- Title
- A comparison of implementation platforms for the visualisation of animal family trees
- Creator
- Kanotangudza, Priviledge
- Subject
- Business intelligence -- Computer programs
- Subject
- Human-computer interaction
- Subject
- Computer science
- Date Issued
- 2024-04
- Date
- 2024-04
- Type
- Master's theses
- Type
- text
- Identifier
- http://hdl.handle.net/10948/64105
- Identifier
- vital:73653
- Description
- Genealogy is the study of family history. Family trees are used to show ancestry and visualise family history. Animal family trees are different from human family trees as animals have more offspring to represent in a family tree visualisation. Auctioneering organisations, such as Boere Korporasie Beperk (BKB), provide livestock auction catalogues containing pictures of the animal on sale, the animal’s family tree and its breeding and selection data. Modern-day farming has become data-driven and livestock farmers use various online devices and platforms to obtain information, such as real-time milk production, animal health monitoring and to manage farming operations. This study investigated and compared two Business Intelligence (BI) platforms namely Microsoft Power BI and Tableau (Salesforce) and the Python programming language used in the implementation of cattle family tree charts. Animal family tree visualisation requirements were identified from analysing data collected from 23 agriculture users and auction attendees who responded to an online questionnaire. The results of an online survey showed that agriculture users preferred an animal family tree that resembled a human one, which is not currently used in livestock auction catalogues. A conference paper was published based on the survey results. The Design Science Research Methodology (DSRM) was used to aid in creating animal family tree charts using Power BI, Tableau and Python. The author compared the visualisation tools against selected criteria, such as learnability, portability interoperability and security. Usability evaluations using eye tracking were conducted with agriculture users in a usability lab to compare the artefacts developed using Power BI and Python. Tableau was discarded during the implementation process as it did not produce the required family tree visualisation The Technology Acceptance Model (TAM) theory, which seeks to predict the acceptance and use of technology based on users' perception of its usefulness and ease of use, was used to guide the research study in evaluating the artefacts. According to TAM, the adoption of the proposed technology to solve the problem of a static animal family tree in livestock auction catalogues was dependent on the agriculture user’s beliefs. This was based upon that the technology would help them make better buying decisions at livestock auctions effortlessly. The other theory used in this study was the Task Technology Fit (TTF). This theory was used mainly to create the task list to be used in the usability test. The results showed that the author of this work and the agriculture users preferred the artefact produced by Power BI. The learnability and development time was shorter and the User Interface (UI) created was more intuitive. The findings of this study indicated that the present auction catalogue could be supplemented using interactive online animal family tree visualisations created using Power BI. This study recommended that livestock auctioneering organisations should, in addition to providing paper catalogues, provide farmers with an online platform to view the family trees of cattle on auction to enhance purchasing decisions.
- Description
- Thesis (MCom) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 2024
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (233 pages)
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela University
- Rights
- All Rights Reserved
- Rights
- Open Access
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Collections
NMU School of Computer Science, Mathematics, Physics and Statistics
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Kanotangudza, P.pdf | 6 MB | Adobe Acrobat PDF | View Details Download |