Geospatial Data Management and Visualization

Recommended Prerequisites

Not applicable.

Teaching Methods

To pass the course, students need to participate actively in the course contact hours (lectures, demonstrations, milestone meetings and introductory practicals) and reserve enough time for self-studying using e-learning materials.

Implementation methods: Lectures, Group working, Practical, Team presentations, Self-studying, Portfolio.

Learning Outcomes

The course aims at deepening students understanding and practical skills of geospatial data management, including data capture, maintenance, updating, quality assessment, data sharing and visualization. After the completion of the course, students:

-are able to use standardized methods of data management and data quality assessment

-are skilled in evaluating quality of different types of geospatial data sets and combining different methods of geospatial data quality assessment in practice

-have advanced geospatial data management and data sharing skills using GIS software and web based applications

-have improved geospatial data visualization skills and confidence in visualizing data for end-users

-have obtained skills in team-working and communication and dissemination of geospatial information.

Work Placement(s)

No

Syllabus

The key topics of the course are geospatial data quality, metadata standards, data quality assessment, spatial data infrastructures (SDIs), data management, data visualization, and data sharing via web-map applications. The course focuses on open data and open-source software and data sharing solutions.

Assessment Methods

Assessment
Lectures, Group working, Practical, Team presentations, Self-studying, Portfolio: 100.0%

Bibliography

Heipke, Christian (2010). Crowdsourcing geospatial data. ISPRS Journal of Photogrammetry and Remote Sensing 65 (2010) 550–557.

Veregin, H. (2005). Data Quality Parameters, chapter 12. In: Paul A. Longley, Michael F. Goodchild, David J. Maguire,

David W. Rhind (2005). Geographical Information Systems: Principles, Techniques, Management and Applications, 2^nd Edition.

Xia Jingfeng (2012). Metrics to Measure Open Geospatial Data Quality. Issues in Science and Technology Librarianship. DOI:10.5062/F4B85627. Access at: http://www.istl.org/12-winter/article1.html?a_aid=3598aabf

Frederika Welle Donker & Bastiaan van Loenen (2017). How to assess the success of the open data ecosystem?, International Journal of Digital Earth, 10:3, 284-306

David J. Maguire, Paul A. Longley (2005). The emergence of geoportals and their role in spatial data infrastructures.

Computers, Environment and Urban Systems 29, 3–14. etc.