GISualization: visualized integration of multiple types of data for knowledge co-production

Abstract

Urban planning deals with multiple layers of information stemming from concurrent activities and stakeholders intervening in urban development. For a better management of complexity more comprehensiveness and data integration are needed. This study develops an adaptive and iterative mixed-method approach for knowledge production in urban transformation processes. Specific research questions relate to data integration from different sources and facilitation of co-production of knowledge beyond triangulation. A new multi-layer framework, GISualization, has been developed in the context of a research project exploring compact city qualities. The framework is structured through five data layers, representing different methods for data collection and different grades of complexity, richness and interpretation: basic statistics; advanced statistics; exogenous quali-quantitative descriptions; exogenous qualitative descriptions; and endogenous qualitative descriptions. Thus, data stem from both quantitative and qualitative sources. Our study has proven that GISualization is a methodological framework that enables analysis and visualization of complex data in a rich format. The approach is closely related to analytical eclecticism and abductivity. It embodies a collaborative communication platform that provides a language to navigate between heterogeneous data, information and methods. The GISualization framework opens up for broader stakeholder involvement and community participation extending research into the domain of transdisciplinary knowledge production.