The AKTiveSA project is using Semantic Web technologies to support information fusion and enhanced situational awareness in a simulated humanitarian relief scenario. We have developed an application that shows how situational awareness can be supported during humanitarian relief situations; often occurring alongside military conflict. Semantic Web technologies provide new opportunities for harvesting information from numerous, disparate and often heterogeneous information sources and can be used to better support complex knowledge fusion

Carr, Leslie

Russell, Alistair

schraefel, m.c.

Shadbolt, Nigel

Smart, Paul R.

Wilson, Max L.

English

Southampton (e-Prints Soton)

ISWC 2005 Poster Paper    PID-55 IAM Research Group  1  University of Southampton Abstract The  AKTiveSA  project  is  using  Semantic  Web technologies to support information fusion and en-hanced situation awareness in a simulated humani-tarian relief scenario. We have developed an appli-cation that shows how situation awareness can be supported during humanitarian relief situations; of-ten occurring alongside military conflict. Semantic Web  technologies  provide  new  opportunities  for harvesting  information  from  numerous,  disparate and  often  heterogeneous  information  sources  and can be used to better support complex knowledge fusion. 1  Introduction Humanitarian relief is an increasingly pressing topic - there is the need for more advanced knowledge resources, so that resource  spread,  meteorological  information  and  a  whole plethora of information can be considered in order to pro-vide the most effective relief [Choudhury, 2005]. Most no-tably, the temporal development of events is becoming criti-cal to the success of modern operations. The term that is central  to  the  majority  of  recent  discussions  is  ‘situation awareness’; this was well defined by Endsley [1988]:    “… the perception of elements in the environment with a volume of space and time, the comprehension of their meaning and the projection of their status in the near future.”  These  days,  the  problem  lies  in  filtering  and  aggregating these vast resources in order to find the most relevant and pertinent information. In this project we aim to show how the Semantic Web initiative1, and its developing technolo-gies, can address the problem of information overload, by providing a more expressive context-orientated medium for information filtering and triage. Central to our argument is that semantic technologies are invaluable to the knowledge-based fusion of physically disparate and semantically het-erogeneous information. 2  System Functionality The prototype software, shown in Figure 1, has six functions that  are  built  upon  semantic  technologies.  Greater  detail about the system can be found in [Smart et al, 2005] and is presented briefly in Sections 3, 4 and 5.                                                   1 http://www.wc.org/2001/sw, W3C Semantic Web Website Figure 1: Interface of Prototype Software showing Semantic In-formation Overlaid onto the Google Earth Visualisation. 2.1  Information Retrieval This functionality is concerned with both active and passive forms of harvesting information. One may wish to actively gather information from heterogeneous information sources such as news feeds, web pages and even tactical data-links; intelligent  screen-scraping  mechanisms  exist  in  projects such as MIT’s Piggy-Bank2 and can be easily supplemented by users. Semantically stored, this information has greater context and relevant information can be discovered through developing  semantic  browsers;  the  interface  is  discussed later in the paper. Passively, one may receive email notifica-tions or updates from external agent software; with semantic mark-ups, this information can be automatically processed. 2.2  Information Triage Information triage is as important to information retrieval. Semantic annotations allow information to be accessed, fil-tered  and  sorted  automatically  by  agents  and  the  central system. Further, this information can be filtered according to the profile of the end user. Those making important deci-sions can, therefore, receive different information to those in the field or even those performing continued research. 2.3  Information Fusion This is concerned with the dimensionality of all the informa-tion  available.  Not  only  is  the  content  important,  but  the validity of  the  source, the accuracy of its content and its provenance  are  all  important  when  making  decisions. Through  semantic  encoding,  this  information  can  be  ac-                                                 2 http://simile.mit.edu/piggy-bank, SIMILE | Piggy Bank Using Semantic Web Technologies to Support Enhanced Situation Awareness Max Wilson, Alistair Russell, Paul Smart, Nigel Shadbolt, Leslie Carr, m.c. schraefel School of Electronics & Computer Science University of Southampton Southampton, SO17 1BJ, UK {mw1, ar5, ps02v, nrs, lac, mc}@ecs.soton.ac.uk ISWC 2005 Poster    PID-55 School of Electronics and Computer Science  2  University of Southampton cessed and represented by the system, as it is provided to the end user; semantic inference allows the system to allocate such meta-data based upon stored context about a source. 2.4  Knowledge Processing Aside from interactions that the user is concerned with and aware of, the system should initiate its own action in certain situations.  An  example  of  this  is  inference.  For  example, with knowledge about an earthquake and its size, the system can automatically estimate the size of response required and even initiate contact humanitarian relief agencies.  2.5  Information Dissemination As mentioned above, an important measure of the system is its ability to coordinate with external agencies that will be involved with the humanitarian relief effort. This entails the timely notification to those involved with the support effort as well as the facilitation of communication links between cooperating agencies. This process will occur through the system’s interoperation with external agents and would not be possible without the system’s semantic understanding of each agent and its role within the system. 2.6  Interaction and Visualisation Visualisation capabilities are clearly important in terms of enabling  improved  situation  awareness.  The  problem  of information overload must be considered as the system pre-sents information to users. Similarly, the user’s platform for presentation must also be considered. 3  Scenario In example of the above terms, we consider a flood scenario triggered by earthquake damage to a damn. For information retrieval, sources such as NEIC may provide automatic noti-fication of the earthquake size and location; further informa-tion about the flood may be drawn from semantically anno-tated news reports. Information fusion provides automatic filtering of unrelated sources and can connect related infor-mation such as water level and death count. Triage would then prioritise these sources based upon aspects like relevant content and associated trust. Knowledge processing would allow the system to develop basic procedures and organise potential resources for a response; the homeless would re-quire both shelter and blankets. Dissemination services al-low third parties, like civil relief agencies, with whom the sharing of newly inferred information is extremely impor-tant. Device-appropriate visualisations can then be provided for various users; rescue units in the field may be using a small  mobile  device,  whereas  agency  headquarters  may monitor the developing events over multiple large displays. 4  Use of Technology 4.1  Knowledge Stores This system comprises a very substantial knowledge base, built upon a number of ontologies; we already have over 1500 classes, 100 properties and 500 individuals. Each of these  is  currently  in  development  and  is  being  refined  in accordance with our growing understanding of the knowl-edge infrastructure of the problem domain. OWL ontologies have been used to describe this information space [Antoniou and Harmelen, 2003], whilst 3Store has been used to store the RDF information [Harris and Gibbins, 2003]; this stor-age system uses an RDQL interface for information retrieval and semantic querying. At this time there are 169,000 stored instance triples. Inferential reasoning over this information is being provided by JESS [Friedman-Hill, 1997]. 4.2  End User Software The  existing  demo  co-opts  the  visualization  capabilities provided by Google Earth3. The system can make inferences over the existing knowledge base as new information is in-cluded. As a result, temporal predictions can be made of the unfolding of events; Google Earth provides a spatial visuali-sation for the event, including these changes over time.   Detailed investigation into the user interface is just begin-ning, and many forms of exploration and data visualisations are being considered. Currently, a hierarchical browser for exploring the ontologies has been included. However, both mSpace, a columnar approach, and Haystack, a faceted ap-proach, provide lightweight but high levels of access to se-mantic  information4.  In  conjunction,  other  multi-platform implementation options are being considered. 5  Conclusions Whilst this project is in the early stages of development it is showing how semantic technologies can be applied to sup-port situation awareness in an area of pressing need.  References [Antoniou  and  Harmelen,  2003]  Grigoris  Antoniou  and Frank  van  Harmelen,  Web  Ontology  Language:  OWL. Handbook on Ontologies, S Steffen and R Studer, Eds. Berlin: Springer Verlag, 2003.  [Choudhury, 2005] Siddiqur Rahman Choudhury. Cluster 5: Preparedness for effective response – Closing State-ments. World Conference on Disaster Reduction, 2005. [Endsley, 1988] Mica Endsley, Design and evaluation for situation awareness enhancement. Paper presented at the Human  Factors  Society  32nd  Annual  Meeting,  Santa Monica, California. 1988.  [Friedman-Hill,  1997]  EJ  Friedman-Hill,  Jess:  The  Java Expert System Shell. Sandia National Laboratories, 1997. [Harris and Gibbins, 2003] Steve Harris and Nicholas Gib-bins, 3store: Efficient Bulk RDF Storage. Presented at The 1st International Workshop on Practical and Scalable Semantic Web Systems, Florida, USA, 2003. [Smart et al 2005] Paul Smart, Nigel Shadbolt, Leslie Carr and  monica  schraefel.  Knowledge-Based  Information Fusion for Improved Situational Awareness. In Proceed-ings of The 8th International Conference on Information Fusion, Philadelphia, USA.                                                  3 http://earth.google.com – Google Earth 4 http://echo.ischool.utexas.edu/~anuj13/semweb_UI.htm - User Interfaces for Semantic Web Applications ISWC 2005 Poster    PID-55 School of Electronics and Computer Science  3  University of Southampton Explanation of Demonstration  An  early  prototype  of  an  application  will  be  presented, demonstrating the humanitarian relief scenario briefly dis-cussed in the short paper above; a screen shot is also shown above. The core capabilities labelled within the paper are each exampled through the demonstration, along with four key interactive capabilities within the development of such a scenario:  1)  The opportunistic exploitation of military assets, for example, the ability of military agents to ad-vertise  their  current  status,  capabilities  and  re-quirements in order to allow for cross-force inte-gration and self-synchronization. This capability is  highly  relevant  to  future  capability  require-ments as documented in the UK Government’s HLOC5. The specific aspect of the scenario rele-vant to this capability concerns the coordination of strategic air assets and land components with respect to reconnaissance activities.  2)  Support  for  anti-fratricide  measures  and  avoid-ance of blue-on-blue engagements via increased situation awareness about the disposition of mili-tary assets Situation awareness in this case will be  promoted  by  the  ability  of  diverse  military agencies to share information in support of the formation of a CROP (Common Relevant Opera-tional Picture).  3)  The ability to monitor the movement of neutral entities, such as relief convoys and refugees, so as  to  avoid  inadvertent  military  attacks  and minimize  collateral  damage.  This  capability  is particularly  relevant  during  the  pre-deployment (the acquisition and assimilation of aid supplies) and the deployment (the transport of supplies to affected region and the distribution of humanitar-ian aid) phases of a humanitarian aid operation. It is also important in terms of avoiding attacks on refugees, which might otherwise have politi-cally aversive repercussions and undermine the struggle for ‘hearts and minds’.  4)  The ability to plan the relief effort in terms of identifying requisite humanitarian aid resources (i.e. those specifically required to deal with the flood crisis), identifying the source of the sup-plies (i.e. the agencies, organizations or countries responsible for the provision of supplies), decid-ing what transport routes are appropriate for the transportation of aid supplies and the constraints that apply to such transport options (e.g. the vi-ability  of  roads  in  terms  of  structural  integrity and security).                                                  5 UK Joint High Level Operational Concept: An Analysis of the Components of the UK Defense Capability Framework, Joint Doc-trine and Concepts Centre (2005), Ministry of Defense, UK.  In terms of our prototype, the demonstration also illustrates: our access to the semantic information through visualizing the ontology and its structure; the exampling inclusion of the  Google  Earth  visualisation  –  utilising  its  altitude  and resolution  capabilities;  and  the  development  of  semantic queries.  The advent of Semantic Web technologies has facilitated the realisation of the capabilities discussed above. We thus see such technologies as a key enabler with respect to enhanced situation  awareness  in  joint  civil-military  operations.  The use of these technologies is highlighted within the demon-stration. 

EJ Friedman-Hill, Jess: The Java Expert System Shell. Sandia National Laboratories,

Grigoris Antoniou and Frank van Harmelen, Web Ontology Language:

Leslie Carr and monica schraefel. Knowledge-Based Information Fusion for Improved Situational Awareness.

Mica Endsley, Design and evaluation for situation awareness enhancement. Paper presented at the Human Factors Society 32nd Annual Meeting,

Siddiqur Rahman Choudhury. Cluster 5: Preparedness for effective response – Closing Statements.

Using Semantic Web Technologies to Support Enhanced Situation Awareness

Using Semantic Web Technologies to Support Enhanced Situation Awareness

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