Visual exploration of high-dimensional spatial data: requirements and deficits

2000 ◽  
Vol 26 (1) ◽  
pp. 77-85 ◽  
Author(s):  
Christoph Uhlenküken ◽  
Benno Schmidt ◽  
Ulrich Streit
Keyword(s):  
Spatial Data ◽  
Visual Exploration ◽  
High Dimensional ◽  
Data Requirements

scholarly journals A redesign of OGC Symbology Encoding standard for sharing cartography

2017 ◽  
Author(s):  
Erwan Bocher ◽  
Olivier Ertz
Keyword(s):  
Spatial Data ◽  
Poor Quality ◽  
Use Cases ◽  
General Observation ◽  
Data Infrastructures ◽  
Open Standards ◽  
Definition Of ◽  
Data Requirements ◽  
Basic Level

Despite most Spatial Data Infrastructures are offering service-based visualization of geospatial data, requirements are often at a very basic level leading to poor quality of maps. This is a general observation for any geospatial architecture as soon as open standards as those of the Open Geospatial Consortium (OGC) shall be applied. To improve the situation, this paper does focus on improvements at the portrayal interoperability side by considering standardization aspects. We propose two major redesign recommendations. First to consolidate the cartographic theory at the core of the OGC Symbology Encoding standard. Secondly to build the standard in a modular way so as to be ready to be extended with upcoming future cartographic requirements. Thus, we start by defining portrayal interoperability by means of typical use cases that frame the concept of sharing cartography. Then we bring to light the strengths and limits of the relevant open standards to consider in this context. Finally we propose a set of recommendations to overcome the limits so as to make these use cases a true reality. Even if the definition of a cartographic-oriented standard is not able to act as a complete cartographic design framework by itself, we argue that pushing forward the standardization work dedicated to cartography is a way to share and disseminate good practices and finally to improve the quality of the visualizations.

Glyphboard: Visual Exploration of High-Dimensional Data Combining Glyphs with Dimensionality Reduction

2020 ◽  
Vol 26 (4) ◽  
pp. 1661-1671 ◽  
Author(s):  
Dietrich Kammer ◽  
Mandy Keck ◽  
Thomas Grunder ◽  
Alexander Maasch ◽  
Thomas Thom ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
High Dimensional Data ◽  
Visual Exploration ◽  
High Dimensional

scholarly journals Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data

2016 ◽  
Vol 111 (513) ◽  
pp. 57-72 ◽  
Author(s):  
Won Chang ◽  
Murali Haran ◽  
Patrick Applegate ◽  
David Pollard
Keyword(s):  
Spatial Data ◽  
Ice Sheet ◽  
High Dimensional

scholarly journals A redesign of OGC Symbology Encoding standard for sharing cartography

2017 ◽  
Author(s):  
Erwan Bocher ◽  
Olivier Ertz
Keyword(s):  
Spatial Data ◽  
Poor Quality ◽  
Use Cases ◽  
General Observation ◽  
Data Infrastructures ◽  
Open Standards ◽  
Definition Of ◽  
Data Requirements ◽  
Basic Level

Despite most Spatial Data Infrastructures are offering service-based visualization of geospatial data, requirements are often at a very basic level leading to poor quality of maps. This is a general observation for any geospatial architecture as soon as open standards as those of the Open Geospatial Consortium (OGC) shall be applied. To improve the situation, this paper does focus on improvements at the portrayal interoperability side by considering standardization aspects. We propose two major redesign recommendations. First to consolidate the cartographic theory at the core of the OGC Symbology Encoding standard. Secondly to build the standard in a modular way so as to be ready to be extended with upcoming future cartographic requirements. Thus, we start by defining portrayal interoperability by means of typical use cases that frame the concept of sharing cartography. Then we bring to light the strengths and limits of the relevant open standards to consider in this context. Finally we propose a set of recommendations to overcome the limits so as to make these use cases a true reality. Even if the definition of a cartographic-oriented standard is not able to act as a complete cartographic design framework by itself, we argue that pushing forward the standardization work dedicated to cartography is a way to share and disseminate good practices and finally to improve the quality of the visualizations.

scholarly journals MODEL FOR SEMANTICALLY RICH POINT CLOUD DATA

2017 ◽  
Vol IV-4/W5 ◽  
pp. 107-115 ◽  
Author(s):  
F. Poux ◽  
R. Neuville ◽  
P. Hallot ◽  
R. Billen
Keyword(s):  
Spatial Data ◽  
Point Cloud ◽  
Point Clouds ◽  
High Dimensional ◽  
Point Cloud Data ◽  
Model Adaptation ◽  
Spatial Concepts ◽  
Cloud Data ◽  
Classification Procedures ◽  
Source Of Information

This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

scholarly journals Visual Exploration of Relationships and Structure in Low-Dimensional Embeddings

2021 ◽  
Author(s):  
Klaus Eckelt ◽  
Andreas Hinterreiter ◽  
Patrick Adelberger ◽  
Conny Walchshofer ◽  
Vaishali Dhanoa ◽  
...  
Keyword(s):  
High Dimensional Data ◽  
Visual Exploration ◽  
High Dimensional ◽  
Data Types ◽  
Structural Relationships ◽  
Or Groups ◽  
Analysis Workflow ◽  
Visual Approach ◽  
Real World Datasets ◽  
Low Dimensional

In this work, we propose an interactive visual approach for the exploration of structural relationships in embeddings of high-dimensional data. These structural relationships, such as item sequences, associations of items with groups, and hierarchies between groups of items, are defining properties of many real-world datasets. Nevertheless, most existing methods for the visual exploration of embeddings treat these structures as second-class citizens or do not take them into account at all. In our proposed analysis workflow, users explore enriched scatterplots of the embedding, in which relationships between items and/or groups are visually highlighted. The original high-dimensional data for single items, groups of items, or differences between connected items and groups is accessible through additional summary visualizations. We carefully tailored these summary and difference visualizations to the various data types and semantic contexts. During their exploratory analysis, users can externalize their insights by setting up additional groups and relationships between items and/or groups, thereby creating graphs that represent visual data stories. We demonstrate the utility and potential impact of our approach by means of two use cases and multiple examples from various domains.

scholarly journals GEO-VISUALISATION AND VISUAL ANALYTICS FOR SMART CITIES: A SURVEY

2018 ◽  
Vol XLII-4/W11 ◽  
pp. 11-18
Author(s):  
S. Harbola ◽  
V. Coors
Keyword(s):  
Public Administration ◽  
Spatial Data ◽  
Smart City ◽  
Visual Analytics ◽  
Smart Cities ◽  
Urban System ◽  
Human Interaction ◽  
White Spots ◽  
Data Requirements ◽  
Insight Into

<p><strong>Abstract.</strong> Geo-Visualisation (GV) and Visual Analytics (VA) of geo-spatial data have become a focus of interest for research, industries, government and other organisations for improving the mobility, energy efficiency, waste management and public administration of a smart city. The geo-spatial data requirements, increasing volumes, varying formats and quality standards, present challenges in managing, storing, visualising and analysing the data. A survey covering GV and VA of the geo-spatial data collected from a smart city helps to portray the potential of such techniques, which is still required. Therefore, this survey presents GV and VA techniques for the geo-spatial urban data represented in terms of location, multi-dimensions including time, and several other attributes. Further, the current study provides a comprehensive review of the existing literature related to GV and VA from cities, highlighting the important open white spots for the cities’ geo-spatial data handling in term of visualisation and analytics. This will aid to get a better insight into the urban system and enable sustainable development of the future cities by improving human interaction with the geo-spatial data.</p>

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