Contributions published at Dynamic and Distributed Information Systems (Abraham Bernstein)

Modern software development has become a complex task. Software systems grow larger and are densely interconnected to other systems making excessive use of large communication frameworks. To cope with this complexity, software developers and project managers need the assistance of tools which extract information about flaws in code as well as general information about the state of a project. In this thesis, we first introduce a data exchange format based on OWL/RDF, the Semantic Web’s format of choice today, able to store data and meta data from the source code, versioning system (i.e. CVS) and bug tracking system (i.e. Bugzilla). In a next step, we present a tool to retrieve the data from the online software repositories and to store it in OWL/RDF. This tool is implemented as a plug-in for the Eclipse IDE and is able to harvest data from projects managed by Eclipse. Finally, we evaluated our data format and tools by applying a set of software metric calculations, pattern detections and similarity measures by using iSPARQL and SimPack. The results of the conducted experiments are promising, and gave a first proof of our approach.

Natural language interfaces offer end-users a familiar and convenient option for querying ontology-based knowledge bases. Several studies have shown that they can achieve high retrieval performance as well as domain independence. This paper focuses on usability and investigates if NLIs are useful from an end-user's point of view. To that end, we introduce four interfaces each allowing a different query language and present a usability study benchmarking these interfaces. The results of the study reveal a clear preference for full sentences as query language and confirm that NLIs are useful for querying Semantic Web data.

This research explores three SPARQL-based techniques to solve Semantic Web tasks that often require similarity measures, such as semantic data integration, ontology mapping, and Semantic Weg service matchmaking. Our aim is to see how far it is possible to integrate customized similarity functions (CSF) into SPARQL to achieve good results for these tasks. Our first approach exploits virtual triples calling property functions to establish virtual relations among resources under comparison; the second approach uses extension functions to filter out resources that do not meet the requested similarity criteria; finally, our third technique applies new solution modifiers to post-process a SPARQL solution sequence. The semantics of the three approaches are formally elaborated and discussed. We close the paper with a demonstration of the usefulness of our iSPARQL framework in the context of a data integration and an ontology mapping experiment.

Traditional process support systems typically offer a static composition of atomic tasks to more powerful services. In the real world, however, processes change over time: business needs are rapidly evolving thus changing the work itself and relevant information may be unknown until workflow execution run-time. Hence, the static approach does not sufficiently address the need for dynamism. Based on applications in the life science domain this paper puts forward five requirements for dynamic process support systems. These demand a focus on a tight user interaction in the whole process life cycle. The system and the user establish a continuous feedback loop resulting in a mixed-initiative approach requiring a partial execution and resumption feature to adapt a running process to changing needs. Here we present our prototype implementation NExT and discuss a preliminary validation based on a real-world scenario.

One of the most important decisions researchers face when analyzing the evolution of software systems is the choice of a proper data analysis/exchange format. Most existing formats have to be processed with special programs written specifically for that purpose and are not easily extendible. Most scientists, therefore, use their own database(s) requiring each of them to repeat the work of writing the import/export programs to their format. We present EvoOnt, a software repository data exchange format based on the Web Ontology Language (OWL). EvoOnt includes software, release, and bug-related information. Since OWL describes the semantics of the data, EvoOnt is (1) easily extendible, (2) comes with many existing tools, and (3) allows to derive assertions through its inherent Description Logic reasoning capabilities. The paper also shows iSPARQL – our SPARQL-based Semantic Web query engine containing similarity joins. Together with EvoOnt, iSPARQL can accomplish a sizable number of tasks sought in software repository mining projects, such as an assessment of the amount of change between versions or the detection of bad code smells. To illustrate the usefulness of EvoOnt (and iSPARQL), we perform a series of experiments with a real-world Java project. These show that a number of software analyses can be reduced to simple iSPARQL queries on an EvoOnt dataset.

The vision of semantic business processes is to enable the integration and inter-operability of business processes across organizational boundaries. Since different organizations model their processes differently, the discovery and retrieval of similar smantic business processes is necessary in order to foster inter-organi ational collaborations. This paper presents our approach of using iSPARQL � our imprecise query engine based on SPARQL � to query the OWL MIT Process Handbook � a large collection of over 5000 semantic business processes. We particularly show how easy it is to use iSPARQL to perform the presented process retrieval task. Furthermore, since choosing the best performing similarity strategy is a non-trivial, data-, and context-dependent task, we evaluate the performance of three simple and two human-engineered similarity strategies. In addition, we conduct machine learning experiments to learn similarity measures showing that complementary information contained in the different notions of similarity strategies provide a very high retrieval accuracy. Our preliminary results indicate that iSPARQL is indeed useful for extending the reach of queries and that it, therefore, is an enabler for inter- and intra-organizational collaborations.

This thesis explores a novel approach to use techniques found in Case-based Reasoner Systems and apply them to the Semantic Web. In the context of the Web Service Ontology OWL-S, a framework following the principles of Case-based Reasoning is introduced. A suitable case structure is defined that builds the basis of the system. Furthermore, various similarity strategies are implemented to determine the appropriate selection of suitable cases based on the novel problem presented to the system. Similarity is measured using semantic, syntactic and graph measurements. Additionally, different adaption strategies are introduced to facilitate the reuse process. The framework's architecture allows for custom extension of additional similarity and adaption strategies in the future.

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This poster describes three static SPARQL optimization approaches for in-memory RDF graphs: (1) a selectivity estimation index (SEI) for single query triple patterns; (2) a query pattern index (QPI) for joined triple patterns; and (3) a hybrid optimization approach that combines both indexes. Using the Lehigh University Benchmark (LUBM), we show that the hybrid approach outperforms other SPARQL query engines such as ARQ and Sesame for in-memory graphs.

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Can we predict locations of future refactoring based on the development history? In an empirical study of open source projects we found that attributes of software evolution data can be used to predict the need for refactoring in the following two months of development. Information systems utilized in software projects provide a broad range of data for decision support. Versioning systems log each activity during the development, which we use to extract data mining features such as growth measures, relationships between classes, the number of authors working on a particular piece of code, etc. We use this information as input into classification algorithms to create prediction models for future refactoring activities. Different state-of-the-art classifiers are investigated such as decision trees, logistic model trees, propositional rule learners, and nearest neighbor algorithms. With both high precision and high recall we can assess the refactoring proneness of object-oriented systems. Although we investigate different domains, we discovered critical factors within the development life cycle leading to refactoring, which are common among all studied projects.

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In diesem Paper wird eine Auszeichnungssprache für multimediale und modularisierte Fallstudien, die in der Wirtschaftsinformatik-Lehre eingesetzt werden, vorgestellt. Während die meisten Fallstudien für eine spezifische Lehr-Lernsituation geschrieben sind, sollen die Fallstudien, wie sie hier beschrieben werden, flexibel und modular für verschiedene Aufgabenstellungen und in unterschiedlichen Lehr-Lern- Szenarien einsetzbar sein. Hierfür ist eine flexible Darstellung der Fallstudien notwendig; sie kann durch die von uns entwickelte Auszeichnungssprache CaseML sicherge- stellt werden.

Query engines for ontological data based on graph models mostly execute user queries without considering any optimization. Especially for large ontologies, optimization techniques are required to ensure that query results are delivered within reasonable time. OptARQ is a first prototype for SPARQL query optimization based on the concept of triple pattern selectivity estimation. The evaluation we conduct demonstrates how triple pattern reordering according to their selectivity affects the query execution performance.

While moving in unknown environments mankind has been relying for thousands of years on the art of navigation. In the last 20 years the emergence of computer-aided positioning systems have facilitated this additionally. However, many users state difficulties to harmonize maps with the real world. The available thesis addresses this problem with embedding compass functionality into an electronic navigation system. On the basis of a mobile device (PDA) this work describes the process of the physical interfacing up to the visualisation of magnetometer data. The result is a functioning navigation software, which was successfully tested by means of a field experiment. The available work serves as basis for further research within the area of navigation support.

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