NASA SBIR 02-1 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER:02- E4.02-9651 (For NASA Use Only - Chron: 022348 )
SUBTOPIC TITLE: Advanced Educational Processes and Tools
PROPOSAL TITLE: Rich Annotation of Images

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Innovative Decision Technologies, Inc.
9000 CYPRESS GREEN DR, 107
JACKSONVILLE , FL   32256 - 5509
(904 ) 636 - 6374

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Pramod Jain
pramod@indent.org
9000 CYPRESS GREEN DR, 107
JACKSONVILLE , FL   32256 - 5509
(904 ) 636 - 6374

TECHNICAL ABSTRACT (LIMIT 200 WORDS)
Objective is to significantly enhance the ability to describe, catalog, search and retrieve images through the use of rich annotations (RA) of features in an image. Traditional approaches rely on text-based notes and keywords in metadata; proposed approach will use annotation layer (AL). AL contains drawings and icons to mark features, and domain specific properties to describe the features. Properties of features are described using a structured format with controlled vocabulary. AL is created in a web browser-based Rich Annotation Workbench (RAW) using Scalable Vector Graphics.

RAW will foster collaboration between earth scientists and educators, and foster productive use by novice users through ability to: a) overlay multiple AL on image, b) share, reuse and extend domain specific annotation palette.

RAW has commercial applications in: Digital Asset Management, telemedicine, and e-learning.

Approach is to: create domain specific annotation palettes; enhance our existing iAnnotate platform to create RAW; define RDF-based metadata model for RA; integrate with existing Earth Sciences digital library metadata repositories of NASA-GCMD and DLESE.

Anticipated results: Phase I, prove feasibility that RA of features can be metadata for images; Phase II, enhance and commercialize RAW to be an annotation service in a variety of domains.

POTENTIAL COMMERCIAL APPLICATIONS (LIMIT 150 WORDS)
National Science Digital Library (NSDL) can use web-based RAW for authoring image based content by describing features of an image in annotation layers. This will significantly increase the use of digital images in education material at all levels.

Sharable Content Object Reference Model (SCORM) compliant Computer-Based Instruction, Training and Testing. Annotation system can be applied to instruction and testing in areas that involve image analysis and interpretation, like medicine, reconnaissance, and meteorology.

Tele-medicine systems can use annotation for remote diagnosis, treatment and monitoring of patients based on images captured at remote locations. RAW can facilitate rich communication between specialists, general physicians and patients.

General-purpose web-based annotation service for annotating images. RAW will be a cost effective solution for businesses that deal with paper-based blueprints: architects, builders, property managers and real estate companies. These businesses will benefit by keeping track of dynamic data electronically as annotations versus marking up paper-based layouts.

POTENTIAL NASA APPLICATIONS (LIMIT 150 WORDS)
Annotation service to Global Change Master Directory (GCMD) of NASA and ADEPT/DLESE/NASA (ADN).

GCMD may use RAW to create richer feature based metadata for images in their collection. RAW will provide a significantly more effective capability to catalog, search and retrieve images because it uses a structured format and controlled vocabulary to describe the features. The ability of annotation layers to visually describe features in an image can be very appealing to users. In addition, the task of creating such rich metadata for images is made less onerous.

ADN may use RAW to foster collaboration between earth scientists and educators. Web browser based user friendly tool with domain specific annotation palette will make the task of creating education content less daunting. Educators will be able to search using a rich set of criteria on annotation properties, and create new annotations on top of annotations done by previous users.


Form Printed on 09-05-02 10:10