University of Twente Student Theses
Organising and disclosing River Knowledge at Rijkswaterstaat : a recommendation to the Platform River Knowledge regarding a pilot website for knowledge disclosure
Luyten, T.J.A. (2020) Organising and disclosing River Knowledge at Rijkswaterstaat : a recommendation to the Platform River Knowledge regarding a pilot website for knowledge disclosure.
|
PDF
2MB |
| Abstract: | As the main organisation that manages the river system of the Netherlands, Rijkswaterstaat (RWS) is closely involved in producing, managing, and disclosing river knowledge. It is important that this knowledge is easily accessible, but this is not always the case. The Platform River Knowledge (Platform Rivierkennis) is a community of practice at RWS that sets out to improve this. One of the goals of the Platform is to launch a pilot website for disclosing river knowledge. This study is a preliminary investigation on the topic and provides the Platform with recommendations on organising river knowledge, automatically categorising documents, and shaping a pilot website. A literature review was carried out to explore different taxonomy forms, or knowledge structures, that could be used to organise river knowledge. Interviews were conducted with eight RWS employees working with river knowledge to discuss the results of the literature review and determine which categories to use for organising river knowledge. A machine learning model has been made to sort documents into predefined categories, based on the Naïve Bayes algorithm. Finally, the results were combined to create a conceptual version of the pilot website. The chosen taxonomy form is a facet structure, which works by using multiple overlapping categories. Relevant categories are selected, and only items that belong to all selected categories remain in the search results. This is a useful way of organising river knowledge, as documents containing river knowledge often belong to multiple categories. The choice for a facet structure was approved by all interviewees. The categories proposed by interviewees have resulted in four alternative set-ups ranging from broad to specific. These alternatives should be treated as suggestions, as other combinations can be made. The Naïve Bayes model has been applied to the simplest alternative which features two sets of categories and has been tested using eight documents. The model has correctly predicted the first category 6 out of 8 times and the second category 7 out of 8 times. However, it is unable to sort documents into multiple categories, which is needed if a document belongs to more than one category. The model is not fully functional. The conclusion of this study is that the pilot website should use a facet structure, with the provided alternatives as suggestions for knowledge organisation. A Naïve Bayes model can be used to categorise documents, but the uploader should check to make sure that documents are labelled correctly. The results have been combined into a conceptual version of the pilot website, provided through visual examples. The Platform is recommended to do further research into the demand for a website for disclosing river knowledge. Through the interviews, the demand turned out to be low among RWS employees. If a new website is introduced, interviewing a broader group of stakeholders is recommended to ensure a large support base among users. |
| Item Type: | Essay (Bachelor) |
| Faculty: | ET: Engineering Technology |
| Programme: | Civil Engineering BSc (56952) |
| Link to this item: | https://purl.utwente.nl/essays/84810 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page