Authors:
Robert Olszewski
1
;
Agnieszka Turek
1
and
Marcin Łączyński
2
Affiliations:
1
Warsaw University of Technology, Poland
;
2
University of Warsaw, Poland
Keyword(s):
Spatial Data Mining, Gamification, Data Analysis, Participatory Modelling, Revitalisation, Smart City.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
City Data Management
;
Data Analytics
;
Data Engineering
;
Data Management and Quality
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Predictive Modeling
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Statistics Exploratory Data Analysis
;
Symbolic Systems
Abstract:
The basic problem in predictive participatory urban planning is activating residents of a city, e.g. through the application of the technique of individual and/or team gamification. The authors of the article developed (and tested in Płock) a methodology and prototype of an urban game called “Urban Shaper”. This permitted obtaining a vast collection of opinions of participants on the directions of potential development of the city. The opinions, however, are expressed in an indirect manner. Therefore, their analysis and modelling of participatory urban development requires the application of extended algorithms of spatial statistics. The collected source data are successively processed by means of spatial data mining techniques, permitting activation of condensed spatial knowledge based on “raw” source data with high volume (big data).