Big data has now become a strong focus of global interest that is increasingly attracting the attention of academia, industry, government and other organizations. Big data can be situated in the disciplinary area of traditional geospatial data handling theory and methods. The increasing volume and varying format of collected geospatial big data presents challenges in storing, managing, processing, analyzing, visualizing and verifying the quality of data. This has implications for the quality of decisions made with big data. Consequently, this position paper of the International Society for Photogrammetry and Remote Sensing (ISPRS) Technical Commission II (TC II) revisits the existing geospatial data handling methods and theories to determine if they are still capable of handling emerging geospatial big data. Further, the paper synthesises problems, major issues and challenges with current developments as well as recommending what needs to be developed further in the near future.

https://orbit.dtu.dk/files/117885360/PHOTO_D_15_00278R1B.pdf

Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges

Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject.

/pdf/crowdsourcing-citizen-science-or-volunteered-geographic-4qhdzgct9c.pdf

Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information

Big data has now become a strong focus of global interest that is increasingly attracting the attention of academia, industry, government and other organizations. Big data can be situated in the disciplinary area of traditional geospatial data handling theory and methods. The increasing volume and varying format of collected geospatial big data presents challenges in storing, managing, processing, analyzing, visualizing and verifying the quality of data. This has implications for the quality of decisions made with big data. Consequently, this position paper of the International Society for Photogrammetry and Remote Sensing (ISPRS) Technical Commission II (TC II) revisits the existing geospatial data handling methods and theories to determine if they are still capable of handling emerging geospatial big data. Further, the paper synthesises problems, major issues and challenges with current developments as well as recommending what needs to be developed further in the near future. 
Keywords: Big data, Geospatial, Data handling, Analytics, Spatial Modeling, Review

Factors influencing effective use of big data: A research framework

User tasks play a pivotal role in visualization design and evaluation. However, the term ‘task’ is used ambiguously within the visualization community. In this article, we critically analyze the re...

Task Cube: A three-dimensional conceptual space of user tasks in visualization design and evaluation:

The 2012 Visual Analytics Science and Technology (VAST) Challenge posed two challenge problems for participants to solve using a combination of visual analytics software and their own analytic reasoning abilities. Challenge 1 (C1) involved visualizing the network health of the fictitious Bank of Money to provide situation awareness and identify emerging trends that could signify network issues. Challenge 2 (C2) involved identifying the issues of concern within a region of the Bank of Money network experiencing operational difficulties utilizing the provided network logs. Participants were asked to analyze the data and provide solutions and explanations for both challenges. The data sets were downloaded by nearly 1100 people by the close of submissions. The VAST Challenge received 40 submissions with participants from 12 different countries, and 14 awards were given.

/pdf/vast-challenge-2012-visual-analytics-for-big-data-k5cvlhiez3.pdf

VAST Challenge 2012: Visual analytics for big data

The 2014 IEEE Visual Analytics Science and Technology (VAST) Challenge presented researchers with a single fictitious scenario: the disappearance of staff members of the GASTech oil and gas company on location on the island of Kronos. A group named the Protectors of Kronos (POK) was the prime suspect in the disappearance. Three mini-challenges and a grand challenge were offered. Mini-challenge 1 included multiple types of text data for participants to provide a timeline of key events and characterize the POK, mini-challenge 2 focused on individuals' movement and financial data for participants to provide patterns of daily life, and mini-challenge 3 featured real-time streaming social media and emergency service data for participants to provide hostage and kidnapper information. The grand challenge asked the participants to integrate results and generate a synopsis of events. The VAST Challenge received 73 submissions from 13 countries.

VAST challenge 2014: The Kronos incident

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VAST Challenge 2012: Visual analytics for big data

VAST challenge 2014: The Kronos incident