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This thesis proposes the use of MSR (Mining Software Repositories) techniques to identify software developers with exclusive expertise about specific APIs and programming domains in software repositories. A pilot Tool for finding such
“Islands of Knowledge” in Node.js projects is presented and applied in a case study to the 180 most popular npm packages. It is found that on average each package has 2.3 Islands of Knowledge, which is possibly explained by the finding that npm packages tend to have only one main contributor. In a survey, the maintainers of 50 packages are contacted and asked for opinions on the results produced by the Tool. Together with their responses, this thesis reports on experiences made with the pilot Tool and how future iterations could produce even more accurate statements about programming expertise distribution in developer teams.
Mapping ORM to TGraph
(2017)
Object Role Modeling (ORM) is a semantic modeling language used to describe objects and their relations amongst each other. Both objects and relations may be subject to rules or ORM constraints.
TGraphs are ordered, attributed, typed and directed graphs. The type of a TGraph and its components, the edges and vertices, is defined using the schema language graph UML (grUML), a profiled version of UML class diagrams. The goal of this thesis is to map ORM schemas to grUML schemas in order to be able to represent ORM schema instances as TGraphs.
Up to this point, the preferred representation for ORM schema instances is in form of relational tables. Though mappings from ORM schemas to relational schemas exist, those publicly available do not support most of the constraints ORM has to offer.
Constraints can be added to grUML schemas using the TGraph query language GReQL, which can efficiently check whether a TGraph validates the constraint or not. The graph library JGraLab provides efficient implementations of TGraphs and their query language GReQL and supports the generation of grUML schemas.
The first goal of this work is to perform a complete mapping from ORM schemas to grUML schemas, using GReQL to sepcify constraints. The second goal is to represent ORM instances in form of TGraphs.
This work gives an overview of ORM, TGraphs, grUML and GReQL and the theoretical mapping from ORM schemas to grUML schemas. It also describes the implementation of this mapping, deals with the representation of ORM schema instances as TGraphs and the question how grUML constraints can be validated.
The Web contains some extremely valuable information; however, often poor quality, inaccurate, irrelevant or fraudulent information can also be found. With the increasing amount of data available, it is becoming more and more difficult to distinguish truth from speculation on the Web. One of the most, if not the most, important criterion used to evaluate data credibility is the information source, i.e., the data origin. Trust in the information source is a valuable currency users have to evaluate such data. Data popularity, recency (or the time of validity), reliability, or vagueness ascribed to the data may also help users to judge the validity and appropriateness of information sources. We call this knowledge derived from the data the provenance of the data. Provenance is an important aspect of the Web. It is essential in identifying the suitability, veracity, and reliability of information, and in deciding whether information is to be trusted, reused, or even integrated with other information sources. Therefore, models and frameworks for representing, managing, and using provenance in the realm of Semantic Web technologies and applications are critically required. This thesis highlights the benefits of the use of provenance in different Web applications and scenarios. In particular, it presents management frameworks for querying and reasoning in the Semantic Web with provenance, and presents a collection of Semantic Web tools that explore provenance information when ranking and updating caches of Web data. To begin, this thesis discusses a highly exible and generic approach to the treatment of provenance when querying RDF datasets. The approach re-uses existing RDF modeling possibilities in order to represent provenance. It extends SPARQL query processing in such a way that given a SPARQL query for data, one may request provenance without modifying it. The use of provenance within SPARQL queries helps users to understand how RDF facts arederived, i.e., it describes the data and the operations used to produce the derived facts. Turning to more expressive Semantic Web data models, an optimized algorithm for reasoning and debugging OWL ontologies with provenance is presented. Typical reasoning tasks over an expressive Description Logic (e.g., using tableau methods to perform consistency checking, instance checking, satisfiability checking, and so on) are in the worst case doubly exponential, and in practice are often likewise very expensive. With the algorithm described in this thesis, however, one can efficiently reason in OWL ontologies with provenance, i.e., provenance is efficiently combined and propagated within the reasoning process. Users can use the derived provenance information to judge the reliability of inferences and to find errors in the ontology. Next, this thesis tackles the problem of providing to Web users the right content at the right time. The challenge is to efficiently rank a stream of messages based on user preferences. Provenance is used to represent preferences, i.e., the user defines his preferences over the messages' popularity, recency, etc. This information is then aggregated to obtain a joint ranking. The aggregation problem is related to the problem of preference aggregation in Social Choice Theory. The traditional problem formulation of preference aggregation assumes a I fixed set of preference orders and a fixed set of domain elements (e.g. messages). This work, however, investigates how an aggregated preference order has to be updated when the domain is dynamic, i.e., the aggregation approach ranks messages 'on the y' as the message passes through the system. Consequently, this thesis presents computational approaches for online preference aggregation that handle the dynamic setting more efficiently than standard ones. Lastly, this thesis addresses the scenario of caching data from the Linked Open Data (LOD) cloud. Data on the LOD cloud changes frequently and applications relying on that data - by pre-fetching data from the Web and storing local copies of it in a cache - need to continually update their caches. In order to make best use of the resources (e.g., network bandwidth for fetching data, and computation time) available, it is vital to choose a good strategy to know when to fetch data from which data source. A strategy to cope with data changes is to check for provenance. Provenance information delivered by LOD sources can denote when the resource on the Web has been changed last. Linked Data applications can benefit from this piece of information since simply checking on it may help users decide which sources need to be updated. For this purpose, this work describes an investigation of the availability and reliability of provenance information in the Linked Data sources. Another strategy for capturing data changes is to exploit provenance in a time-dependent function. Such a function should measure the frequency of the changes of LOD sources. This work describes, therefore, an approach to the analysis of data dynamics, i.e., the analysis of the change behavior of Linked Data sources over time, followed by the investigation of different scheduling update strategies to keep local LOD caches up-to-date. This thesis aims to prove the importance and benefits of the use of provenance in different Web applications and scenarios. The exibility of the approaches presented, combined with their high scalability, make this thesis a possible building block for the Semantic Web proof layer cake - the layer of provenance knowledge.
With global and distributed project teams being increasingly common Collaborative Project Management is becoming the prevalent paradigm for the work in most organisations. Software has for many years been one of the most used tools for supporting Project Management and with the focus on Collaborative Project Management and accompanied by the emergence of Enterprise Collaboration Systems (ECS), Collaborative Project Management Software (CPMS) is gaining increased attention. This thesis examines the capabilities of CPMS for the long-term management of information which not only includes the management of files within these systems, but the management of all types of digital business documents, particularly social business documents. Previous research shows that social content in collaboration software is often poorly managed which poses challenges to meeting performance and conformance objectives in a business. Based on literature research, requirements for the long-term management of information in CPMS are defined and 7 CPMS tools are analysed regarding the content they contain and the functionalities for the long-term management of this content they offer. The study shows that CPMS by and large are not able to meet the long-term information management needs of an organisation on their own and that only the tools geared towards enterprise customers have sufficient capabilities to support the implementation of an Enterprise Information Management strategy.
Key mechanisms for the release of metal(loid)s from a construction material in hydraulic engineering
(2017)
Hydraulic engineering and thus construction materials are necessary to enable the navigability of water ways. Since, a variety of natural as well as artificial materials are used, this materials are world wide tested on a potential release of dangerous substances to prevent adverse effects on the environment. To determine the potential release, it is important to identify and to understand key mechanisms which are decisive for the release of hazardous substances. A limited correlation between the conditions used in regulatory tests and those found in environmental systems is given and hence, often the significance of results from standardised tests on construction materials is questioned, since they are not designed to mimic environmental conditions.
In Germany industrial by-products are used as armour stones in hydraulic engineering. Especially the by-product copper slag is used during the last 40 years for the construction of embankments, groynes and coastal protection. On the one hand, this material has a high density and natural resources (landscape) are protected. One the other hand, the material contains high quantities of metal(loid)s. Therefore the copper slag (product name: iron silicate stones) is very suitable as test material. Metal(loid)s examined were As, Sb and Mo as representatives for (hydr)oxide forming elements and Cd, Co, Cu, Fe, Ni, Pb and Zn were studied as representatives for elements forming cations during the release.
Questions addressed in this Thesis were: (i) can we transfer the results from batch experiments to construction scenarios under the prevalent environmental conditions, (ii) which long-term trends exist for the release of metal(loid)s from copper slags and (iii) how environmental conditions influence the leaching of metal(loid)s from water construction materials?
To answer the first question the surface depending release of the metal(loid)s from the construction materials was examined. Therefore, batch leaching experiments with different particle sizes and a constant liquid/solid ratio were performed. In a second step a comparison between different methods for the determination of the specific surface area of armour stones with a 3D laser scanning method as a reference were performed. In a last step it was possible to show that via a roughness factor the results of the specific surface area from small stones, measured with gas adsorption, can be connected with the results from armour stones, determined with an aluminium foil method. Based on calculations of the specific surface area, it was possible to significantly improve catchment scale calculation about the release of metal(loid)s and to evaluate a potential impact of construction materials in hydraulic engineering on the water chemistry of rivers and streams.
To answer the second question long-term leaching diffuse gradient in thin films supported experiments were performed for half a year. Diffuse gradients in thin films (DGT) is an in situ method to passive sample metal(loid)s in water, sediments and soils. They were used as a sink for metal(loid)s in the eluate to provide solution equilibriums. Thus the exchange of the eluent, which is performed normally in long-term experiments, was superfluous and long-term effects under undisturbed conditions were studied. The long-term leaching experiments with DGT have proven to be capable (i) to differentiate between the depletion of the material surface and the solution equilibriums and (ii) to study sorption processes with or without a further release of the analytes. This means for the practically relevant test material copper slag that: (i) the cations Cd, Co, Cu, Ni and Pb are confirmed to be released from the slag over the whole time period of six months, (ii) a surface depletion of Zn was detected, and (iii) that the (hydr)oxide forming elements As, Mo and Sb were released from the slag over the hole periods of six months but the release was masked by adsorption to Fe-oxide colloids, which were formed during the leaching experiments. It was confirmed, that sulphide minerals are the main source for long-term release of Cd, Cu, Ni, Pb and Mo.
To answer the third question short-term leaching experiments simulating environmental conditions in hydraulic engineering were performed. One factor is the salinity. The influence of this parameter was tested in batch experiments with sea salt solution (30 g/l), river Rhine water, ultra pure water and in addition with different NaCl concentration (5, 10, 20 and 30 g/l). In general, the ionic strength is an important factor for the metal(loid) release but the composition of the water (e.g. the HCO3- content) may superimpose this effect. Therefore, the concentrations of the metal(loid)s in the experiments with ultra-pure water spiked with sea salt or native river water and the ultra-pure water spiked with NaCl were significantly different. In a second experiment the influence of the environmental parameters and the interactions between the environmental parameters pH (4–10), sediment content (0 g–3.75 g), temperature (4 °C–36 °C) and ionic strength (0 g/l–30 g/l NaCl) on the release of metal(loid)s from the test material was examined. The statistical Design of Experiments (DoE) was used to study the influence of these factors as well as their interactions. All studied factors may impact the release of metal(loid)s from the test material to the eluent, whereas the release and the partitioning between sediment and eluate of metal(loid)s was impacted by interactions between the studied factors. The main processes were sorption, complexation, solubility, buffering and ion exchange. In addition, by separating the sediment from the slag after the experiments by magnetic separation, the enrichment of metal(loid)s in the sediment was visible. Thus, the sediment was the most important factor for the release of the metal(loid)s, via pH, temperature and ionic strength, because the sediment acted as a sink.
The presence of anthropogenic chemicals in the natural environment may impact both habitats and human use of natural resources. In particular the contamination of aquatic resources by organic compounds used as pharmaceuticals or household chemicals has become evident. The newly identified environmental pollutants, also known as micropollutants, often have i) unknown ecotoxicological impacts, ii) unknown partitioning mechanisms, e.g. sorption to sediments, and iii) limited regulation to control their emission. Furthermore, like any compound, micropollutants can be transformed while in the environmental matrix to unknown transformation products (TPs), which add to the number of unknown chemicals to consider and thus increase the complexity of risk management. Transformation is at the same time a natural mechanism for the removal of anthropogenic compounds, either by complete degradation (mineralisation) or to innocuous TPs. However, how transformation occurs in real-world conditions is still largely unknown. During the transport of micropollutants from household wastewater to surface water, a large amount of transformation can occur during wastewater treatment—specifically during biological nitrifying–denitrifying treatment processes. The thesis considers the systematic optimisation of laboratory investigative techniques, application of sensitive mass-spectrometry-based analysis techniques and the monitoring of full-scale wastewater treatment plants (WWTPs) to elucidate transformation processes of five known micropollutants.
The first of the five compounds investigated was the antibiotic trimethoprim. Incubation experiments were conducted at different analyte spike concentrations and different sludge to wastewater ratios. Using high-resolution mass spectrometry, a total of six TPs were identified from trimethoprim. The types of TPs formed was clearly influenced by the spike concentration. To the best of our knowledge, such impacts have not been previously described in the literature. Beginning from the lower spike concentration, a relatively stable final TP was formed (2,4-diaminopyrimidine-5-carboxylic acid, DAPC), which could account for almost all of the transformed trimethoprim quantity. The results were compared to the process in a reference reactor. Both by the detection of TPs (e.g., DAPC) and by modelling the removal kinetics, it could be concluded that only experimental results at the low spike concentrations mirrored the real reactor. The limits of using elevated spike concentrations in incubation experiments could thus be shown.
Three phenolic micropollutants, the antiseptic ortho-phenylphenol (OPP), the plastics additive bisphenol A (BPA) and the psychoactive drug dextrorphan were investigated with regard to the formation of potentially toxic, nitrophenolic TPs. Nitrite is an intermediate in the nitrification– denitrification process occurring in activated sludge and was found to cause nitration of these phenols. To elucidate the processes, incubation experiments were conducted in purified water in the presence of nitrite with OPP as the test substance. The reactive species HNO2, N2O3 and the radicals ·NO and ·NO2 were likely involved as indicated by scavenger experiments. In conditions found at WWTPs the wastewater is usually at neutral pH, and nitrite, being an intermediate, usually has a low concentration. By conducting incubation experiments inoculated with sludge from a conventional WWTP, it was found that the three phenolic micropollutants, OPP, BPA and dextrorphan were quickly transformed to biological TPs. Nitrophenolic TPs were only formed after artificial increase of the nitrite concentration or lowering of the pH. However, nitrophenolic-TPs can be formed as sample preparation artefacts through acidification or freezing for preservation, creating optimal conditions for the reaction to take place.
The final micropollutant to be studied was the pain-reliever diclofenac, a micropollutant on the EU-watch list due to ecotoxicological effects on rainbow trout. The transformation was compared in two different treatment systems, one employing a reactor with suspended carriers as a biofilm growth surface, while the other system employed conventional activated sludge. In the biofilm-based system, the pathway was found to produce many TPs each at relatively low concentration, many of which were intermediate TPs that were further degraded to unknown tertiary TPs. In the conventional activated sludge system some of the same reactions took place but all at much slower rates. The main difference between the two systems was due to different reaction rates rather than different transformation pathways. The municipal WWTPs were monitored to verify these results. In the biofilm system, a 10-day monitoring campaign confirmed an 88% removal of diclofenac and the formation of the same TPs as those observed in the laboratory experiments. The proposed environmental quality standard of 0.05 μg/L might thus be met without the need for additional treatment processes such as activated carbon filtration or ozonation.
The extensive literature in the data visualization field indicates that the process of creating efficient data visualizations requires the data designer to have a large set of skills from different fields (such as computer science, user experience, and business expertise). However, there is a lack of guidance about the visualization process itself. This thesis aims to investigate the different processes for creating data visualizations and develop an integrated framework to guide the process of creating data visualizations that enable the user to create more useful and usable data visualizations. Firstly, existing frameworks in the literature will be identified, analyzed and compared. During this analysis, eight views of the visualization process are developed. These views represent the set of activities which should be done in the visualization process. Then, a preliminary integrated framework is developed based on an analysis of these findings. This new integrated framework is tested in the field of Social Collaboration Analytics on an example from the UniConnect platform. Lastly, the integrated framework is refined and improved based on the results of testing with the help of diagrams, visualizations and textual description. The results show that the visualization process is not a waterfall type. It is the iterative methodology with the certain phases of work, demonstrating how to address the eight views with different levels of stakeholder involvement. The findings are the basis for a visualization process which can be used in future work to develop the fully functional methodology.
The Internet of Things (IoT) recently developed from the far-away vision of ubiquitous computing into very tangible endeavors in politics and economy, implemented in expensive preparedness programs. Experts predict considerable changes in business models that need to be addressed by organizations in order to respond to competition. Although there is a need to develop strategies for upcoming transformations, organizational change literature did not turn to the specific change related to the new technology yet. This work aims at investigating IoT-related organizational change by identifying and classifying different change types. It therefore combines the methodological approach of grounded theory with a discussion and classification of identified change informed by a structured literature review of organizational change literature. This includes a meta-analysis of case studies using a qualitative, exploratory coding approach to identify categories of organizational change related to the introduction of IoT. Furthermore a comparison of the identified categories to former technology-related change is provided using the example of Electronic Business (e-business), Enterprise Resource Planning (ERP) systems, and Customer Relationship Management (CRM) systems. As a main result, this work develops a comprehensive model of IoT-related business change. The model presents two main themes of change indicating that personal smart things will transform businesses by means of using more personal devices, suggesting and scheduling actions of their users, and trying to avoid hazards. At the same time, the availability of information in organizations will further increase to a state where information is available ubiquitously. This will ultimately enable accessing real time information about objects and persons anytime and from any place. As a secondary result, this work gives an overview on concepts of technology-related organizational change in academic literature.
The output of eye tracking Web usability studies can be visualized to the analysts as screenshots of the Web pages with their gaze data. However, the screenshot visualizations are found to be corrupted whenever there are recorded fixations on fixed Web page elements on different scroll positions. The gaze data are not gathered on their fixated fixed elements; rather they are scattered on their recorded scroll positions. This problem has raised our attention to find an approach to link gaze data to their intended fixed elements and gather them in one position on the screenshot. The approach builds upon the concept of creating the screenshot during the recording session, where images of the viewport are captured on visited scroll positions and lastly stitched into one Web page screenshot. Additionally, the fixed elements in the Web page are identified and linked to their fixations. For the evaluation, we compared the interpretation of our enhanced screenshot against the video visualization, which overcomes the problem. The results revealed that both visualizations equally deliver accurate interpretations. However, interpreting the visualizations of eye tracking Web usability studies using the enhanced screenshots outperforms the video visualizations in terms of speed and it requires less temporal demands from the interpreters.
For a comprehensive understanding of evolutionary processes and for providing reliable prognoses about the future consequences of environmental change, it is essential to reveal the genetic basis underlying adaptive responses. The importance of this goal increases in light of ongoing climate change, which confronts organisms worldwide with new selection pressures and requires rapid evolutionary change to avoid local extinction. Thereby, freshwater ectotherms like daphnids are particularly threatened. Unraveling the genetic basis of local adaptation is complicated by the interplay of forces affecting patterns of genetic divergence among populations. Due to their key position in freshwater communities, cyclic parthenogenetic mode of reproduction and resting propagules (which form biological archives), daphnids are particularly suited for this purpose.
The aim of this thesis was to assess the impact of local thermal selection on the Daphnia longispina complex and to reveal the underlying genetic loci. Therefore, I compared genetic differentiation among populations containing Daphnia galeata, Daphnia longispina and their interspecific hybrids across time, space, and species boundaries. I revealed strongly contrasting patterns of genetic differentiation between selectively neutral and functional candidate gene markers, between the two species, and among samples from different lakes, suggesting (together with a correlation with habitat temperatures) local thermal selection acting on candidate gene TRY5F and indicating adaptive introgression. To reveal the candidate genes’ impact on fitness, I performed association analyses among data on genotypes and phenotypic traits of D. galeata clones from seven populations. The tests revealed a general temperature effect as well as inter-population differences in phenotypic traits and imply a possible contribution of the candidate genes to life-history traits. Finally, utilizing a combined population transcriptomic and reverse ecology approach, I introduced a methodology with a wide range of applications in evolutionary biology and revealed that local thermal selection was probably a minor force in shaping sequence and gene expression divergence among four D. galeata populations, but contributed to sequence divergence among two populations. I identified many transcripts possibly under selection or contributing strongly to population divergence, a large amount thereof putatively under local thermal selection, and showed that genetic and gene expression variation is not depleted specifically in temperature-related candidate genes.
In conclusion, I detected signs of local adaptation in the D. longispina complex across space, time, and species barriers. Populations and species remained genetically divergent, although increased gene flow possibly contributed, together with genotypes recruited from the resting egg bank, to the maintenance of standing genetic variation. Further work is required to accurately determine the influence of introgression and the effects of candidate genes on individual fitness. While I found no evidence suggesting a response to intense local thermal selection, the high resilience and adaptive potential regarding environmental change I observed suggest positive future prospects for the populations of the D. longispina complex. However, overall, due to the continuing environmental degradation, daphnids and other aquatic invertebrates remain vulnerable and threatened.