledge structures, including ontologies, taxonomies and folksonomies, and of information management systems leveraging such knowledge structures. It also includes benefit analysis models whose results can be used in conjunction with cost-related information in order to identify potential cost savings and to assess the feasibility of specific engineering strategies, in particular ontology reuse. The application of the methods proposed in the framework is supported by project management tools which can be used to customize these methods to a given project environment, to evaluate and validate the underlying estimations using empirical data, and to take into account their results for planning and controlling purposes.

Achieving Maturity: The State of Practice in Ontology Engineering in 2009

In this paper we give an account of the current state of practice in ontology engineering (OE) based on the findings of a 6 months empirical survey that analyzed 148 OE projects. The survey focused on process-related issues and looked into the impact of research achievements on real-world OE projects, the complexity of particular ontology development tasks, the level of tool support, and the usage scenarios for ontologies. The main contributions of this survey are twofold: 1) the size of the data set is larger than every other similar endeavor; 2) the findings of the survey confirm that OE is an established engineering discipline w.r.t the maturity and level of acceptance of its main components, methodologies, etc. whereas further research should target economic aspects of OE and the customization of existing technology to the specifics of vertical domains.

Smart content factory: assisting search for digital objects by generic linking concepts to multimedia content

Search, retrieval and navigation in audiovisual repositories is a task common to all media asset management systems: Users are supported by a wide range of features which are traditionally based on full text search and metadata queries. In this paper we describe an approach to superimpose a semantic indexing infrastructure over the media assets and the metadata associated with them. The infrastructure is based on formal knowledge models and facilitates the use of further navigation dimensions: By identifying semantic concepts we are able to create a dynamic navigation structure which is based on the underlying knowledge model and the conceptual relations defined therein.

Framework for Value Prediction of Knowledge-Based Applications

Knowledge-based applications are characterized by their use of machine-understandable formalizations of expert knowledge. Complex knowledge structures, and the features which exploit them, can have a significant effect on the effort needed to develop such applications. Means to estimate this effort are, however, lacking. Furthermore, precise benefits of such applications, which are directly attributed to specific functionalities, remain unknown.

A novel system for interactive live TV

For the production of interactive live TV formats, new content and new productions workflows are necessary. We explain how future content of a parallel multi-stream production of live events may be created from a design and a technical perspective. It is argued, that the content should be arranged by dramaturgical principles taking into account the meaning of the base material. To support the production process a new approach for content recommendation is described which uses semantic annotation from audio-visual material and user feedback.