Tran, Thai Binh: The knowledge-based search for water-related information system for the Mekong delta, Vietnam. - Bonn, 2014. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc:
author = {{Thai Binh Tran}},
title = {The knowledge-based search for water-related information system for the Mekong delta, Vietnam},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2014,
month = mar,

note = {In recent years, the World Wide Web has strongly changed way of sharing and accessing data. Moreover, with new methods of data collection are developed we have much more data today. However, it is not straightforward to integrate and to discover data or information from different systems, different fields of research as well, especially when users need to find and retrieve the relevant data for their demands. Normally, users get lost in a huge amount of irrelevant search results or may miss relevant data or information. The issue happens because the data are heterogeneity, which are various in formats and organized under different schemas and likely named in different terms to describe the meaning. Thus, it is necessary to have a proper solution to ensure interoperability between different systems. This study proposes an innovation way to describe the meaning of data on how they relate to each other based on the expert knowledge and common dictionaries in order to provide a search result more precise and sufficient for user queries.
The thesis focuses on applying the ontology to discovering and retrieving data for the WISDOM Information System (IS), a Web-based information system for water related information system in Mekong Delta, Vietnam. The proposed approach applies the hybrid ontology and the WISDOM IS is devided into three main domains: i) Data domain, ii) Observed Object domain and iii) Application domain.
Data Domain contains classes that present the properties of datasets, e.g. format type; geometric resolution – pixel size; spatial representation – line, point, polygon or pixel; and spatial relation - which area the datasets relate to; and thematic reference classes of datasets.
Observed Object Domain consists of classes that describe physical and non-physical objects related to the water subject, i.e. “man-made feature”, “natural” and “social”, called observed objects. Phenomena are also presented concerning observed objects. The relationships in this domain are described independently from user’s tasks. Application Domain describes the user’s tasks, divided into types, e.g. response task, monitoring task, etc. The user tasks are described in relation to observed objects, which are the main concerns of these tasks.
The relations between domains are based on the expert knowledge and common dictionaries. These relations describe how the data concern to each other, to phenomena or to observed objects. The real world object observing by users task are describe in relating with the phenomenon in order to provide all relevant data set just for one search.
This study also builds a prototype. The result returns from the prototype are evaluated to prove the sufficiency of the proposed approach. The evaluation uses the common criteria, i.e. precision, recall and average precision. The evaluation proves that the proposed approach is good and has high ability to apply in practice.
This study concluded that ontology can resolve the semantic heterogeneity of data. It can describe the properties of dataset and the relations of dataset’s topic on the real world object, phenomena and users’ tasks as well. The proposed approach can be applied not only for water related domain, but also for another domain.},

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