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Ontologies play an important role in knowledge representation for sharing information and collaboratively developing knowledge bases. They are changed, adapted and reused in different applications and domains resulting in multiple versions of an ontology. The comparison of different versions and the analysis of changes at a higher level of abstraction may be insightful to understand the changes that were applied to an ontology. While there is existing work on detecting (syntactical) differences and changes in ontologies, there is still a need in analyzing ontology changes at a higher level of abstraction like ontology evolution or refactoring pattern. In our approach we start from a classification of model refactoring patterns found in software engineering for identifying such refactoring patterns in OWL ontologies using DL reasoning to recognize these patterns.
Iterative Signing of RDF(S) Graphs, Named Graphs, and OWL Graphs: Formalization and Application
(2013)
When publishing graph data on the web such as vocabulariesrnusing RDF(S) or OWL, one has only limited means to verify the authenticity and integrity of the graph data. Today's approaches require a high signature overhead and do not allow for an iterative signing of graph data. This paper presents a formally defined framework for signing arbitrary graph data provided in RDF(S), Named Graphs, or OWL. Our framework supports signing graph data at different levels of granularity: minimum self-contained graphs (MSG), sets of MSGs, and entire graphs. It supports for an iterative signing of graph data, e. g., when different parties provide different parts of a common graph, and allows for signing multiple graphs. Both can be done with a constant, low overhead for the signature graph, even when iteratively signing graph data.
Currently more than 850 biological databases exist. The majority of biological knowledge is not in these databases but rather contained as free text in scientific literature. For systems biology tasks it is often necessary to integrate and extract data from heterogeneous databases and free text as well as to analyse the information in the context of experimental data. ONDEX is an integration framework which aims to address these challenges by combining features of database integration, text mining and sequence analysis with methods for graph-based data analysis and visualisation. The main topics of this diploma thesis are the redesign of the ONDEX backend, the development of a data exchange format, the development of a query environment and the allocation of Web services for data integration, data exchange and queries. These Web services allow backend workflow control from both local and remote workstations.
SPARQL can be employed to query RDF documents using RDF triples. OWL-DL ontologies are a subset of RDF and they are created by using specific OWL-DL expressions. Querying such ontologies using only RDF triples can be complicated and can produce a preventable source of error depending on each query.
SPARQL-DL Abstract Syntax (SPARQLAS) solves this problem using OWL Functional-Style Syntax or a syntax similar to the Manchester Syntax for setting up queries. SPARQLAS is a proper subset of SPARQL and uses only the essential constructs to obtain the desired results to queries on OWL-DL ontologies implying least possible effort in writing.
Due to the decrease in size of the query and having a familiar syntax the user is able to rely on, complex and nested queries on OWL-DL ontologies can be more easily realized. The Eclipse plugin EMFText is utilized for generating the specific SPARQLAS syntax. For further implementation of SPARQLAS, an ATL transformation to SPARQL is included as well. This transformation saves developing a program to directly process SPARQLAS queries and supports embedding SPARQLAS into running development environments.