Visualisation of Animal Tracking Data James Walker BCUR - 19.04.11.

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Visualisation of Animal Tracking Data James Walker BCUR - 19.04.11

Transcript of Visualisation of Animal Tracking Data James Walker BCUR - 19.04.11.

Visualisation of Animal Tracking DataJames Walker

BCUR - 19.04.11

Introduction to Data

Visualisation

What is Data Visualisation?• A tool that allows the user to gain insight into

data. e.g. a graph

• Visualisation used on a day to day basis – Weather, maps... Etc.

• Data set sizes are ever-increasing making a graphical approach necessary.Data explosion!

• Abstract Data▫ Any data from a database!▫ Doesn’t exist in a spatial domain –

Our job to place it in space.

Information Visualisation

Visualisation of Animal Tracking

Data

Motivation•Biologists at

Swansea University use animal tracking devices

•Record real animal movement

•Some animals are not observable especially underwater (even with GPS!)Device attached to a penguin

How does it work?•Contain tri-axel

accelerometers •Accelerometer data can be

used to extract▫Orientation▫Movement vector

Its hard to extract these!!•Contain a tri-axel compass

– Used for determining an animals headingA Daily Diary

device

Devices contd...•Contain sensors to

determine the locale environment. Such as:▫Temperature▫Pressure▫Light intensity▫and More! Up to 13

sensors...•Small – About the size of a

match box.•Can record data for up to

4 days.

Benefits• Indirectly observe animals• Discover new animal behaviours (example)• Gain more insight into animals – Energy

expenditure

Whale Shark – Previously couldn’t be observed

Data AnalysisData from a Bird displayed on time intensity plots:

•Wave patterns represent animal activity•Typically 5 plots combined to determine a behaviour•Showing approx 1,000 data items – Data set consists

of 800,000 items. 800 Slides to analyse

The Problem...•Hard to combine several data attributes

and translate into an animal movement•Relies on the skill on biologist to extract

data from plots – Need years of experience

•Error prone!

Data sets can contain over a million entries.This is a massive challenge to biologists!

Large 2D time plots take a long time to analyse. Potentially days!

Our Solution!

Project Aims•Make data analysis less reliant on skill of

biologists.▫ Intuitive visual metaphors for perceiving the data.

•Combine multiple attributes together into one visualisation.▫ More knowledge based experience.

•Enable pattern finding capabilities.▫ Gain more knowledge from the data – Common

animal orientations.

•Quicker data analysis.▫ Assisting biologists in identifying areas of interest.

Demo of Solution

Project Aims - Recap•Make data analysis less reliant on skill of

biologists.▫ Visual metaphors for perceiving the data.

•Combine multiple attributes together into one visualisation.▫ More knowledge based experience.

•Enable pattern finding capabilities.▫ Gain more knowledge from the data – Common

animal orientations.

•Quicker data analysis.▫ Assisting biologists in identifying areas of interest.

Future WorkBiologists are currently working on a virtual reality software. Animal is mapped into Google Earth Environment – Location can be inferred from compass data, conditions can be set using environment sensors.

Conclusion• This new technology is pushing the frontiers of

research into animal behaviour. New discoveries have already been made (e.g. Whale Shark).

• Aims have been achieved to enabled a better and more knowledgeable experience in data analysis.

• Important research area as indirectly observing animals is a key problem in many animal research areas.

• Firm belief that as Daily Diary devices get smaller and more advanced they will becoming more prevalent.

AcknowledgementsImages:1. Rolex Awards/Jürgen Freund

URL: http://rolexawards.com/en/the-laureates/rorywilson-home.jsp2. Conservation Magazine - Vol. 8, No. 1

URL: http://www.conservationmagazine.org/2008/07/wildlife-flight-recorder/

Research Papers:3. Visualisation of Sensor Data from Animal Movement

Edward Grundy2. Identification of animal movement patterns using tri-axial

accelerometryEmily Shepard

Supervisor:3. Bob Laramee