eScanner

Environmental Scanner - LT Product

 

What is it?

The eScanner is a tool for scanning open/public information sources for information on developments
and changes in external factors impacting the user organization and its business. Since it scans the
relevant external environment, it is also call an ‘environmental scanner’, giving rise to the product
name “eScanner”. We distinguish between two major kinds of applications of the eScanner: (1)
environmental scanning for early warning of threats or opportunities, and (2) environmental scanning
for discovering new knowledge kinds of situations of interest.

 

1. Environmental scanning for early warning of threats or opportunities

The data streams may be from multiple sources that may be of different kinds, depending on the
application domain. The information is extracted, harmonized, interpreted, etc., by the iExtractor
module.
Examples of kind of sources are data sensors, video sensors, transaction (business, financial) data,
news feeds, security information and intelligence (multi INF/INT) and investigative findings.

The first is for a user organization to monitor changes in the relevant external factors that may provide
a treat or an opportunity for the user organization. A general approach here is to monitor relevant
factors in the different dimensions of human society for indicators of change. The dimensions
considered are the political, economic, social (and demographic), technological, legal and
environmental dimensions, also call so-called PESTLE dimensions after the first letter of the
dimension name.

The FP7 project ePOOLICE (THIS) provided a proof-of-concept of such a scanning system as

part of the early warning system for the detection of

emerging organized crime threats as a tool for law enforcement analysts, as illustrated by the
figure on top.

2. Environmental scanning for discovering new knowledge about situations of interest

In this application, the relevant open/public data and information are scanned with the purpose of
maintaining an up-to- date rich picture of the situation area of interest for the Recognizer. Thus, the
focus is on gathering relevant information and mining it for knowledge about the situation area.
Examples of questions that this aims at answering are: What characterizes a kind of situation of
interest? Which varieties (subtypes) of the kind of situation are known, and what to look for to
recognize the occurrences of them?