The dataflow visualization pipeline as a problem solving environment
Proceedings of the Eurographics workshop on Virtual environments and scientific visualization '96
Extreme programming explained: embrace change
Extreme programming explained: embrace change
Knowing-Why About Data Processes and Data Quality
Journal of Management Information Systems
Overview and Framework for Data and Information Quality Research
Journal of Data and Information Quality (JDIQ)
Design Research in Information Systems: Theory and Practice
Design Research in Information Systems: Theory and Practice
Design science in information systems research
MIS Quarterly
Meta-analysis of design science research within the IS community: trends, patterns, and outcomes
DESRIST'10 Proceedings of the 5th international conference on Global Perspectives on Design Science Research
Suggested research directions for a new frontier – active conceptual modeling
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
Test driven development: the state of the practice
Proceedings of the 50th Annual Southeast Regional Conference
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Geoscientists and engineers use anomalies which are parts of a profile that is above or below the surrounding average to infer subsurface targets (groundwater, ore and petroleum). Customarily, they are detected by processing field measurements including geological and geophysical data using methods such as stacking (averaging), Fourier analysis and filtering. The issue is these methods often result in partial detection because they perform partial separation of wanted from unwanted anomalies and the error in separation gets propagated into data layers and subsequent analyses, thereby resulting in less accurate spatial predictions. In order to understand and address this issue, we investigate whether the design methodology for construction of mapping applications for characterizing geospatial variables achieves logical consistency of data layers and improve mapping accuracy of groundwater flow. We present a design methodology as an artifact and evaluated it by applying it to hydrogeological and geodetic data acquired from the Santa Clara Valley, CA, USA. The result shows that data parts offer distinctive patterns of geometric features that are signatures of groundwater flow for sustainable groundwater management. The practical implications of the result can be applied by software developers and data modelers, information systems and operations managers to construct logically consistent and well-composed environmental information systems.