GeoTagging Photographs |Sanjay

Rana

Contents

• Introduction

• Current Streams of Research

• Cartography of Tag Clouds• Topology of Tag Clouds

• Future Directions

“A picture is worth thousand words.”Fred Barnard,

An advertising manager in the early 1920s

Introduction

•GeoTagging is the process of assigning geographical information metadata, called geo-tags, to various media e.g. photographs, video, websites etc.

• A tag is a term/label/keyword that describes some property of an object. It probably - a) originated from a Scandinavian/German word meaning point/prong/spike/prickle/thorn, b) is a cognate of tack (Source: etymonline.com).

Introduction…

Tags•lyon •france •2005 •night •october •geotagged

Machine tags (2) •geo:lat=45.75 •geo:lon=4.82

Source: http://www.flickr.com/photos/nodomain/57506095/

GeoTags

Introduction…• Some observations:

– The primary purpose of GeoTagging is to assign suitable identifiers to a photograph so that searching in a large catalogue of photographs can produce relevant results quickly.

– Therefore as a concept, it is basically same as the focus of large body of research on Geographical Metadata e.g. FGDC in the last 40 years, and that of broader Archival Science of over several hundreds of years and perhaps even thousands of years.

– So, what's different about GeoTagging?

Introduction…• GeoTagging is different

because:

– Crowd-sourced / Volunteered Geographical Information

– Strongly linked to online community (NeoGeography)

– Free-form text with very nominal formatting structure except for the geographical coordinates

– Inconsistent quality

Introduction…

• Tags are valuable because they :Help to generate User-

Oriented and User-Relevant indexing of information in databases i.e. Ego-Centric Design & Mental Map.

Reveal fascinating insights into the sociological behaviour & semantics of participants – Vernacular Geography, Folksonomy, Narrative Geography, Storytelling, Locative Media.

Introduction…

• Aim of this presentation is to propose:– Cartographical Approach set in a – Graph-Theoretic Framework that can be used primarily by :– System Designers &– Exploratory Users for displaying and analysing relationships

between all Tags i.e. not only geo-tags.• Disclaimer: In progress ideas..

Contents…

• Introduction

• Current Streams of Research

• Cartography of Tag Clouds• Topology of Tag Clouds

• Future Directions

Current Streams of ResearchBroadly three streams of research

1. Creation of Tags2. Visualisation of Tags3. Analysis of Tags

Current Streams of Research…• Creation of Tags

– Largely technological Topics:

– Hardware related research:

• Robust integration of GPS adapters, cameras, handheld devices, desktop devices etc to create a seamless approach.

– Software related research:

• Automated association of tags using geographical and image parameters, cool mash-ups, storage standards (EXIF, ICBM, RDF, GeoBloggers, GeoHash, FlickrFly…).

Current Streams of Research…• Visualisation of Tags

– Ever increasing ways to display the tags and relationships between tags.

• Active interest from researchers from various disciplines including Information Visualisation, HCI, Graphic Arts, Social Sciences,…

• ManyEyes Project by IBM.– Most basic approach involves a static 2D plot where

tag’s font size is proportional to its count/frequency in the database. Example

– Advanced visualisations are animated and interactive and generally display more complex relationships between tags. Example.

– Seen as an viable alternative to navigation of large databases.

– However, no widely accepted guidelines or approach to generate a tag cloud. For example,

Current Streams of Research…• Which of the following colour

classification is more informative?

Current Streams of Research…• Which of the following label styles is

more informative?

Current Streams of Research…• Analysis of Tags

– Implicit ways of organising the tags into meaningful clusters i.e. unlike the explicit ways, which involve user-led exploratory visualisation

• Ordinary frequency distributions.• Semantic Similarity and Semantic Relatedness

measures– Various statistical, probability etc. type measures for

measuring relationships between tags - kind of like Google’s ranking. For example,

– Showing only few representative photos of a city from millions of photos.

– Recognising that “Lift” and “Elevator” are similar

– Understanding social networking and sociological profiling of users.

Contents…

• Introduction

• Current Streams of Research

• Cartography of Tag Clouds• Topology of Tag Clouds

• Future Directions

Cartography of Tag Clouds

• Hypothesis:– Tag Clouds are essentially a sort of

Topological Cartograms. Example– Tag’s text label is analogous to the

geographical feature or symbol.

• Implications of the hypothesis:– Availability of vast bank of design

guidelines and usability studies in Cartography to represent Tag Clouds. For example,

Cartography of Tag Clouds…• The optimal number of thematic classes

in a map was found to be 7+2 (Miller)

Application of Cartographic Principles

Cartography of Tag Clouds…• Other (but not all) useful Cartography

Concepts:– Techniques of Cartographic Abstraction and

Generalisation.– Visual Variables for both Static and Dynamic

Maps e.g.:– Choice of Colour Classification– Choice of Font Face/Size/Weight or using Symbols– Brushing to show relationships between two

representations.– Reducing Clutter and Redundancy

– Multi-modal e.g. Haptic visualisation, sounds, etc.

• Cartography Cube - A benchmark to evaluate a Tag Cloud representation?

Cartography of Tag Clouds…

User Audience

Interaction

Data Relation

s

Public

Private

Low

High

Unknown

Known

Contents…

• Introduction

• Current Streams of Research

• Cartography of Tag Clouds• Topology of Tag Clouds

• Future Directions

Topology of Tag Clouds

• A Tag Cloud can be represented as an:– Undirected– Non-Planar Graph G=(V,E) where

V = {Tag1, Tag2, Tag3,…}; E = Some connectivity basis e.g. co-occurrence, semantic relatedness etc.

• Several interesting graph-theoretic measures can be derived to visualise and analyse the structure of the tag clouds.

• For example,

Topology of Tag Clouds…

• What is the least number of tags and photos that will represent the contents of all the photographs in the database?

• Is the Tag Cloud graph a Scale-Free Network i.e. are there any patterns in the database of photographs?

Sand (60%) Aquarium (22%)

Beach (40%)

Palm Tree (2%)

Yacht (25%)

0

600

0

20

600

90

Frequency

Co-occurrence

10

0

Contents…

• Introduction

• Current Streams of Research

• Cartography of Tag Clouds• Topology of Tag Clouds

• Future Directions

Future Directions…

– Technological• Instrument accuracy/portability/affordability,

data formats, System scalability (massive information).

• Metadata Standards.

– Conceptual• Exploration and Application of Geo-Tags• Risks to the Netizens

– Misinformation - Queen storming out or walking in.– Google search collapse by incorrect tagging of all

links to be bad.– Privacy - Revelation of personal preferences.

• In summary, it is proposed that the visualisation and analysis of Tag Clouds can be formalised by using the principles of Cartography and Graph Theory.

• Thank you!

Simple Tag Cloud

Source: ManyEyes Project

Keywords For Photographs Of Dubai

Advanced Tag Cloud

Elastic Tag Maps by Moritz Stefaner

Source: well-formed-data.net

Cartogram

Number of Internet Users in 2002

Source: WorldMapper.Org

Visual Variables

Source: How Maps Work (MacEachren, 2004)

Dynamic Maps

Source: GeoVista, University of Pennsylvania

Scale-Free Network

Is it the case that there are a few tags that exist in a lot of photographs while most photographs have dissimilar tags – Scale Free Network and Small-World Networks?

Misinformation

How to Lie with Maps (Monmonier 1996) = How to lie with Photographs or How to lie with geo-tags…?