Visual Parameter Selection for Spatial Blind Source Separation
Analysis of spatial multivariate data, i.e., measurements at irregularly‐spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA...
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| Vydané v: | Computer graphics forum Ročník 41; číslo 3; s. 157 - 168 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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England
Blackwell Publishing Ltd
01.06.2022
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | Analysis of spatial multivariate data, i.e., measurements at irregularly‐spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non‐expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data. |
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| AbstractList | Analysis of spatial multivariate data, i.e., measurements at irregularly‐spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non‐expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data. Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non-expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data.Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non-expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data. |
| Author | Nordhausen, K. Miksch, S. Muehlmann, C. Bögl, M. Piccolotto, N. Filzmoser, P. |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36248193$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1002/9781119115151 10.1109/IMMERSIVE.2016.7932377 10.1080/00031305.1991.10475810 10.1016/j.heliyon.2019.e02236 10.1179/000870408x311378 10.1109/tvcg.2019.2934591 10.1109/tvcg.2013.66 10.1109/tvcg.2010.223 10.1111/j.2517-6161.1982.tb01195.x 10.1109/tvcg.2007.70558 10.1109/tvcg.2015.2466992 10.1109/tvcg.2014.2346321 10.1007/978-3-540-70956-5_7 10.1080/15230406.2020.1733438 10.1109/2945.841121 10.1080/15230406.2016.1160797 10.1016/B978-0-12-814022-2.00005-8 10.32614/CRAN.package.SpatialBSS 10.1109/VISUAL.2000.885678 10.1007/978-3-662-05294-5 10.1080/13658810701674970 10.1007/s11004-011-9360-7 10.1080/00045608.2012.689236 10.1111/gean.12048 10.1109/tvcg.2016.2598468 10.1145/3334480.3383101 10.1109/tvcg.2018.2865146 10.1080/15230406.2016.1174623 10.1038/hdy.2008.34 10.1016/j.cag.2013.11.002 10.1016/s0198-9715(01)00046-1 10.1109/tvcg.2018.2865051 10.1214/14-sts487 10.1109/tvcg.2014.2346265 10.1080/23729333.2017.1301346 10.1177/1473871617693041 10.1109/tvcg.2016.2598830 10.1016/c2009-0-19334-0 10.1016/j.spasta.2021.100574 10.1093/biomet/asz079 10.3390/info10100302 10.1007/978-1-4757-1904-8 10.1145/2601097.2601129 10.1007/s11004-014-9559-5 10.1109/tvcg.2015.2467199 10.1109/tvcg.2015.2500225 10.1109/LGRS.2020.3011549 10.1109/tvcg.2019.2945960 |
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| References | 1991; 45.3 2012 2015; 47.7 2010 2021; 27.3 2019; 5.8 2009 1998 2008 1996 2020; 26.1 2015; 47.2 2005 1993 2020; 47.4 2003 2007; 13.6 2002 2008; 45.3 2008; 22.7 2014; 33.4 2019; 10.10 2019; 25.1 2014; 20.12 1982; 44.2 2020; 107.3 2017; 23.1 2000 2022 2002; 26.4 2021 2013; 103.1 2020 2016; 22.9 2000; 6.1 2015; 30.2 1986 2018 2016 2016; 22.1 2013; 19.9 2017; 44.5 2014 2010; 16.6 2017; 3.1 2018; 17.2 e_1_2_9_52_2 Matejka J. (e_1_2_9_39_2) 2018 e_1_2_9_10_2 e_1_2_9_33_2 e_1_2_9_56_2 e_1_2_9_12_2 e_1_2_9_31_2 e_1_2_9_54_2 e_1_2_9_14_2 e_1_2_9_37_2 e_1_2_9_16_2 e_1_2_9_35_2 Reimann C. (e_1_2_9_50_2) 2014 e_1_2_9_58_2 e_1_2_9_18_2 e_1_2_9_41_2 e_1_2_9_62_2 e_1_2_9_60_2 e_1_2_9_20_2 e_1_2_9_45_2 e_1_2_9_22_2 e_1_2_9_43_2 e_1_2_9_64_2 Aitchison J. (e_1_2_9_2_2) 1982; 44 e_1_2_9_6_2 e_1_2_9_4_2 e_1_2_9_8_2 e_1_2_9_24_2 e_1_2_9_26_2 e_1_2_9_47_2 e_1_2_9_51_2 e_1_2_9_30_2 e_1_2_9_34_2 e_1_2_9_55_2 e_1_2_9_11_2 e_1_2_9_32_2 e_1_2_9_53_2 e_1_2_9_13_2 e_1_2_9_38_2 e_1_2_9_59_2 e_1_2_9_15_2 e_1_2_9_36_2 e_1_2_9_57_2 e_1_2_9_17_2 e_1_2_9_19_2 e_1_2_9_40_2 e_1_2_9_63_2 e_1_2_9_61_2 e_1_2_9_21_2 e_1_2_9_44_2 Hrnčiarová T. (e_1_2_9_28_2) 2009 e_1_2_9_23_2 e_1_2_9_42_2 e_1_2_9_7_2 e_1_2_9_5_2 e_1_2_9_3_2 Reimann C. (e_1_2_9_49_2) 1998 e_1_2_9_9_2 e_1_2_9_48_2 Haslett J. (e_1_2_9_25_2) 1991; 45 e_1_2_9_27_2 e_1_2_9_46_2 e_1_2_9_29_2 |
| References_xml | – volume: 26.1 start-page: 34 year: 2020 end-page: 44 article-title: NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation publication-title: IEEE Transactions on Visualization and Computer Graphics – year: 2009 – year: 2005 – start-page: 1 year: 2020 end-page: 9 article-title: Interactive Parallel Coordinates for Parametric Design Space Exploration – year: 2021 – volume: 17.2 start-page: 108 year: 2018 end-page: 127 article-title: Augmenting the Usability of Parallel Coordinate Plot: The Polyline Glyphs publication-title: Information Visualization – volume: 23.1 start-page: 111 year: 2017 end-page: 120 article-title: Characterizing Guidance in Visual Analytics publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 44.5 start-page: 390 year: 2017 end-page: 409 article-title: BinSq: Visualizing GeoGraphic Dot Density Patterns with Gridded Maps publication-title: CartoGraphy and GeoGraphic Information Science – volume: 22.1 start-page: 599 year: 2016 end-page: 608 article-title: Visualizing Multiple Variables Across Scale and GeoGraphy publication-title: IEEE Transactions on Visualization and Computer Graphics – year: 2018 – year: 2014 – volume: 107.3 start-page: 627 year: 2020 end-page: 646 article-title: Spatial Blind Source Separation publication-title: Biometrika – year: 1998 – volume: 25.1 start-page: 491 year: 2019 end-page: 500 article-title: A Heuristic Approach to Value-Driven Evaluation of Visualizations publication-title: IEEE Transactions on Visualization and Computer Graphics – start-page: 286 year: 2014 end-page: 290 – start-page: 100574 year: 2022 – year: 1986 – volume: 47.7 start-page: 753 year: 2015 end-page: 770 article-title: Blind Source Separation for Spatial Compositional Data publication-title: Mathematical Geosciences – volume: 25.1 start-page: 256 year: 2019 end-page: 266 article-title: Drag and Track: A Direct Manipulation Interface for Contextualizing Data Instances within a Continuous Parameter Space publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 16.6 start-page: 1458 year: 2010 end-page: 1467 article-title: World Lines publication-title: IEEE Transactions on Visualization and Computer Graphics – year: 2008 – volume: 47.4 start-page: 305 year: 2020 end-page: 320 article-title: Micro DiaGrams: Visualization of Categorical Point Data from Location-Based Social Media publication-title: CartoGraphy and GeoGraphic Information Science – start-page: 1 year: 2018 end-page: 12 article-title: Dream Lens: Exploration and Visualization of Large-Scale Generative Design Datasets – volume: 44.2 start-page: 139 year: 1982 end-page: 177 article-title: The Statistical Analysis of Compositional Data publication-title: Journal of the Royal Statistical Society – start-page: 154 year: 2008 end-page: 175 article-title: Visual Analytics: Definition, Process, and Challenges – year: 1993 – volume: 3.1 start-page: 45 year: 2017 end-page: 60 article-title: Multivariate Label-Based Thematic Maps publication-title: International Journal of CartoGraphy – volume: 23.1 start-page: 81 year: 2017 end-page: 90 article-title: Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 45.3 start-page: 182 year: 2008 end-page: 192 article-title: Combining Geovisual Analytics with Spatial Statistics: The Example of GeoGraphically Weighted Regression publication-title: The CartoGraphic Journal – volume: 19.9 start-page: 1438 year: 2013 end-page: 1454 article-title: Bristle Maps: A Multivariate Abstraction Technique for Geovisualization publication-title: IEEE Transactions on Visualization and Computer Graphics – start-page: 92 year: 2008 end-page: 103 – year: 2003 – volume: 26.4 start-page: 267 year: 2002 end-page: 292 article-title: Introducing GeoVISTA Studio: An Integrated Suite of Visualization and Computational Methods for Exploration and Knowledge Construction in Geography publication-title: Computers, Environment and Urban Systems – year: 1996 – year: 2000 – volume: 10.10 start-page: 302 year: 2019 article-title: Multivariate Maps—A Glyph-Placement Algorithm to Support Multivariate Geospatial Visualization publication-title: Information – volume: 22.7 year: 2008 article-title: Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (REDCAP) publication-title: International Journal of Geographical Information Science – start-page: 1931 year: 2021 end-page: 1935 – volume: 22.9 start-page: 2200 year: 2016 end-page: 2213 article-title: Visual Encoding of Dissimilarity Data via Topology-Preserving Map Deformation publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 30.2 start-page: 147 year: 2015 end-page: 163 article-title: Cross-Covariance Functions for Multivariate Geostatistics publication-title: Statistical Science – year: 2016 – volume: 20.12 start-page: 2161 year: 2014 end-page: 2170 article-title: Visual Parameter Space Analysis: A Conceptual Framework publication-title: IEEE Transactions on Visualization and Computer Graphics – year: 2010 – volume: 6.1 start-page: 59 year: 2000 end-page: 78 article-title: Designing Pixel-Oriented Visualization Techniques: Theory and Applications publication-title: IEEE Transactions on Visualization and Computer Graphics – start-page: 85 year: 2018 end-page: 101 – volume: 103.1 start-page: 106 year: 2013 end-page: 128 article-title: Principal Component Analysis on Spatial Data: An Overview publication-title: Annals of the Association of American GeoGraphers – volume: 45.3 year: 1991 article-title: Dynamic Graphics for Exploring Spatial Data with Application to Locating Global and Local Anomalies publication-title: The American Statistician – volume: 20.12 start-page: 2033 year: 2014 end-page: 2042 article-title: Attribute Signatures: Dynamic Visual Summaries for Analyzing Multivariate Geographical Data publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 33.4 start-page: 1 year: 2014 end-page: 10 article-title: Pteromys: Interactive Design and Optimization of Free-Formed Free-Flight Model Airplanes publication-title: ACM Transactions on Graphics – volume: 5.8 year: 2019 article-title: A Meta-Analysis of Selected near-Road Air Pollutants Based on Concentration Decay Rates publication-title: Heliyon – year: 2002 – start-page: 381 year: 2012 end-page: 393 – year: 2020 – volume: 22.1 start-page: 579 year: 2016 end-page: 588 article-title: Evaluation of Parallel Coordinates: Overview, Categorization and Guidelines for Future Research publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 47.2 start-page: 146 year: 2015 end-page: 172 article-title: Enhancements to a Geographically Weighted Principal Component Analysis in the Context of an Application to an Environmental Data Set publication-title: Geographical Analysis – volume: 44.5 start-page: 374 year: 2017 end-page: 389 article-title: Point Grid Map: A New Type of Thematic Map for Statistical Data Associated with Geographic Points publication-title: Cartography and Geographic Information Science – volume: 27.3 start-page: 2000 year: 2021 end-page: 2014 article-title: Phoenixmap: An Abstract Approach to Visualize 2D Spatial Distributions publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 13.6 start-page: 1161 year: 2007 end-page: 1168 article-title: GeoGraphically Weighted Visualization: Interactive Graphics for Scale-Varying Exploratory Analysis publication-title: IEEE Transactions on Visualization and Computer Graphics – ident: e_1_2_9_12_2 doi: 10.1002/9781119115151 – ident: e_1_2_9_4_2 doi: 10.1109/IMMERSIVE.2016.7932377 – volume: 45 year: 1991 ident: e_1_2_9_25_2 article-title: Dynamic Graphics for Exploring Spatial Data with Application to Locating Global and Local Anomalies publication-title: The American Statistician doi: 10.1080/00031305.1991.10475810 – ident: e_1_2_9_36_2 doi: 10.1016/j.heliyon.2019.e02236 – ident: e_1_2_9_15_2 doi: 10.1179/000870408x311378 – ident: e_1_2_9_27_2 doi: 10.1109/tvcg.2019.2934591 – ident: e_1_2_9_35_2 doi: 10.1109/tvcg.2013.66 – ident: e_1_2_9_60_2 doi: 10.1109/tvcg.2010.223 – volume: 44 start-page: 139 year: 1982 ident: e_1_2_9_2_2 article-title: The Statistical Analysis of Compositional Data publication-title: Journal of the Royal Statistical Society doi: 10.1111/j.2517-6161.1982.tb01195.x – ident: e_1_2_9_13_2 doi: 10.1109/tvcg.2007.70558 – ident: e_1_2_9_30_2 doi: 10.1109/tvcg.2015.2466992 – ident: e_1_2_9_53_2 doi: 10.1109/tvcg.2014.2346321 – ident: e_1_2_9_33_2 doi: 10.1007/978-3-540-70956-5_7 – ident: e_1_2_9_18_2 doi: 10.1080/15230406.2020.1733438 – ident: e_1_2_9_34_2 doi: 10.1109/2945.841121 – ident: e_1_2_9_48_2 – ident: e_1_2_9_64_2 doi: 10.1080/15230406.2016.1160797 – ident: e_1_2_9_24_2 doi: 10.1016/B978-0-12-814022-2.00005-8 – ident: e_1_2_9_42_2 doi: 10.32614/CRAN.package.SpatialBSS – ident: e_1_2_9_31_2 doi: 10.1109/VISUAL.2000.885678 – ident: e_1_2_9_58_2 doi: 10.1007/978-3-662-05294-5 – ident: e_1_2_9_23_2 doi: 10.1080/13658810701674970 – ident: e_1_2_9_54_2 – ident: e_1_2_9_8_2 doi: 10.1007/s11004-011-9360-7 – ident: e_1_2_9_51_2 – volume-title: Chemistry of Europe's Agricultural Soils. Part A: Methodology and Interpretation of the GEMAS Data Set year: 2014 ident: e_1_2_9_50_2 – ident: e_1_2_9_40_2 – ident: e_1_2_9_16_2 doi: 10.1080/00045608.2012.689236 – ident: e_1_2_9_21_2 – ident: e_1_2_9_26_2 doi: 10.1111/gean.12048 – ident: e_1_2_9_9_2 doi: 10.1109/tvcg.2016.2598468 – ident: e_1_2_9_44_2 doi: 10.1145/3334480.3383101 – ident: e_1_2_9_52_2 – ident: e_1_2_9_59_2 doi: 10.1109/tvcg.2018.2865146 – ident: e_1_2_9_11_2 doi: 10.1080/15230406.2016.1174623 – ident: e_1_2_9_29_2 doi: 10.1038/hdy.2008.34 – volume-title: Atlas Krajiny České Republiky year: 2009 ident: e_1_2_9_28_2 – ident: e_1_2_9_37_2 doi: 10.1016/j.cag.2013.11.002 – ident: e_1_2_9_22_2 doi: 10.1016/s0198-9715(01)00046-1 – ident: e_1_2_9_46_2 doi: 10.1109/tvcg.2018.2865051 – ident: e_1_2_9_20_2 doi: 10.1214/14-sts487 – ident: e_1_2_9_56_2 doi: 10.1109/tvcg.2014.2346265 – volume-title: Environmental Geochemical Atlas of the Central Barents Region year: 1998 ident: e_1_2_9_49_2 – ident: e_1_2_9_61_2 – ident: e_1_2_9_3_2 doi: 10.1080/23729333.2017.1301346 – ident: e_1_2_9_47_2 doi: 10.1177/1473871617693041 – ident: e_1_2_9_17_2 – ident: e_1_2_9_62_2 doi: 10.1109/tvcg.2016.2598830 – ident: e_1_2_9_10_2 doi: 10.1016/c2009-0-19334-0 – ident: e_1_2_9_14_2 – ident: e_1_2_9_6_2 – ident: e_1_2_9_38_2 doi: 10.1016/j.spasta.2021.100574 – ident: e_1_2_9_7_2 doi: 10.1093/biomet/asz079 – ident: e_1_2_9_41_2 doi: 10.3390/info10100302 – start-page: 1 volume-title: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems year: 2018 ident: e_1_2_9_39_2 – ident: e_1_2_9_32_2 doi: 10.1007/978-1-4757-1904-8 – ident: e_1_2_9_57_2 doi: 10.1145/2601097.2601129 – ident: e_1_2_9_45_2 doi: 10.1007/s11004-014-9559-5 – ident: e_1_2_9_55_2 – ident: e_1_2_9_19_2 doi: 10.1109/tvcg.2015.2467199 – ident: e_1_2_9_5_2 doi: 10.1109/tvcg.2015.2500225 – ident: e_1_2_9_43_2 doi: 10.1109/LGRS.2020.3011549 – ident: e_1_2_9_63_2 doi: 10.1109/tvcg.2019.2945960 |
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| Snippet | Analysis of spatial multivariate data, i.e., measurements at irregularly‐spaced locations, is a challenging topic in visualization and statistics alike. Such... Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such... |
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| SubjectTerms | CCS Concepts Domains Evaluation Geochemistry GeoGraphic visualization Human‐centered computing → Visualization techniques Multivariate analysis Parameter identification Prototypes Separation Signal processing Spatial data Visualization |
| Title | Visual Parameter Selection for Spatial Blind Source Separation |
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