Potentials, problems and possibilities for developing New Zealand’s built environment through high-value geospatial information

Abstract

Gaining useful information about our built, social and natural environments is vital and possible. The value of data for cities is more informed, more effective management and development choices resulting in more benefits to a greater range of stakeholders. This article explores the state-of-play of data infrastructures in New Zealand to identify the challenges to gaining better value from geospatial information. Following engagement with built environment data custodians and information users, it analyses how digital information infrastructure can support the sharing and use of richer and more comprehensive information by weaving a supportive fabric across data. The analysis reveals that data infrastructures primarily need to facilitate agreement on data management, sharing and use; the sharing of costs and benefits across stakeholders; and emphasise place as a powerful driver to richer information. An overarching sociotechnical approach to digital information infrastructure weaves data platforms, policy and technology together.

Emerging technical risks from the application of building information modelling

“…Once the risk factors are identified from literature, common risk factors are categorised according to their source and influence. The technical BIM risk categories that were identified are the most recurrent in recent literature and are in line with recent studies such as Zhao et al (2017), Singh et al (2017), Ivory et al (2019), Ayinla and Adamu (2018) and Guo et al (2019).…”

“…Furthermore, it is argued that there is a need to use data between different BIM applications smoothly and avoid unnecessary data re-entry downstream while ensuring data integrity (Gholami et al , 2015; Jiao et al , 2013; Howard and Bjork, 2008; Fox and Hietanen, 2007). Furthermore, Ivory et al (2019) stressed the security barriers of dealing with data and its impediment of information use based on the sensitivity of such data. In current practice, there are divergences in the capability between BIM software.…”

From spatial data to spatial knowledge infrastructure: A proposed architecture

“…Solving the architectural and technical issues is only part of the SKI implementation challenge. The issues of policy and governance are equally very difficult to solve-the research in this domain is emerging, with a few first challenges described in detail in Ivory, O'Donnell, and Schindler (2019).…”