Norbert Luttenberger’s research while affiliated with Kiel University and other places

Trade classifications are a necessary prerequisite for the compilation of trade statistics, and they should – beyond that – be regarded as a valuable base for the definition of shared controlled vocabularies for linked business data that deal with import, export etc. The Standard International Trade Classification (SITC) provided by the UN Statistics Division is a widely used classification mostly applied for scientific and analytical purposes. SITC – as most other trade classifications – is available today only in text or spreadsheet formats. These formats reveal the inner hierarchical structure of SITC to the human reader, because SITC trade codes are built according to the decimal classification scheme, but unfortunately, SITC’s inner structure is opaque to computer applications in text and spreadsheet formats. The paper discusses an approach to set up an OWL-2 ontology for SITC that states subsumption relations between classes of goods. This kind of semantic underpinning of SITC is suited to ease both checking and extending SITC and to derive from it a shared controlled vocabulary for business linked data. Some problems of today’s SITC (among them missing inner nodes of the trade code hierarchy) are carefully discussed, and the paper motivates several decisions that were taken for ontology design. Finally, the study introduces the semantic reasoner as a tool for the (at least partial) automatic derivation of structural information for SITC from the trade code building rule. The paper reports on reasoner runtimes observed for different versions of the SITC ontology and for different versions of the Pellet reasoner.

The transcription of highly-structured source documents like registers, tables and the like is a common task in many Digital Humanities projects. Often, it is the goal to reconstruct evenly structured records from the "entries" in such documents, such that these records can be processed by automatic algorithms. Entries in highly-structured source documents may contain text fragments that must for various reasons be transcribed by human editors, and other text fragments that use a limited vocabulary and thus lend themselves for dictionary-enhanced Optical Character Recognition (OCR). In this paper, we present an algorithm that allows us to combine partial entries that were transcribed by human editors with left-over information from the same entries that are provided by our ENRICHER algorithm. Two main problems had to be solved: the correct OCR-based detection of entries in highly-structured documents and the assignment of ENRICHER-generated information to human-transcribed partial entries. To evaluate the ENRICHER algorithm, we conducted a case study comprising several experiments with approx. 25,000 entries from the Germany WW1 casualty lists, which have poor visual quality and are printed in an old-fashioned font. The evaluation showed a recall of up to 0.922 and a precision of up to 0.97. We consider this as a valid proof for the overall quality of our approach.

In this paper we present the evaluation of a collaborative transcription project: Volunteers transcribed the German WW1 casualty lists (31,000 newspaper-format pages, 8.5 million entries) in a 32-month effort using the "Data Entry System" (CG-DES). CG-DES has an easy-to-use browser-based interface that heavily contributed to the motivation of approx. 700 volunteers. We characterize volunteer behavior patterns based on observations collected during CG-DES operation time. We discuss several hypotheses and underpin these hypotheses with our statistic data.

Identifying and referencing places is important for many fields of research. Very different approaches of how to represent administrative structures on the Semantic Web can be found. This survey attempts to provide a broad overview of systems that work on (historic) administrative information. We present a classification for such systems, with special attention to the difference that arise from the processing of historic data. We also describe a sample of systems which approach the problem in very different ways. We conclude by evaluating which of the presented characteristics make a system universal and future-proof.

We present an approach for modeling, verification and debugging of railway infrastructures. The aim of this work is to improve the planning process of new railway lines. We define a set of OWL ontologies for describing the static interrelations of railway tracks and safety elements. Planning instructions-so far available in natural language only-are formally modeled by SWRL rules. The Open World Assumption underlying OWL makes it difficult to perform ontology debugging. Therefore, the concept of Semantic Constraints-based on a dynamic rule composition process-is developed.

The ISO 19103 standard - defining rules and guidelines for conceptual modeling in the geographic domain - has deliberately chosen the Unified Modeling Language (UML) as "conceptual schema language" for geographic information systems. From today's perspective - i.e. when taking into account today's mature semantic web technology - another language might also be envisioned as language for specifying application-oriented conceptual models, namely the Web Ontology Language OWL 2. Both language definitions refer to comparable meta-models laid down in terms of OMG's Meta Object Facility, but in contrast to UML, OWL\,2 is fully built upon formal logic which allows logical reasoning on OWL 2 ontologies. In this paper, we investigate language similarities and differences by specifying and implementing the transformation on the meta-model level using the QVT transformation language.

"A child's year of birth is always greater than the year of birth of its parents." - it is not easily possible to code this simple knowledge into a pure OWL ontology, i.e. without using any additional rule languages. Therefore it is not easy in OWL to detect semantic violations in this kind of statements. The two challenges are putting two orders ("greater" and "parent") into relation and representing integers as individuals allowing a reasoner to infer knowledge about the ``greater'' relation. In the first part of this contribution we show a pattern for putting two transitive and asymmetric orders into a relation, such that conflicting information results in an inconsistent ontology. In the second part we present a pattern for expressing integers using their binary code. Due to the special construction a reasoner can infer knowledge about the relation between all integers in the ontology. By combining the two patterns we are able to represent the initial statement in an ontology.