Object Orientation, Open Regional Science, and Cumulative Knowledge Building

Abstract

Integrating human and physical systems is a daunting challenge that spans a great many problem domains, including social and economic production systems, residential behaviors, environmental exchange, and resource and land use. Because so much current research continues to be focused within rather than across these areas, our cumulative knowledge in many respects is little more than a simple summation of various disciplinary and sub-disciplinary learning curves, rather than a truly integrated, synergistic base of understanding. Indeed, a complete understanding of any subdomain may not even be possible in the absence of domain integration. Even within some subdomains, there may be very few instances of truly cumulative science, where one scholar's work adopts another's directly as the foundation for a new and tightly integrated cumulative model. If it were possible to speed the diffusion of modeling innovations and research findings within and among subdomains, the cumulative frontiers of knowledge could be expected also to advance apace.We believe that the future of research in regional science, and indeed in all social science modeling, will be based on a research infrastructure that leverages the power of networked individuals focusing their collective intellect on problem R. Jackson ( )

Spatial Optimization for Land-use Allocation

“…Recently, the open source initiatives 1 have offered great opportunities and flexibility to develop new software tools for land use optimization problems. Open source software is usually developed by collaborations and can be used, changed and shared for free, thereby facilitating and encouraging the adoption and use of various research methodologies (Jackson et al, 2017). Finally, an element that has attracted less attention in sustainable land use planning is the temporal dimension.…”

“…Recently, the open source initiatives (http://opensource.org/) have offered great opportunities and flexibility to develop new software tools for land-use optimization problems. Open source software is usually developed by collaborations and can be used, changed, and shared for free, thereby facilitating and encouraging the adoption and use of various research methodologies (Jackson, Rey, and Járosi 2017). Although recent years have seen an extensive growth in both open source GIS software tools (e.g., QGIS, http://www.qgis.org) and open source optimization tools (e.g., COIN-OR, http://www.coin-or.org, and Liger, http://codem.group.shef.ac.uk/index.php/liger), there are few software tools available in the field of spatial optimization combining GIS and operations research.…”