Artifact management and behavioral discourse in the software development process for a large public participatory geographic information system
The objective of this work is to develop an artifact management framework (AMF) for supporting a large public participation geographic information system (PPGIS) software development effort. AMF is a conceptual framework to describe minimal necessary artifacts, and tools, people and languages to implement those artifacts for a large PPGIS project. AMF describes how to manage minimal necessary artifacts for a large PPGIS project in a complex environment. We developed AMF for PPGIS based on a popular software design methodology of Model Driven Architecture (MDA). Unified Modeling Language (UML) was generally accepted as the standard technique for object-oriented modeling. MDA takes the next logical step towards abstraction, by applying the principle of separation of concerns. Without any reliance on specific Information Technology environments, MDA-based AMF allows developers to concentrate on building complete and consistent logical model and artifacts of different abstractions in developing PPGIS. An extensive analysis of AMF was performed in both analytic and behavioral discourse approaches in a large PPGIS project-participatory geographic information system for transportation (PGIST). Through human-computer interaction (HCI) research in PGIST system development, we refined the minimal sets of artifact types needed in AMF so that it allows us to model a business domain and generate most of an application's repetitive code, through a set of automated transformations and rules. We investigated the behavioral dynamics in the PGIST software design process within a conceptual framework of five layers and how they affected artifact management. As AMF is collaborative design framework, we developed a participatory assessment strategy and conducted a survey to the PGIST research team. We analyzed questionnaire responses. The results of the analysis suggest that our considering behavioral interaction is important when developing AMF for a large PPGIS project. In general, the analysis showed that AMF is complete, information, transparent and useful for developing a large PPGIS.