With the increase in the number of fast-moving vehicles and the simultaneous development of road building technology, roadside bird mortality has become an increasingly important environmental issue that has the potential to do serious damage to already vulnerable bird populations. This project was therefore initiated after an alarming number of owls were found dead along the N17 and R550 roads in the rural areas between Springs and Devon in the East Rand highveld of Gauteng Province. Five hundred and fifty four owls of four species, namely Marsh Owls, the Red Data listed Grass Owl, Barn Owl and the Spotted Eagle Owl were collected on the stretches of the R550 and N17 during the period between October 2001 and September 2003. They accounted for 53.6%, 27.4%, 17.5% and 1.3% of the mortalities respectively. Unidentified species of owls accounted for the remaining 0.2%. It was found that the monthly mortality rates of the birds varied throughout the year, with the greatest losses being suffered during July, as opposed to relatively lower mortalities occurring during the warmer months. All carcasses were collected, their GPS locations plotted on a map, and ‘hotspot areas’ identified as places of highest incidences of mortalities of the owls. Vehicle-induced mortalities are then discussed in relation to these hotspots, in terms of vegetation and habitat descriptions, daily vehicle counts along the route, as well as fixtures found along the route. It was found that traffic density was indirectly proportional to owl mortalities, with higher traffic speeds definitely having an increasingly detrimental effect on the owl mortalities. Weather conditions also play a role in mortality counts, with the mortalities being significantly negatively correlated to rainfall. Moon phases were also related to the times of highest mortalities, however, this factor did not play a significant role in influencing road mortalities. Another factor that was studied was the influence of differing tarmac road surface temperatures as opposed to gravel road verge surface temperatures, and how these temperatures differed from the ambient temperature. It was found that there was not a big enough difference in the temperatures that would warrant (the previously thought notion) that the owls were attracted to the roads at night to gain heat. Gravel roads had very low incidences of owl mortalities with the highest mortalities recorded along tarmac roads that are bordered by open grasslands or cattle grazing paddocks. It was shown that tarmac roads, bordered by croplands, had a lesser effect on the owl mortalities. Another factor influencing the road mortalities of the owls is grain that is spilled on the road during transport. This initially seemed to be the major factor in attracting granivorous rodents to the roads, and in turn, attracting the owls to prey on them. Rodents identified from recovered pellets and the stomach contents of dead owls confirmed the fact that the majority of rodent prey items were indeed granivorous species, namely Mastomys natalensis and Rhabdomys pumilio. This is in disagreement with previous studies that indicated that a large proportion of the prey species of the Grass Owl was Otomys irroratus, a grass-eating species, even though a rodent trapping study to determine prey abundance within the area indicated a healthy population of O. irroratus. Further studies into prey items of the owls that were dissected indicated that the majority of the prey items recovered were not caught directly on the road as it was already partially digested, suggesting that the prey was caught prior to the owl being killed. From the pellet analyses, other prey items were also found to form part of the owls’ diets. It was found that insects formed largely the diet of the Marsh Owl during the spring, summer and autumn months, with them resorting to smaller rodents during the winter months. Spotted Eagle Owls also preyed almost exclusively on insects. Grass Owls, on the other hand, preyed on small mammals exclusively, with the very rare exception of some insects also being taken. Of all of the dead owls recovered on the roads, post mortems were carried out on only 78 of the carcasses. All of the dead owls examined were in good health prior to death. Various morphometrics of the examined owls were noted. Comparisons of body mass showed that females were larger than males for most species. This was also found for most other measurements as well. It was also found that, according to body mass comparisons, Barn Owls and Marsh Owls were significantly similar. Conducting ANOVA analysis on other morphometrics to determine gender differences, it was found that Grass Owl males were significantly different to females in terms of body mass and length. Marsh Owl males were significantly different to females in terms of body mass and tail length; with Barn Owl males being significantly different in terms of tarsus length to females. Except for Spotted Eagle Owl tarsus lengths all other measurements were in favour of females being significantly larger. These findings were also confirmed when applying the Dimorphism Index to all morphometrics measurements, especially body mass. The degree of parasite infestation was also studied during post mortem examinations. Very few cestodes and nematodes were found, with too few to have an effect on the overall health of the birds prior to death. The vegetation type was studied at transects that coincided with hotspot and non-hotspot sites. Using the PRIMER statistical software package, hotspot sites were found to have highest plant cover and diversity, whereas nonhotspot sites showed lowest plant cover and diversity, generally dominated by Hyparrhenia hirta. During these studies, the degree of available nesting habitat was determined and nesting sites were identified, using the ropedragging technique to flush out roosting and nesting owls that would otherwise have been impossible to find in the thick cover. It was found that Grass Owls preferred a habitat rich in thick grass cover that was relatively high (0.75 m–1 m). It was found that the grass species preferred by these owls were Eragrostis curvula, Paspalum sp., Setaria sp., Sporobolis sp., with few other small herbaceous plants. Marsh Owls, on the other hand, seemed not to be too partial regarding roosting and nesting sites, with them roosting and breeding in more mixed vegetation grasslands that had sparser cover, not reaching the height of the grass cover typical of the habitat preferred by the Grass Owls. Opposed to this were the non-hotspot vegetation sites. These sites were found to have vegetation cover unsuited to both the Marsh and Grass owls, with mixed H. hirta grassland not forming the dense cover, or the height, needed by those two species of owls. Foraging owls were also observed, with the vegetation type in the immediate vicinity noted. Vegetation types similar to breeding areas were noted in these foraging areas. Habitat preferences as well as breeding performance were noted for both grassland species of owls, and found to be directly related to land usage in terms of varying agricultural practices and regimes. Fallow, undisturbed lands were found to be highly productive for the owls. Lands planted with Eragrostis sp. were also found to be very productive, but only if left undisturbed for a period of time sufficient to allow the grassland owls to colonise it. Maize-planted fields were found to be utilised only as foraging fields and no breeding of owls was found to take place close to these fields. After extensive nest searching, it was found that both Marsh and Grass owls were breeding from late March to early June, with the Barn Owls breeding in October and again in March. Grass Owls occur in the study area because of the presence of a natural corridor of suitable habitat that runs parallel with the Blesbokspruit. This favourable habitat of the study area is thus conducive to high population density of grassland owls utilising these uncultivated patches of dense and tall vegetation. The high incidence of mortalities on the road in the study area is due to the concomitant high population densities. This healthy population seems to be sustaining the losses occurring on roads. Owls also seem to be gathering in larger numbers in hotspot zones because of the easy available prey, which are attracted to these high productive areas. Agricultural practices in the area lead to the spillage of grain on the road during transportation. Potential prey species foraging on the roads expose themselves to the nocturnal hunters offering an easy dinner. This process leaves these owls vulnerable to vehicle collisions. The overall population size may be larger than previously thought, not with standing the high mortalities already recorded. The small patches of viable habitat in the study area remains suitable for the breeding of the two grassland owl species allowing for such high densities to occur in the area. The Grass Owl, nonetheless, remains severely threatened as it already occurs as a high priority species for conservation concern in the Gauteng Province. This study provides the first assessment of this owl species of this scale in South Africa and this will ultimately promote the long-term survival of these owls. / Dr. V. Wepener

Semantic approaches have been used to facilitate interoperability in different fields of study. Current literature, however, shows that the semantic approach has not been used to facilitate the interoperability of addresses across domains. Addresses are important reference data used to identify locations and /or delivery points. Interoperability of address data across address or application domains is important because it facilitates the sharing of address data, addressing software and tools which can be used across domains. The aim of this research study has been to evaluate how a semantic (ontologies) approach could be used to facilitate address data interoperability and what the challenges and benefits of the semantic approach are. To realize the hypothesis and answer the research problems, a multi-tier hierarchy of ontology architecture was designed to integrate (across domain) address data with different levels of granularities. Four-tier hierarchy of ontologies was argued to be the optimal architecture for address data interoperability. At the top of the hierarchy was Foundation-Tier that includes vocabularies for location-related information and semantic language rules and concepts. The second tier has address reference ontology (called Base Address Ontology) that was developed to facilitate interoperability across the address domains. Developing optimal address reference ontology was one of the major goals of the research. Different domain ontologies were developed at the third tier of the hierarchy. Domain ontologies extend the vocabulary of the BAO (address reference ontology) with domain specific concepts. At the bottom of the hierarchy are application ontologies that are designed for specific purpose within an address domain or domains. Multiple scenarios of address data usage were considered to answer the research questions from different perspectives. Two interoperable address systems were developed to demonstrate the proof of concepts for the semantic approach. These interoperable environments were created using the UKdata+UPUdata ontology and UKpostal ontology, which illustrate different use cases of ontologies that facilitate interoperability. Ontology reason, inference, and SPARQL query tools were used to share, exchange, and process address data across address domains. Ontology inferences were done to exchange address data attributes between the UK administrative address data and UK postal service address data systems in the UKdata+UPUdata ontology. SPARQL queries were, furthermore, run to extract and process information from different perspective of an address domain and from combined perspectives of two (UK administrative and UK postal) address domains. The second interoperable system (UKpostal ontology) illustrated the use of ontology inference tools to share address data between two address data systems that provide different perspectives of a domain. / Dissertation (MSc)--University of Pretoria, 2014. / tm2015 / Computer Science / MSc / Unrestricted

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Mobile device technology with the influence of the Internet is creating a lot of Webbased services so that people can have easy and 24-hour access to the services. Recently, the Google’s Android has revolutionized applications development for the mobile platform. As there is an increasing number of companies exposing their services as Web services, enabling flexible mobile access to distributed Web resources is a relevant challenge. However, the current Web is a collection of human readable pages that are unintelligible to computer programs. Semantic Web and Web services have the potential of overcoming this limitation. For this, a standard ontology called Ontology Web Language for Services (OWL-S) is employed. The vision is to automatically discover services like Sensor Web services from mobile. In this thesis, a mobile framework is developed for the automatic discovery of services. The application is implemented for the Coastal Sensor Web and the Semantic Web service.

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A Plataforma Lattes é uma excelente base de dados de pesquisadores para a sociedade brasileira, adotada pela maioria das instituições de fomento, universidades e institutos de pesquisa do País. Entretanto, é limitada quanto à exibição de dados sumarizados de um grupos de pessoas, como por exemplo um departamento de pesquisa ou os orientandos de um ou mais professores. Diversos projetos já foram desenvolvidos propondo soluções para este problema, alguns inclusive desenvolvendo ontologias a partir do domínio de pesquisa. Este trabalho tem por objetivo integrar todas as funcionalidades destas ferramentas em uma única solução, a SOS Lattes. Serão apresentados os resultados obtidos no desenvolvimento desta solução e como o uso de ontologias auxilia nas atividades de identificação de inconsistências de dados, consultas para construção de relatórios consolidados e regras de inferência para correlacionar múltiplas bases de dados. Além disto, procura-se por meio deste trabalho contribuir com a expansão e disseminação da área de Web Semântica, por meio da criação de uma ferramenta capaz de extrair dados de páginas Web e disponibilizar sua estrutura semântica. Os conhecimentos adquiridos durante a pesquisa poderão ser úteis ao desenvolvimento de novas ferramentas atuando em diferentes ambientes. / The Lattes Platform is an excellent database of researchers for the Brazilian society , adopted by most Brazilian funding agencies, universities and research institutes. However, it is limited as to displaying summarized data from a group of people, such as a research department or students supervised by one or more professor. Several projects have already been developed which propose solutions to this problem, including some developing ontologies from the research domain. This work aims to integrate all the functionality of these tools in a single solution, SOS Lattes. The results obtained in the development of this solution are presented as well as the use of ontologies to help identifying inconsistencies in the data, queries for building consolidated reports and rules of inference for correlating multiple databases. Also, this work intends to contribute to the expansion and dissemination of the Semantic Web, by creating a tool that can extract data from Web pages and provide their semantic structure. The knowledge gained during the study may be useful for the development of new tools operating in different environments.

A Plataforma Lattes é, hoje, a principal base de currículos dos pesquisadores brasileiros. Os currículos da Plataforma Lattes armazenam de forma padronizada dados profissionais, acadêmicos, de produções bibliográficas e outras informações dos pesquisadores. Através de uma base de Currículos Lattes, podem ser gerados vários tipos de relatórios consolidados. As ferramentas existentes da Plataforma Lattes não são capazes de detectar alguns problemas que aparecem na geração dos relatórios consolidados como duplicidades de citações ou produções bibliográficas classificadas de maneiras distintas por cada autor, gerando um número total de publicações errado. Esse problema faz com que os relatórios gerados necessitem ser revistos pelos pesquisadores e essas falhas deste processo são a principal inspiração deste projeto. Neste trabalho, utilizamos como fonte de informações currículos da Plataforma Lattes para popular uma ontologia e utilizá-la principalmente como uma base de dados a ser consultada para geração de relatórios. Analisamos todo o processo de extração de informações a partir de arquivos HTML e seu posterior processamento para inserí-las corretamente dentro da ontologia, de acordo com sua semântica. Com a ontologia corretamente populada, mostramos também algumas consultas que podem ser realizadas e fazemos uma análise dos métodos e abordagens utilizadas em todo processo, comentando seus pontos fracos e fortes, visando detalhar todas as dificuldades existentes no processo de população (instanciação) automática de uma ontologia. / Lattes Platform is the main database of Brazilian researchers resumés in use nowadays. It stores in a standardized form professional, academic, bibliographical productions and other data from these researchers. From these Lattes resumés database, several types of reports can be generated. The tools available for Lattes platform are unable to detect some of the problems that emerge when generating consolidated reports, such as citation duplicity or bibliographical productions misclassified by their authors, generating an incorrect number of publications. This problem demands a revision performed by the researcher on the reports generated, and the flaws of this process are the main inspiration for this project. In this work we use the Lattes platform resumés database as the source for populating an ontology that is intended to be used to generate reports. We analyze the whole process of information gathering from HTML files and its post-processing to insert them correctly in the ontology, according to its semantics. With this ontology correctly populated, we show some new reports that can be generated and we perform also an analysis of the methods and approaches used in the whole process, highlighting their strengths and weaknesses, detailing the dificulties faced in the automated populating process (instantiation) of an ontology.