4 research outputs found
'Inventions and adventures': the work of the Stevenson engineering firm in Scotland, c. 1830 - c. 1890
This thesis examines the work of the nineteenth-century Stevenson civil engineering firm to argue
that civil engineering should be approached geographically both because it takes place in and is
shaped by particular spaces, but also because the result of such work reshapes space and the
relationship between places. Geographers have extensively analysed the ways in which humans
have worked to alter environments, but relatively little attention has been paid to engineering as a
socially and geographically transformative process, to the technical questions and to the engineering
professionals whose work brought about such change. This thesis analyses engineers as social and
technical agents of environmental change, rather than viewing their role as the simple
implementation of directives developed elsewhere and by others. It combines insights from the
history and historical geography of science, environmental history and the history of technology to
make a case for the relevance of an historical geography of engineering.
The thesis explores these issues through the work of the Stevenson family. The Stevensons
were an Edinburgh-based and internationally-renowned firm of engineers who specialised in the
construction of coastal infrastructure. The start and end dates of the thesis indicate, broadly, the
careers of David and Thomas Stevenson, who jointly managed the family firm under the name D. &
T. Stevenson between 1850 and 1886. The empirical basis for this thesis draws upon the detailed
analysis of the firm’s archival records: technical publications, project reports, diaries,
correspondence, maps, plans and diagrams.
The work of the Stevensons—their engineering epistemologies, practices, and professional
identities— are examined through four diverse projects undertaken by the firm in the nineteenth
century. These projects are: the training of new engineers; surveying and designing improvement
works for the rivers Tay and Clyde; the implementation of a coastal sound-based fog signal network;
and the failed attempt to expand Wick harbour through the construction of a breakwater. These
projects highlight the range of activities undertaken by nineteenth-century engineers and illustrate
the ‘making’ of engineers and the work they did by highlighting training and learning, surveying,
maintenance, testing, evaluation, repair and the explanation of failure. With reference to these
projects and by drawing upon relevant contextual material, the thesis examines the
conceptualisation of geographical space and natural forces in engineering, the relationship between
science and engineering, the nature of expertise and notions of engineering judgement, and the role
of family, legacy and reputation in securing professional credibility and status.
This approach challenges older historiographical traditions which portrayed engineers as
individual geniuses. The thesis instead understands engineering to be a combination of specialist
knowledge and tacit skill and situates engineers within their social and institutional networks of
power and authority. In pointing out that some engineering works failed, the thesis challenges the
tendency in histories of engineering works to focus on success. It makes the case for an historical
geography of engineering as a way of understanding engineering as an activity, a status and as
processes which changed human-environment relations
Exploiting general-purpose background knowledge for automated schema matching
The schema matching task is an integral part of the data integration process. It is usually the first step in integrating data. Schema matching is typically very complex and time-consuming. It is, therefore, to the largest part, carried out by humans. One reason for the low amount of automation is the fact that schemas are often defined with deep background knowledge that is not itself present within the schemas. Overcoming the problem of missing background knowledge is a core challenge in automating the data integration process.
In this dissertation, the task of matching semantic models, so-called ontologies, with the help of external background knowledge is investigated in-depth in Part I. Throughout this thesis, the focus lies on large, general-purpose resources since domain-specific resources are rarely available for most domains. Besides new knowledge resources, this thesis also explores new strategies to exploit such resources.
A technical base for the development and comparison of matching systems is presented in Part II. The framework introduced here allows for simple and modularized matcher development (with background knowledge sources) and for extensive evaluations of matching systems.
One of the largest structured sources for general-purpose background knowledge are knowledge graphs which have grown significantly in size in recent years. However, exploiting such graphs is not trivial. In Part III, knowledge graph em- beddings are explored, analyzed, and compared. Multiple improvements to existing approaches are presented.
In Part IV, numerous concrete matching systems which exploit general-purpose background knowledge are presented. Furthermore, exploitation strategies and resources are analyzed and compared. This dissertation closes with a perspective on real-world applications
Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року
Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року
Génération automatique d'alignements complexes d'ontologies
Le web de données liées (LOD) est composé de nombreux entrepôts de données. Ces données sont décrites par différents vocabulaires (ou ontologies). Chaque ontologie a une terminologie et une modélisation propre ce qui les rend hétérogènes. Pour lier et rendre les données du web de données liées interopérables, les alignements d'ontologies établissent des correspondances entre les entités desdites ontologies. Il existe de nombreux systèmes d'alignement qui génèrent des correspondances simples, i.e., ils lient une entité à une autre entité. Toutefois, pour surmonter l'hétérogénéité des ontologies, des correspondances plus expressives sont parfois nécessaires. Trouver ce genre de correspondances est un travail fastidieux qu'il convient d'automatiser. Dans le cadre de cette thèse, une approche d'alignement complexe basée sur des besoins utilisateurs et des instances communes est proposée. Le domaine des alignements complexes est relativement récent et peu de travaux adressent la problématique de leur évaluation. Pour pallier ce manque, un système d'évaluation automatique basé sur de la comparaison d'instances est proposé. Ce système est complété par un jeu de données artificiel sur le domaine des conférences.The Linked Open Data (LOD) cloud is composed of data repositories. The data in the repositories are described by vocabularies also called ontologies. Each ontology has its own terminology and model. This leads to heterogeneity between them. To make the ontologies and the data they describe interoperable, ontology alignments establish correspondences, or links between their entities. There are many ontology matching systems which generate simple alignments, i.e., they link an entity to another. However, to overcome the ontology heterogeneity, more expressive correspondences are sometimes needed. Finding this kind of correspondence is a fastidious task that can be automated. In this thesis, an automatic complex matching approach based on a user's knowledge needs and common instances is proposed. The complex alignment field is still growing and little work address the evaluation of such alignments. To palliate this lack, we propose an automatic complex alignment evaluation system. This system is based on instances. A famous alignment evaluation dataset has been extended for this evaluation