Erik Mannens

XML to RDF Conversion: A Generic Approach

The role of metadata is gaining importance due to todays growth of multimedia content. Currently, XML is the standard for data interchange. However, as XML Schemas do not express semantics but rather the document structure, there is a lack of semantic interoperability regarding current (XML-based) metadata standards. By using semantic Web technologies, ontologies can be created to describe the semantics of a particular metadata format. A problem is that the existing XML data (compliant with a particul.ar metadata format) cannot be used by an ontology, implying the need for a conversion of XML data to RDF instances. In this paper, a generic approach is proposed for the transformation of XML data into RDF instances in an ontology-dependent way. By means of a mapping document, the link is described between an XML Schema (describing the structure of particular XML data) and an OWL ontology. Our approach is illustrated by applying it to the DIG35 specification, which is an XML-based metadata standard for the description of digital images.

Enabling context-aware multimedia annotation by a novel generic semantic problem-solving platform

Automatic generation of metadata, facilitating the retrieval of multimedia items, potentially saves large amounts of manual work. However, the high specialization degree of feature extraction algorithms makes them unaware of the context they operate in, which contains valuable and often necessary information. In this paper, we show how Semantic Web technologies can provide a context that algorithms can interact with. We propose a generic problem-solving platform that uses Web services and various knowledge sources to find solutions to complex requests. The platform employs a reasoner-based composition algorithm, generating an execution plan that combines several algorithms as services. It then supervises the execution of this plan, intervening in case of errors or unexpected behavior. We illustrate our approach by a use case in which we annotate the names of people depicted in a photograph.

NinSuna: a fully integrated platform for format-independent multimedia content adaptation and delivery using Semantic Web technologies

The current multimedia landscape is characterized by a significant heterogeneity in terms of coding and delivery formats, usage environments, and user preferences. The main contribution of this paper is a discussion of the design and functioning of a fully integrated platform for multimedia adaptation and delivery, called NinSuna. This platform is able to efficiently deal with the aforementioned heterogeneity in the present-day multimedia ecosystem, thanks to the use of format-agnostic adaptation engines (i.e., engines independent of the underlying coding format) and format-agnostic packaging engines (i.e., engines independent of the underlying delivery format). Moreover, NinSuna also provides a seamless integration between metadata standards and adaptation processes. Both our format-independent adaptation and packaging techniques rely on a model for multimedia bitstreams, describing the structural, semantic, and scalability properties of these multimedia streams. News sequences were used as a test case for our platform, enabling the user to select news fragments matching his/her specific interests and usage environment characteristics.

Automatic discovery of high-level provenance using semantic similarity

As interest in provenance grows among the Semantic Web community, it is recognized as a useful tool across many domains. However, existing automatic provenance collection techniques are not universally applicable. Most existing methods either rely on (low-level) observed provenance, or require that the user discloses formal workflows. In this paper, we propose a new approach for automatic discovery of provenance, at multiple levels of granularity. To accomplish this, we detect entity derivations, relying on clustering algorithms, linked data and semantic similarity. The resulting derivations are structured in compliance with the Provenance Data Model (PROV-DM). While the proposed approach is purposely kept general, allowing adaptation in many use cases, we provide an implementation for one of these use cases, namely discovering the sources of news articles. With this implementation, we were able to detect 73% of the original sources of 410 news stories, at 68% precision. Lastly, we discuss possible improvements and future work.

Evaluating the success of vocabulary reconciliation for cultural heritage collections

The concept of Linked Data has made its entrance in the cultural heritage sector due to its potential use for the integration of heterogeneous collections and deriving additional value out of existing metadata. However, practitioners and researchers alike need a better understanding of what outcome they can reasonably expect of the reconciliation process between their local metadata and established controlled vocabularies which are already a part of the Linked Data cloud. This paper offers an in-depth analysis of how a locally developed vocabulary can be successfully reconciled with the Library of Congress Subject Headings (LCSH) and the Arts and Architecture Thesaurus (AAT) through the help of a general-purpose tool for interactive data transformation (OpenRefine). Issues negatively affecting the reconciliation process are identified and solutions are proposed in order to derive maximum value from existing metadata and controlled vocabularies in an automated manner.

Semantic patient information aggregation and medicinal decision support

Although the health care sector has already been subjected to a major computerization effort, this effort is often limited to the implementation of standalone systems which do not communicate with each other. Interoperability problems limit health care applications from achieving their full potential. In this paper, we propose the use of Semantic Web technologies to solve interoperability problems between data providers. Through the development of unifying health care ontologies, data from multiple health care providers can be aggregated, which can then be used as input for a decision support system. This way, more data is taken into account than a single health care provider possesses in his local setting. The feasibility of our approach is demonstrated by the creation of an end-to-end proof of concept, focusing on Belgian health care providers and medicinal decision support.

Format-independent and metadata-driven media resource adaptation using semantic web technologies

Adaptation of media resources is an emerging field due to the growing amount of multimedia content on the one hand and an increasing diversity in usage environments on the other hand. Furthermore, to deal with a plethora of coding and metadata formats, format-independent adaptation systems are important. In this paper, we present a new format-independent adaptation system. The proposed adaptation system relies on a model that takes into account the structural metadata, semantic metadata, and scalability information of media bitstreams. The model is implemented using the web ontology language. Existing coding formats are mapped to the structural part of the model, while existing metadata standards can be linked to the semantic part of the model. Our new adaptation technique, which is called RDF-driven content adaptation, is based on executing SPARQL Protocol and RDF Query Language queries over instances of the model for media bitstreams. Using different criteria, RDF-driven content adaptation is compared to other adaptation techniques. Next to real-time execution times, RDF-driven content adaptation provides a high abstraction level for the definition of adaptations and allows a seamless integration with existing semantic metadata standards.

Automatic metadata enrichment in news production

News production is characterized by complex and dynamic workflows in which it is important to produce and distribute news items as fast as possible. In this paper, we show how personalized distribution and consumption of news items can be enabled by automatically enriching news metadata with open linked datasets available on theWeb of data, thus providing a more pleasant experience to fastidious consumers where news content is presented within a broader historical context. Further we present a faceted browser that provides a convenient way for exploring news items based on an ontology of NewsML-G2 and rich semantic metadata.

Assessing and Refining Mappingsto RDF to Improve Dataset Quality

rdf dataset quality assessment is currently performed primarily after data is published. However, there is neither a systematic way to incorporate its results into the dataset nor the assessment into the publishing workflow. Adjustments are manually ---but rarely--- applied. Nevertheless, the root of the violations which often derive from the mappings that specify how the rdf dataset will be generated, is not identified. We suggest an incremental, iterative and uniform validation workflow for rdf datasets stemming originally from semi-structured datai¾?e.g., csv, xml, json. In this work, we focus on assessing and improving their mappings. We incorporate ii¾?a test-driven approach for assessing the mappings instead of the rdf dataset itself, as mappings reflect how the dataset will be formed when generated;i¾?and iii¾?perform semi-automatic mapping refinementsbased on the results of the quality assessment. The proposed workflow is applied to diverse cases, e.g., large, crowdsourced datasets such as dbpedia, or newly generated, such as iLastic. Our evaluation indicates the efficiency of our workflow, as it significantly improves the overall quality of an rdf dataset in the observed cases.

Distributed affordance: an open-world assumption for hypermedia

Hypermedia links and controls drive the Web by transforming information into affordances through which users can choose actions. However, publishers of information cannot predict all actions their users might want to perform and therefore, hypermedia can only serve as the engine of application state to the extent the users intentions align with those envisioned by the publisher. In this paper, we introduce distributed affordance, a concept and architecture that extends application state to the entire Web. It combines information inside the representation with knowledge of action providers to generate affordance from the users perspective. Unlike similar approaches such as Web Intents, distributed affordance scales both in the number of actions and the number of action providers, because it is resource-oriented instead of action-oriented. A proof-of-concept shows that distributed affordance is a feasible strategy on todays Web.