Towards a framework for developing visual analytics in supply chain environments

Abstract

Visual Analytics (VA) has shown to be of significant importance for Supply Chain (SC) analytics. However, SC partners still have challenges incorporating it into their data-driven decision-making activities. A conceptual framework for the development and deployment of a VA system provides an abstract, platform-independent model for the whole process of VA, covering requirement specification, data collection and pre-processing, visualization recommendation, visualization specification and implementation, and evaluations. In this paper, we propose such a framework based on three main aspects: 1) Business view, 2) Asset view, and 3) Technology view. Each of these views covers a set of steps to facilitate the development and maintenance of the system in its context. The framework follows a consistent process structure that comprises activities, tasks, and people. The final output of the whole process is the VA as a deliverable. This facilitates the alignment of VA activities with business processes and decision-making activities. We presented the framework's applicability using an actual usage scenario and left the implementation of the system for future work.

The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

“…When we started to research Visual Analytics (VA) systems for supply chain decisionmaking support [1], we found that supply chain actors have enormous and heterogeneous data and different domain analytics problems. Generally, to deploy VA, they need to deal with three aspects [2]: (1) Identifying decisions that VA can support known as VA tasks, (2) data requirements, and (3) VA system development. These aspects formulate the primary constructs of a VA system.…”