Parallel Coordinates-based Visual Analytics for Materials Property

Diwas Bhattarai, Jian Zhang, Bijaya B. Karki

2019

Abstract

Because of major advances in experimental and computational techniques, materials data are abundant even for specific classes of materials such as magma-forming silicate melts. A given material property M can be posed as a complex multivariate data problem. The relevant variables or dimensions are the values of the property itself, the factors which influence the property (pressure P, temperature T, multicomponent composition X), and meta data information I. Here we present an innovative visual analytics system for the melt viscosity (η), which can be represented by M (η, P, T, X1, X2, ..., I1, I2, ...). Our system consists of a viscosity data store along with a web-based visualization support. In particular, we enrich the parallel coordinates plot with non-standard features, such as derived axes/sub-axes, dimension merging, binary scaling, and nested plot. It offers many insights of relevance to underlying physics, data modeling, and guiding future experiments/computations. Other material properties such as density can be incorporated as new attributes and corresponding new axes in the plot. Our aim is to collect all published data on various melt properties and develop a framework supporting database, visualization and modelling functions.

Paper Citation

in Harvard Style

Bhattarai D., Zhang J. and Karki B. (2019). Parallel Coordinates-based Visual Analytics for Materials Property. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 2: IVAPP; ISBN 978-989-758-354-4, SciTePress, pages 83-95. DOI: 10.5220/0007375400830095

in Bibtex Style

@conference{ivapp19,
author={Diwas Bhattarai and Jian Zhang and Bijaya B. Karki},
title={Parallel Coordinates-based Visual Analytics for Materials Property},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 2: IVAPP},
year={2019},
pages={83-95},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007375400830095},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 2: IVAPP
TI - Parallel Coordinates-based Visual Analytics for Materials Property
SN - 978-989-758-354-4
AU - Bhattarai D.
AU - Zhang J.
AU - Karki B.
PY - 2019
SP - 83
EP - 95
DO - 10.5220/0007375400830095
PB - SciTePress