Open AccessMethodologies for publishing linked open government data on the Web: A systematic mapping and a unified process model
Author(s) -
Bruno Elias Penteado,
José Carlos Maldonado,
Seiji Isotani
Publication year - 2023
Publication title -
semantic web
Language(s) - English
Resource type - Journals
eISSN - 2210-4968
pISSN - 1570-0844
DOI - 10.3233/sw-222896
Subject(s) - computer science , process (computing) , data science , publishing , quality (philosophy) , set (abstract data type) , scale (ratio) , linked data , systematic process , systematic review , data quality , government (linguistics) , process management , management science , world wide web , work in process , engineering , semantic web , political science , metric (unit) , philosophy , physics , operations management , medline , epistemology , quantum mechanics , law , programming language , operating system , linguistics
Since the beginning of the release of open data by many countries, different methodologies for publishing linked data have been proposed. However, they seem not to be adopted by early studies exploring linked data for different reasons. In this work, we conducted a systematic mapping in the literature to synthesize the different approaches around the following topics: common steps, associated tools and practices, quality assessment validations, and evaluation of the methodology. The findings show a core set of activities, based on the linked data principles, but with additional critical steps for practical use in scale. Furthermore, although a fair amount of quality issues are reported in the literature, very few of these methodologies embed validation steps in their process. We describe an integrated overview of the different activities and how they can be executed with appropriate tools. We also present research challenges that need to be addressed in future works in this area.