=Paper=
{{Paper
|id=Vol-52/paper-19
|storemode=property
|title=The DoD Ontology Gap - Applications of Agent Technology in the Military
|pdfUrl=https://ceur-ws.org/Vol-52/oas01-richards.pdf
|volume=Vol-52
}}
==The DoD Ontology Gap - Applications of Agent Technology in the Military==
https://ceur-ws.org/Vol-52/oas01-richards.pdf
The DoD Ontology Gap - Applications of Agent
Technology in the Military
Mr. Dale W. Richards Mr. Mark Gorniak
Air Force Research Laboratory Air Force Research Laboratory
525 Brooks Rd 525 Brooks Rd
Rome NY 13441 Rome NY 13441
(315) 330-3014 (315) 330-7724
richardsd@rl.af.mil gorniakm@rl.af.mil
ABSTRACT are addressing many of the basic architecture and integration
This position paper describes ontology issues important to the issues, but have only scratched the surface of the semantic aspects
fielding of military agent-based systems. of these systems. The DARPA Agent Markup Language (DAML)
program has made a good start in this direction; but new
information systems, presumably agent-based, being proposed
General Terms must be ontologically aware and compatible from the beginning.
Management, Design, Standardization, Languages, Verification.
The DoD has made a strong push in some quarters for increased
Keywords emphasis on the use of XML and the related tagging of data. This
Ontology, Military, Information Systems, Intelligent Agents.
has not always been accompanied by a clear understanding that
there is more to the task than simply tagging everything in sight.
1. POSITION Properly tagged data is seen as the key to efficient information
The vision for future military information systems often includes and knowledge retrieval across multiple, and often dynamic, data
the integration of a vast number of existing heterogeneously and knowledge sources. Tagging must go beyond text to imagery
developed information sources to obtain a “big picture” view of and other media as well as more exotic data types such as
global events. The desire is to have a system of systems which is recorded waveforms and other scientific data sets. Real-time
dynamic in its configuration and owned by players from distinct automated tagging, and retrieval, is also desired.
political, geographic and service-specific units.
However, there are many unresolved issues relating to this use of
The reality of today is that many military information systems are semantically aware agent technology in larger military systems:
often stood up in conjunction with a particular mission or theatre 1. How to bring ontological awareness to specifiers and
of operations and involve the forced integration of "legacy" and developers of military systems?
"stovepiped" systems. Traditional software integration methods
are used to stitch together existing (legacy) systems either on a 2. How ontologically heterogeneous can new systems be,
one-to-one basis or via common, often overconstraining, and still be integrated into larger systems-of-systems?
data/interface standards. Heavyweight, often long in development How scaleable is the incorporation of additional
and outdated upon delivery, have become a de facto result. ontologies?
Operators of these systems continue to look to technology to make 3. How to efficiently incorporate legacy systems, including
those systems more responsive, less costly, more automated the tagging of legacy data, into newer systems, and
(autonomous) and requiring of less staffing systems of systems, which are ontologically friendly?
4. How to move the processes of ontology definition and
Future command and control (C2) systems are often described as data markup from an art to a science via rigorous
containing hundreds or thousands of active, autonomous methodologies? And thence to common practice via a
information components working with an even larger number of robust, established software engineering/programming
operational or engaged "fighting" units. The attainment of this paradigm?
goal is usually predicated on the development of a new class of 5. Will ontologies be defined/managed by programmers or
information system - clearly heterogeneous, often loosely coupled operators? And what will be their tools of choice?
- by policy or necessity, and most likely distributed - the same
6. How to quantify the amount of resources, e.g., labor
robust qualities promised by autonomous agents.
hours, calendar time, level of expertise, etc.; needed to
create ontologies and to mark up data sources (including
On going work in the area of agent infrastructure, e.g., DARPA validation)?
Control of Agent Based Systems (CoABS), and other programs ***