Title
Unapređenje upotrebljivosti otvorenih podataka definisanjem metode kategorizacije zasnovane na metapodacima portala otvorenih podataka
Creator
Frtunić Gligorijević, Milena, 1989-
CONOR:
22049127
Copyright date
2023
Object Links
Select license
Autorstvo-Nekomercijalno-Bez prerade 3.0 Srbija (CC BY-NC-ND 3.0)
License description
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Language
Serbian
Cobiss-ID
Theses Type
Doktorska disertacija
description
Datum odbrane: 26.03.2024
Other responsibilities
Academic Expertise
Tehničko-tehnološke nauke
University
Univerzitet u Nišu
Faculty
Elektronski fakultet
Group
Katedra za računarstvo
Alternative title
ǂThe ǂenhancement of open data usability by defining a categorization method based on the open data portal metadata
Publisher
[M. B. Frtunić Gligorijević]
Format
114 lista
description
Biografija autora: list [160].
Bibliografija: listovi 149-159.
description
Electrical and Computer Engineering (Computer Science).
Open data categorization.
Abstract (en)
Due to numerous data transparency and open government initiatives, a large volume of data was published on open data portals. To make it more accessible and visible, these portals have introduced data filtering by category, tags, format, organization, etc. This information is stored as metadata and provided when publishing the data. However, the metadata is not always complete.
The lack of data categories has a great impact on the data visibility, accessibility, and usability of information. As the data increases on the portals, it becomes harder to find and identify the wanted information when the category is missing.
Within this doctoral dissertation, an analysis of metadata on open data portals, as well as an analysis of categories and tags usage, and their connections on open data portals was performed. Afterward, the problem of missing data categories was addressed by proposing a methodology for data categorization based on the combination of tags.
Within the methodology, the hierarchical organization of tags in a category was defined based on their usage in categorized data. Then, a tool was presented for visual analysis of the hierarchical organization of tags, and a proposal was given for the data categorization based on the combination of tags.
The presented categorization relies on the way tags are used in categorized data, i.e. their hierarchical organization. The approach calculates the similarity between two tags, and two combinations of tags, as well as defines the parameters for categorizing the combination of tags with categories on the portal. Afterward, an algorithm was defined that proposes the categories for a dataset with a given combination of tags.
For the proposed categorization, an evaluation was performed using the data from the Canadian open data portal. Lastly, within the doctoral dissertation, a model was proposed for supplementing the datasets’ metadata on open data portals.
Authors Key words
otvoreni podaci, kategorizacija otvorenih podataka, analiza formalnih koncepata, kategorizacija
Authors Key words
open data, formal concept analysis, open data categorization, cetegorization
Classification
(3:001):004.738.5(043.3)
Subject
T 120
Type
Tekst
Abstract (en)
Due to numerous data transparency and open government initiatives, a large volume of data was published on open data portals. To make it more accessible and visible, these portals have introduced data filtering by category, tags, format, organization, etc. This information is stored as metadata and provided when publishing the data. However, the metadata is not always complete.
The lack of data categories has a great impact on the data visibility, accessibility, and usability of information. As the data increases on the portals, it becomes harder to find and identify the wanted information when the category is missing.
Within this doctoral dissertation, an analysis of metadata on open data portals, as well as an analysis of categories and tags usage, and their connections on open data portals was performed. Afterward, the problem of missing data categories was addressed by proposing a methodology for data categorization based on the combination of tags.
Within the methodology, the hierarchical organization of tags in a category was defined based on their usage in categorized data. Then, a tool was presented for visual analysis of the hierarchical organization of tags, and a proposal was given for the data categorization based on the combination of tags.
The presented categorization relies on the way tags are used in categorized data, i.e. their hierarchical organization. The approach calculates the similarity between two tags, and two combinations of tags, as well as defines the parameters for categorizing the combination of tags with categories on the portal. Afterward, an algorithm was defined that proposes the categories for a dataset with a given combination of tags.
For the proposed categorization, an evaluation was performed using the data from the Canadian open data portal. Lastly, within the doctoral dissertation, a model was proposed for supplementing the datasets’ metadata on open data portals.
“Data exchange” service offers individual users metadata transfer in several different formats. Citation formats are offered for transfers in texts as for the transfer into internet pages. Citation formats include permanent links that guarantee access to cited sources. For use are commonly structured metadata schemes : Dublin Core xml and ETUB-MS xml, local adaptation of international ETD-MS scheme intended for use in academic documents.