A review of data visualization: opportunities in manufacturing sequence management.

Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application

Hypothesis exploration with visualization of variance.

BackgroundThe Consortium for Neuropsychiatric Phenomics (CNP) at UCLA was an investigation into the biological bases of traits such as memory and response inhibition phenotypes-to explore whether they are linked to syndromes including ADHD, Bipolar disorder, and Schizophrenia. An aim of the consortium was in moving from traditional categorical approaches for psychiatric syndromes towards more quantitative approaches based on large-scale analysis of the space of human variation. It represented an application of phenomics-wide-scale, systematic study of phenotypes-to neuropsychiatry research.ResultsThis paper reports on a system for exploration of hypotheses in data obtained from the LA2K, LA3C, and LA5C studies in CNP. ViVA is a system for exploratory data analysis using novel mathematical models and methods for visualization of variance. An example of these methods is called VISOVA, a combination of visualization and analysis of variance, with the flavor of exploration associated with ANOVA in biomedical hypothesis generation. It permits visual identification of phenotype profiles-patterns of values across phenotypes-that characterize groups. Visualization enables screening and refinement of hypotheses about variance structure of sets of phenotypes.ConclusionsThe ViVA system was designed for exploration of neuropsychiatric hypotheses by interdisciplinary teams. Automated visualization in ViVA supports 'natural selection' on a pool of hypotheses, and permits deeper understanding of the statistical architecture of the data. Large-scale perspective of this kind could lead to better neuropsychiatric diagnostics

An Integrated Development Environment for Declarative Multi-Paradigm Programming

In this paper we present CIDER (Curry Integrated Development EnviRonment), an analysis and programming environment for the declarative multi-paradigm language Curry. CIDER is a graphical environment to support the development of Curry programs by providing integrated tools for the analysis and visualization of programs. CIDER is completely implemented in Curry using libraries for GUI programming (based on Tcl/Tk) and meta-programming. An important aspect of our environment is the possible adaptation of the development environment to other declarative source languages (e.g., Prolog or Haskell) and the extensibility w.r.t. new analysis methods. To support the latter feature, the lazy evaluation strategy of the underlying implementation language Curry becomes quite useful.Comment: In A. Kusalik (ed), proceedings of the Eleventh International Workshop on Logic Programming Environments (WLPE'01), December 1, 2001, Paphos, Cyprus. cs.PL/011104

MULTI-SCALE DYNAMIC PARTITIONING SYSTEM OF URBAN SPATIAL UNITS

As the spatial structure of cities becomes increasingly complex and sustainable development goals are promoted, society places higher demands on the management and planning of cities. As the basic unit of urban analysis, the combination pattern and scale shape of urban spatial units are crucial for rational management and planning of cities. However, existing urban analysis management systems often adopt a prefabricated fixed cell division method, which is difficult to meet the needs of high precision and multi-scale analysis of urban information. Therefore, this paper proposes an interactive dynamic partitioning technology, and designs a multi-scale dynamic partitioning system for urban spatial units (SUPS), in order to meet the diverse needs of urban management and planning. The system consists of a data management module, a spatial unit module, an integration module and a visualization module. The system not only realises the multi-scale dynamic partitioning of spatial units in the form of interactive operation, but also obtains more detailed identification results by applying the multi-scale spatial units to the identification of urban functional areas, verifying the effectiveness and feasibility of the interactive multi-scale dynamic partitioning of spatial units, and providing a new technical support for fine urban management

Context-aware visual exploration of molecular databases

Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the resulting space to generate a two dimensional map based on a singular value decomposition algorithm and a self organizing map. Experiments on real datasets show that the resulting visual landscape groups molecules of similar chemical properties in densely connected regions