Professor Simeon Yates
Director of the Culture, Communication and Computing Research Institute, Sheffield Hallam University
Project Odyssey: investigating European gun crime
Project Odyssey, a European Union funded research and development project to develop a ballistic crime data sharing system, uses SAS® software for data integration and intelligent data mining of large sets of ballistics and crime information data. The SAS software plays a key role in helping investigators quickly and efficiently find answers to queries about firearm crime from a central project database.
Project Odyssey, part funded under the European U framework 7 programme and coordinated by Sheffield Hallam University (SHU), was set up to explore the challenges of establishing a pan-European ballistics and crime information network and to propose solutions including a demonstrator prototype system.
Throughout Project Odyssey, SAS has provided extensive training and technical support as well as help in implementing its data mining software on servers at SHU's Sheffield headquarters.
Professor Simeon Yates
The project partners include Atos Origin, Forensic Pathways Ltd, EUROPOL, XLAB, SESA, Politecnico di Milano, National Ballistics Intelligence Service, Royal Military Academy, North Yorkshire Police and An Garda Siochana, D.A.C. - Servizio Polizia Scientifica. The project had a range of key technical goals, several of which involved the use of industry leading data mining and data integration software from SAS .
The main objective was to develop a database through which gun crime data could be shared with relevant stakeholders across Europe. The system needed to be able to look across all of the appropriate databases. At the same time, the tools and techniques used for uploading, downloading and sharing data had to be secure - and sensitive data kept invisible to certain groups.
The second important technical goal was to allow individual police officers, forensic scientists and other stakeholders to enter new data, gauge whether it is connected to any existing data across Europe, to use SAS software to enter queries with regards to information in their home databases and see if they could find relevant matches across Europe.
These queries, typically relating to firearm crime, can then be left indefinitely in the system, which checks at regular intervals to see if new data coming into the system, the discovery of a weapons cache in Germany, for example, has changed the answers to those queries.
The third level was to look for patterns regarding the kinds of firearms that are being used in crimes in Europe. This would allow cross-region views of gun crime patterns and answer queries such as: are gun crime patterns in Eastern Europe being replicated in Ireland or are there connections between criminal gangs in the two regions? Again, the SAS data mining software had a key role to play in discovering relevant patterns and helping analyze peaks and troughs in the level of gun crime in different countries. This information could then be made available to national police forces or region-wide organizations such as Europol.
How it worked
The SAS software was used throughout the project as part of the back-end project platform to allow SHU, in particular, to carry out intelligent data mining of the large data sets that were generated.
SAS was used to manage data uploads and to mine the data repository looking for patterns and hidden structures. The data mining and knowledge extraction modules need to pre-process the database data in order to extract information for later use.
The SAS tools supported answering queries that were made of the system. Typically, these were at three different levels. An initial query would draw basic parallels between specific crimes; a second would query features of those crimes and a third more general query would draw parallels between types of crimes and types of weapons, people or places.
This information helps police in following a range of specific lines of enquiry, in addressing patterns of behaviour that they are starting to see and need to understand and finally in drawing up strategies such as preventing guns from being manufactured in one country and subsequently being used for gun crime in another. The SAS backend software helped here by enabling investigators to find this kind of information quickly and efficiently.
To ensure the system was made secure, SHU first defined the types of data that police forces typically use in the gun crime domain. It then developed a domain specific language, called the Odyssey Semantic Language (OSL). All queries and data entries that went into the system had to be encoded using OSL and only validated OSL statements would be processed All results were also translated into OSL to be processed by the Odyssey User Interface. Data mining queries presented in OSL would be processed and sent to the SAS back engine allowing users to securely explore connections between individuals, firearms and specific crimes.
A key feature in the fight against gun crime is to identify large-scale patterns and undertake data mining to highlight key issues. The ability to pinpoint the use of a particular type of weapon or ammunition in crime across Europe can help reveal the source of the arms and ultimately help cut off its supply through police, border security or international political and economic action.
The SAS data mining tool has been instrumental in helping the project team to achieve this. In particular, it has had a key role to play throughout the project in helping extract and identify meaningful data that the team could use to determine the distribution of gun crime. Ballistics data that appears to map to similar incidents can be flagged up instantly to show connections between crimes, allowing agencies to share and cross-reference information based on more accurate evidence. Similarly, agents in other geographies are automatically alerted to matches on gun and bullet signatures so they can build a profile of crime networks that may affect their area.
"The benefits of working with SAS extend beyond the functionality of the solutions. For Project Odyssey in general and for us in particular, one of the key advantages of using SAS software was that it was backed by one of the world's leading and most highly respected software companies," says Professor Simeon Yates, director of the Cultural, Communication and Computing Research Institute at Sheffield Hallam University. "Throughout Project Odyssey, SAS has provided extensive training and technical support as well as help in implementing its data mining software on servers at SHU's Sheffield headquarters."
Develop a database through which gun crime data could be shared with relevant stakeholders across Europe. Tools and techniques for uploading, downloading and sharing data had to be secure. Another key focus was to allow individual police officers, forensic scientists and other stakeholders to enter new data and gauge whether connected to any existing data across Europe.
SAS software used as part of the back-end of the project platform to enable intelligent data mining of large data sets generated. SAS used to manage data uploads and mine the data repository looking for patterns and hidden structures.
A key feature in the fight against gun crime is to reveal large-scale patterns and undertake data mining to pinpoint key issues. Highlighting such patterns can help reveal the source of the arms and ultimately cut off the supply. The SAS® data mining tool has been instrumental in enabling the project team to achieve this.