Birds of Feather Session 4:Context areas beyond traditional CS and GIS

Participants (in alphabetical order):Peggy AgourisArie Croitoru

Pete DoucettePasquale Franzese

Michael GouldJames Pustejovsky

John Schnase

Context areas (1)

• Context areas:– areas in which research is carried out that can be linked

with the current geospatial and geotemporal research– Includes:• Earth & atmospheric sciences• Defense & homeland security• Forestry• Agriculture• Biology• Arts

Context areas (2)• A better interface with the following areas is

needed:– GUI interface design / psychology– NeuroGeoSci (brain maps)– Artificial intelligence and machine learning,

particularly in the context of modeling– Gaming– Linguistics– Information science/library science– English studies/history– …

Some observations on context areas

• Very different missions, goals and expectations

• The context of scale differs significantly• We should promote spatial thinking across the

board:– Developing spatial thinking for everyday activity

Why isn’t it happening?

• There are some significant barriers:– Semantics– Education and skill level– Data handling/sharing/ownership– Trust– Lack of incentive– Tendency towards multidisciplinary rather than

interdisciplinary

The role of education• The current approach in education plays a

fundamental role in creating these barriers!• A need to create a common knowledge/skill-set

for spatial thinking – it has to be a bottom up process.

• We need to define the “fundamental laws” of the domain, e.g.– DBs– Vector processing– Raster processing– …

An emerging opportunity

• Google earth as a stepping stone– Creating a broad awareness– Creating new needs and demands– Brings coherence to the field

The evolving funding landscape

• Currently, Geospatial/GeoTemporal research is not a distinct funding category.

• A need for a new context-driven funding model. – Context should not be eliminated.

Environmental change As a case study (1)

– increase in wildfires–Invasive species–Response requires rapid decision

making, integration of data etc.

Environmental change As a case study (2)

• Requires a suite of tools that has not been fully developed:

• Change detection• Modeling/studying/predicting phenomena• Multi-scale analysis• Temporal analysis• Uncertainty

Environmental change As a case study (3)

– There is a suite of tools that does not exist:• Rapid deployment of data without continuous reliable

communication• Communication = computer + non-computer (enabling

human communication)

– Need to support various users with various levels of skills

– Need to educate users/funding agencies/professionals.