Template Based Semantic Integration: From Legacy Archaeological Datasets to Linked Data

The online dissemination of datasets to accompany site monographs and summary documentation is becoming common practice within the archaeology domain. Since the legacy database schemas involved are often created on a per-site basis, cross searching or reusing this data remains difficult. Employing an integrating ontology, such as the CIDOC CRM, is one step towards resolving these issues. However, this has tended to require computing specialists with detailed knowledge of the ontologies involved. Results are presented from a collaborative project between computer scientists and archaeologists that provided light weight tools to make it easier for non-specialists to publish Linked Data. Applications developed for the STELLAR project were applied by archaeologists to major excavation datasets and the resulting output was published as Linked Data, conforming to the CIDOC CRM ontology. The template-based Extract Transform Load method is described. Reflections on the experience of using the template-based tools are discussed, together with practical issues including the need for terminology alignment and licensing consideration

Inspecting Java Program States with Semantic Web Technologies

Semantic debugging, as introduced by Kamburjan et al., refers to the practice of applying technologies of the semantic web to query the run-time state of a program and combine it with external domain knowledge. This master thesis aims to take the first step toward making the benefits of semantic debugging available for real-world application development. For this purpose, we implement a semantic debugging tool for the Java programming language, called the Semantic Java Debugger or sjdb. The sjdb tool provides an interactive, command line-based user interface through which users can (1) run Java programs and suspend their execution at user-defined breakpoints, (2) automatically extract RDF knowledge bases with description logic semantics that describe the current state of the program, (3) optionally supplement the knowledge base with external domain knowledge formalized in OWL, (4) run (semantic) queries on this extended knowledge base, and resolve the query results back to Java objects. As part of this debugging tool, the development of an extraction mechanism for knowledge bases from the states of suspended Java programs is one of the main contributions of this thesis. For this purpose, we also devise an OWL formalization of Java runtime states to structure this extraction process and give meaning to the resulting knowledge base. Moreover, case studies are conducted to demonstrate the capabilities of sjdb, but also to identify its limitations, as well as its response times and memory requirements