The Problem: Information Overload
In many situations within an organization, a group of
collaborating knowledge workers work on a common task by accessing,
disseminating, summarizing and debating large amounts of information
available in documents, databases or the web. For example, a group of
business analysts needs to keep track of current trends and events and
assess how these affect the strategic objectives of their organization.
Likewise, a group of tax credit experts needs to assess projects
running within their organization in order to determine whether they
qualify for tax credits because of risks the projects involve. Finally,
a group of software engineers owning a large software system needs to
share knowledge about the source code, changes made to it, its history,
purpose and the like.
These groups have similar needs and similar problems too.
Foremost, they suffer from information overload. The explosive growth
of the web, the proliferation of internal and external reports and the
growth of print publishing have all contributed. A study
produced by the School of Information Management and Systems at the
University of California at Berkeley estimated the world's
production of information in 2002 would require approximately 5 billion
gigabytes of storage, and that this number is growing about 30% per
The surfeit of information coming from outside is not the only
problem. Even within an organization, information is often hard for
workers to access. In addition, experienced workers always accumulate a
body of tacit knowledge, which others in the organization would benefit
from having access to.
A Solution: A Shared Semantic Model
Our research is founded on the premise that such groups of
collaborating knowledge workers have a shared semantic model of the
application they are working on. For example, a group of strategic
business analysts have a shared model of the strategic objectives of
their organization, and a group of software engineers have a shared
model of the structure and purpose of their software system. EXIP
(the Executive Information Portal) is a knowledge management portal
that adopts such shared semantic models as an organizing principle.
Knowledge from both internal sources (presentations, spreadsheets,
reports, emails, etc.) and external sources (web pages, news feeds,
etc.) is then classified according to the semantic model.
Classification is a semi-automatic process, using information retrieval
techniques. Complete documents are classified according to the semantic
model, but classification can also be more fine-grained; for example,
the paragraphs that make up a report can be classified individually.
The distribution of knowledge is enhanced by the fact that the
model is common to the workers that use it, since this fact serves to
make knowledge accessible and to facilitate its transfer. In addition,
there is a system of direct and indirect notifications when an item or
event of interest occurs. Knowledge retention is also enhanced, first
because EXIP serves to store all knowledge relevant to a group and so
provides a central location to store and find knowledge. Also, implicit
knowledge, such as annotations, ratings of documents and
recommendations, is captured.
Research continues in several areas, including into the use of
natural language processing techniques combined with information
retrieval techniques for the classification of knowledge, model
analysis techniques, the construction of semantic models for new groups
of workers, and the relationship of EXIP to the Semantic Web.
This project is done in collaboration with Techné Knowledge Systems.