One of the most difficult tasks a programmer can be confronted with is the migration of a legacy system. Usually, these systems are unstructured, poorly documented and contain complex program logic. The reason for this, in most cases, is an emphasis on raw performance rather than on clean and structured code as well as a long period of applying quick fixes and enhancements rather than doing a proper software reengineering process including a full redesign during major enhancements. Nowadays, the old programming paradigms are becoming an increasingly serious problem. It has been identified that 90% of the costs of a typical software system arise in the maintenance phase. Many companies are simply too afraid of changing their software infrastructure and prefer to continue with principles like "never touch a running system". These companies experience growing pressure to migrate their legacy systems onto newer platforms because the maintenance of such systems is expensive and dangerous as the risk of losing vital parts of sources code or its documentation increases drastically over time. The FermaT transformation system has shown the ability to automatically or semi-automatically restructure and abstract legacy code within a special intermediate language called WSL (Wide Spectrum Language). Unfortunately, the current transformation process only supports the migration of assembler as WSL lacks the ability to handle data types properly. The data structures in assembler are currently directly translated into C data types which involves many assumptional “hard coded” conversions. The absence of an adequate type system for WSL caused several flaws for the whole transformation process and limits its abilities significantly. The main aim of the presented research is to tackle these problems by investigating and formulating how a type system can contribute to a safe and reliable migration of legacy systems. The described research includes the definition of key aspects of type related problems in the FermaT migration process and how to solve them with a suitable type system approach. Since software migration often includes a change in programming language the type system for WSL has to be able to support various type system approaches including the representation of all relevant details to avoid assumptions. This is especially difficult as most programming languages are designed for a special purpose which means that their possible programming constructs and data types differ significantly. This ranges from languages with simple type systems whose program sare prone to unintended side-effects, to languages with strict type systems which are constrained n their flexibility. It is important to include as many type related details as necessary to avoid making assumptions during language to language translation. The result of the investigation is a novel multi layered type system specifically designed to satisfy the needs of WSL for a sophisticated solution without imposing too many limitations on its abilities. The type system has an adjustable expressiveness, able to represent a wide spectrum of typing approaches ranging from weak typing which allows direct memory access and down casting, via very strict typing with a high diversity of data types to object oriented typing which supports encapsulation and data hiding. Looking at the majority of commercial relevant statically typed programming languages, two fundamental properties of type strictness and safety can be identified. A type system can be either weakly or strongly typed and may or may not allow unsafe features such as direct memory access. Each layer of the Wide Spectrum Type System has a different combination of these properties. The approach also includes special Type System Transformations which can be used to move a given WSL program among these layers. Other emphasised key features are explicit typing and scalability. The whole approach is based on a sound mathematical foundation which assures correctness and integrates seamlessly into the present mathematical definition of WSL. The type system is formally introduced to WSL by constructing an attribute grammar for the language. Type checking and type inference are used to annotate the Abstract Syntax Tree of a given WSL program with type derivations which can be used to reveal and indicate possible typing errors or to infer types if the program did not feature explicit type declarations in the first place. Notable in this approach is also the fact that object orientation is introduced to a procedural programming language without the introduction of new semantics. It is shown that object orientation can be introduced just by adjusting type checking rules and adding some syntactical notations. The approach was implemented and tested on two case studies. The thesis describes and discusses both cases in detail and shows how a migration which ignores type systems could accidentally introduce errors due to assumptions during translation. Both case studies use all important aspects of the approach, Including type transformations and object identification. The thesis finalises by summarising the whole work, identifying limitations, presenting future perspectives and drawing conclusions

The ultimate causes of bird migration are largely unknown despite more than a century of research. By studying partially migratory short-distance tropical migrants and by employing comparative methods, some difficulties in testing hypotheses for evolution of migration can be overcome. Using comparative methods I tested the evolutionary precursor hypothesis, a major hypothesis for why migration evolved in some lineages and not in others. The results of this study conflicted with many assumptions and predictions of the evolutionary precursor hypothesis. Most importantly, migratory behavior was not related to diet and habitat in simple ways. The interaction between diet and habitat, as well as consistent associations between flocking behavior and migration suggested that food variability is poorly captured by the surrogates embodied in the evolutionary precursor hypothesis. I then employed comparative methods to studying tropical altitudinal migration. Comparisons of diets and fruit preferences between species pairs showed that migrants are more frugivorous, eat a broader diversity of fruits, and have diets that more strongly resemble their preferences than do residents. Although providing evidence that food limitation plays a role in altitudinal migration, these results do not support the hypothesis that interspecific competition explains variation in migratory behavior. Next, I provided the first test of a predation-based hypothesis to explain altitudinal migration. Migrants breed at higher elevations than where they spend their non-breeding season. Thus, birds may migrate uphill to escape high nest predation risk at lower elevations. Results from this experimental study are largely consistent with this hypothesis, but anomalies between predicted and observed patterns suggest that either migration of lowland birds occurs in response to other factors, or that anthropogenic change has altered the tradeoffs involved in migratory decisions. Finally, I focus on a single migrant species and evaluate (a) two food-based hypotheses to explain the destination of migration movements, and (b) mechanisms underlying intra-specific differences in migratory strategy. Food can explain why Corapipo altera migrate uphill, but not why they migrate downhill. My data on sex bias and body condition leads to a new hypothesis explaining the complete annual cycle of this tropical migrant bird.

Der Einsatz von Ontologien hat in den letzten Jahren, gerade in den Lebenswissenschaften, stark an Bedeutung zugenommen. Durch die parallele Entwicklung von Ontologien mit verschiedenen Schwerpunkten gibt es teilweise mehrere Ontologien zum gleichen Themengebiet. So beinhaltet die Open Biomedical Ontologies (OBO) Foundry mehr als 30 Ontologien, mit dem Schwerpunkt Anatomie. Diese Ontologien sind teilweise sehr groß, zum Beispiel Foundational Model of Anatomy (FMA), National Cancer Institute Thesaurus (NCIt) oder SNOMED Clinical Terms (SNOMED-CT). Um bestimmte Datenintegrationsaufgaben zu vereinfachen werden Mappings zwischen verschiedenen Ontologien benötigt. So sind Ontologiemappings zum Beispiel für das Zusammenführen (Mergen) mehrerer Ontologien in eine integrierte Ontologie/Datenquelle wie das Unified Medical Language System (UMLS) notwendig.

Im Bereich der Lebenswissenschaften steht eine große und wachsende Menge heterogener Datenquellen zur Verfügung, welche häufig in quellübergreifenden Analysen und Auswertungen miteinander kombiniert werden. Um eine einheitliche und strukturierte Erfassung von Wissen sowie einen formalen Austausch zwischen verschiedenen Applikationen zu erleichtern, kommen Ontologien und andere strukturierte Vokabulare zum Einsatz. Sie finden Anwendung in verschiedenen Domänen wie der Molekularbiologie oder Chemie und dienen zumeist der Annotation realer Objekte wie z.B. Gene oder Literaturquellen. Unterschiedliche Ontologien enthalten jedoch teilweise überlappendes Wissen, so dass die Bestimmung einer Abbildung (Ontologiemapping) zwischen ihnen notwendig ist. Oft ist eine manuelle Mappingerstellung zwischen großen Ontologien kaum möglich, weshalb typischerweise automatische Verfahren zu deren Abgleich (Matching) eingesetzt werden. Aufgrund neuer Forschungserkenntnisse und Nutzeranforderungen verändern sich die Ontologien kontinuierlich weiter. Die Evolution der Ontologien hat wiederum Auswirkungen auf abhängige Daten wie beispielsweise Annotations- und Ontologiemappings, welche entsprechend aktualisiert werden müssen. Im Rahmen dieser Arbeit werden neue Methoden und Algorithmen zum Umgang mit der Evolution ontologie-basierter Mappings entwickelt. Dabei wird die generische Infrastruktur GOMMA zur Verwaltung und Analyse der Evolution von Ontologien und Mappings genutzt und erweitert. Zunächst wurde eine vergleichende Analyse der Evolution von Ontologiemappings für drei Subdomänen der Lebenswissenschaften durchgeführt. Ontologien sowie Mappings unterliegen teilweise starken Änderungen, wobei die Evolutionsintensität von der untersuchten Domäne abhängt. Insgesamt zeigt sich ein deutlicher Einfluss von Ontologieänderungen auf Ontologiemappings. Dementsprechend können bestehende Mappings infolge der Weiterentwicklung von Ontologien ungültig werden, so dass sie auf aktuelle Ontologieversionen migriert werden müssen. Dabei sollte eine aufwendige Neubestimmung der Mappings vermieden werden. In dieser Arbeit werden zwei generische Algorithmen zur (semi-) automatischen Adaptierung von Ontologiemappings eingeführt. Ein Ansatz basiert auf der Komposition von Ontologiemappings, wohingegen der andere Ansatz eine individuelle Behandlung von Ontologieänderungen zur Adaptierung der Mappings erlaubt. Beide Verfahren ermöglichen die Wiederverwendung unbeeinflusster, bereits bestätigter Mappingteile und adaptieren nur die von Änderungen betroffenen Bereiche der Mappings. Eine Evaluierung für sehr große, biomedizinische Ontologien und Mappings zeigt, dass beide Verfahren qualitativ hochwertige Ergebnisse produzieren. Ähnlich zu Ontologiemappings werden auch ontologiebasierte Annotationsmappings durch Ontologieänderungen beeinflusst. Die Arbeit stellt einen generischen Ansatz zur Bewertung der Qualität von Annotationsmappings auf Basis ihrer Evolution vor. Verschiedene Qualitätsmaße erlauben die Identifikation glaubwürdiger Annotationen beispielsweise anhand ihrer Stabilität oder Herkunftsinformationen. Eine umfassende Analyse großer Annotationsdatenquellen zeigt zahlreiche Instabilitäten z.B. aufgrund temporärer Annotationslöschungen. Dementsprechend stellt sich die Frage, inwieweit die Datenevolution zu einer Veränderung von abhängigen Analyseergebnissen führen kann. Dazu werden die Auswirkungen der Ontologie- und Annotationsevolution auf sogenannte funktionale Analysen großer biologischer Datensätze untersucht. Eine Evaluierung anhand verschiedener Stabilitätsmaße erlaubt die Bewertung der Änderungsintensität der Ergebnisse und gibt Aufschluss, inwieweit Nutzer mit einer signifikanten Veränderung ihrer Ergebnisse rechnen müssen. Darüber hinaus wird GOMMA um effiziente Verfahren für das Matching sehr großer Ontologien erweitert. Diese werden u.a. für den Abgleich neuer Konzepte während der Adaptierung von Ontologiemappings benötigt. Viele der existierenden Match-Systeme skalieren nicht für das Matching besonders großer Ontologien wie sie im Bereich der Lebenswissenschaften auftreten. Ein effizienter, kompositionsbasierter Ansatz gleicht Ontologien indirekt ab, indem existierende Mappings zu Mediatorontologien wiederverwendet und miteinander kombiniert werden. Mediatorontologien enthalten wertvolles Hintergrundwissen, so dass sich die Mappingqualität im Vergleich zu einem direkten Matching verbessern kann. Zudem werden generelle Strategien für das parallele Ontologie-Matching unter Verwendung mehrerer Rechenknoten vorgestellt. Eine größenbasierte Partitionierung der Eingabeontologien verspricht eine gute Lastbalancierung und Skalierbarkeit, da kleinere Teilaufgaben des Matchings parallel verarbeitet werden können. Die Evaluierung im Rahmen der Ontology Alignment Evaluation Initiative (OAEI) vergleicht GOMMA und andere Systeme für das Matching von Ontologien in verschiedenen Domänen. GOMMA kann u.a. durch Anwendung des parallelen und kompositionsbasierten Matchings sehr gute Ergebnisse bezüglich der Effektivität und Effizienz des Matchings, insbesondere für Ontologien aus dem Bereich der Lebenswissenschaften, erreichen. / In the life sciences, there is an increasing number of heterogeneous data sources that need to be integrated and combined in comprehensive analysis tasks. Often ontologies and other structured vocabularies are used to provide a formal representation of knowledge and to facilitate data exchange between different applications. Ontologies are used in different domains like molecular biology or chemistry. One of their most important applications is the annotation of real-world objects like genes or publications. Since different ontologies can contain overlapping knowledge it is necessary to determine mappings between them (ontology mappings). A manual mapping creation can be very time-consuming or even infeasible such that (semi-) automatic ontology matching methods are typically applied. Ontologies are not static but underlie continuous modifications due to new research insights and changing user requirements. The evolution of ontologies can have impact on dependent data like annotation or ontology mappings. This thesis presents novel methods and algorithms to deal with the evolution of ontology-based mappings. Thereby the generic infrastructure GOMMA is used and extended to manage and analyze the evolution of ontologies and mappings. First, a comparative evolution analysis for ontologies and mappings from three life science domains shows heavy changes in ontologies and mappings as well as an impact of ontology changes on the mappings. Hence, existing ontology mappings can become invalid and need to be migrated to current ontology versions. Thereby an expensive redetermination of the mappings should be avoided. This thesis introduces two generic algorithms to (semi-) automatically adapt ontology mappings: (1) a composition-based adaptation relies on the principle of mapping composition, and (2) a diff-based adaptation algorithm allows for individually handling change operations to update mappings. Both approaches reuse unaffected mapping parts, and adapt only affected parts of the mappings. An evaluation for very large biomedical ontologies and mappings shows that both approaches produce ontology mappings of high quality. Similarly, ontology changes may also affect ontology-based annotation mappings. The thesis introduces a generic evaluation approach to assess the quality of annotation mappings based on their evolution. Different quality measures allow for the identification of reliable annotations, e.g., based on their stability or provenance information. A comprehensive analysis of large annotation data sources shows numerous instabilities, e.g., due to the temporary absence of annotations. Such modifications may influence results of dependent applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. The question arises to what degree ontology and annotation changes may affect such analyses. Based on different stability measures the evaluation assesses change intensities of application results and gives insights whether users need to expect significant changes of their analysis results. Moreover, GOMMA is extended by large-scale ontology matching techniques. Such techniques are useful, a.o., to match new concepts during ontology mapping adaptation. Many existing match systems do not scale for aligning very large ontologies, e.g., from the life science domain. One efficient composition-based approach indirectly computes ontology mappings by reusing and combining existing mappings to intermediate ontologies. Intermediate ontologies can contain useful background knowledge such that the mapping quality can be improved compared to a direct match approach. Moreover, the thesis introduces general strategies for matching ontologies in parallel using several computing nodes. A size-based partitioning of the input ontologies enables good load balancing and scalability since smaller match tasks can be processed in parallel. The evaluation of the Ontology Alignment Evaluation Initiative (OAEI) compares GOMMA and other systems in terms of matching ontologies from different domains. Using the parallel and composition-based matching, GOMMA can achieve very good results w.r.t. efficiency and effectiveness, especially for ontologies from the life science domain.