dc.contributor.author | Mugabo, Dennis Raymond | |
dc.date.accessioned | 2023-02-03T08:51:08Z | |
dc.date.available | 2023-02-03T08:51:08Z | |
dc.date.issued | 2022-09 | |
dc.identifier.citation | Mugabo, D.R. (2022). Use of linked data model to publish land acquisition data (a case study of Lusalira – Kasambya – Nkonge – Sembabule Road Project) (Unpublished Master's dissertation). Makerere University, Kampala, Uganda | en_US |
dc.identifier.uri | http://hdl.handle.net/10570/11797 | |
dc.description | A project submitted to the department of Geomatics and Land Management, Makerere University in partial fulfilment of the requirements for the award of Masters of Science in Geo Information Science and Technology | en_US |
dc.description.abstract | The Uganda National Roads Authority through the Department of Land Acquisition under the
Directorate of Roads and Bridges Development is in charge of gathering, administering, and
preserving information on the national road projects. Structured data that is linked to other data
to increase its value through querying is known as linked data. Relational databases and graph
databases differ significantly in that the relationships between the data are maintained in graph
databases as discrete bits of information. Likewise, although in a different way, relational
databases imply that the emphasis on relationships between data is important. The relational
database focus is on the columns of data tables rather than the data pieces.
Land Acquisition data currently exists in a scattered format where by the valuation data, land
survey data, social-economic data and data about payments for a particular project can be stored
in separate locations. The main goal of this study is to explore the use of the Linked data model
to store, manage and query this data.
Focus group discussions were used to determine the current data maturity level of the LA data as
well as determine the competence questions that one would be interested in from the modeled
data. The structured data was transformed into RDF turtles using transformation rules that were
guided by the physical model of the Class and Subclasses of the data developed in Protégé
software.
It was determined that all the LA data was currently stored at the One star, Two star and Three
star levels of the 5 Star Open Data Model of Linked data. This data was transformed into the
Four star level where basically each entry in the data is denoted with Uniform Resource
Identifiers (URLs) which provide a unique identifier for each instance of the data. Queries were
then performed on the data using SPARQL querying language to validate the data model if it can
answer the competence questions.
The model was successfully validated therefore creating a Linked data model for the LA data of
the pilot project. This indicated that if all the LA data across all the various projects under
UNRA is modeled this way, it can easily be stored, managed and stored centrally and once this
Linked data is published on the web, it can be accessible from any location however access
constraints have to be put in place to cater for data security. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Linked data model | en_US |
dc.subject | Linked data | en_US |
dc.subject | Land acquisition data | en_US |
dc.subject | Sembabule Road Project | en_US |
dc.title | Use of linked data model to publish land acquisition data (a case study of Lusalira – Kasambya – Nkonge – Sembabule Road Project) | en_US |
dc.type | Thesis | en_US |