DESIGNING SPATIAL DATA MANAGEMENT COURSE BASED ON SPATIAL DATA INFRASTRUCTURE FOR NON-ICT BACKGROUND STUDENTS
Latvia University of Life Sciences and Technologies (LATVIA)
About this paper:
Conference name: 17th International Technology, Education and Development Conference
Dates: 6-8 March, 2023
Location: Valencia, Spain
Abstract:Spatial data and its management are appearing in various processes around multiple disciplines. Driver for these changes are availability of spatial data in various fields, development of hardware which allows to generate such data and industry needs for precision technologies and move towards, for example, digital twin (incl. digital twin of Earth) developments to enforce fact based digital decision-making.
The upcoming European Interoperability Framework presents the four Principles of Interoperability and Interoperability Management: Legal Interoperability, Organizational Interoperability, Semantic Interoperability and Technical Interoperability. The relatively elegant technical implementation of some EU level activities like INSPIRE may indicate that the main problem in the implementation of SDI may not be in the Technical interoperability, but in Legal, Organizational and Semantic interoperability. Therefore, it can be concluded that the implementation of SDI only at the technical level (involving only ICT specialists) is impossible and the technical scope covers only part of the total implementation of SDI.
In this article authors described correlations between four interoperability’s and student’s studying fields with accent on Spatial data infrastructure’s applying skills with aim to engage non-ICT students and raise awareness on Technical and Semantic Interoperability’s to decrease the lack of cross-interoperability’s Principles’ competence. As additional result a new study course program for master's students “Information technologies in geoinformatics” was designed and curriculum proposed for similar course development.
The aim of the study course is to provide knowledge about spatial data processing and data exchange solutions. Students gain knowledge about the types of spatial data, the possibilities of storage, processing, and dissemination. During the practical tasks students get acquainted with performing topological SQL queries in a database and building trivial solutions for the dissemination and presentation of spatial information. In addition, to make the idea of SDI and GII more accessible not only to IT professionals, but also for researchers, data enthusiasts, journalists and students, SDI related source code listings were published in the GitHub source code repository under an open CC0 license, which allows all interested parties freely (without any conditions) to reuse them in the new course development or other activities as well as to improve existing solution.
Keywords: Interdisciplinary course design, learning spatial data, SDI, Interoperability.