Moses Kamai
KM Practice Lead
Battelle Memorial Institute

James Paat
Chief Executive Officer
Sypherlink

Wednesday 9:45am - 10:45am

Level: Data Management - Intermediate

Local, regional and state agencies need to gather better crime-fighting intelligence by exchanging information among various organizations (e.g., courthouses, police stations, public safety) at all levels of government. These efforts, however, are typically difficult to implement because of the many challenges involved including interoperability issues, data ownership and privacy issues; and the time, cost and complexity required to understand the various data systems. Several large horizontal and vertical information integration efforts are underway across the US, each of which may be using a different approach or standard. As these networks develop; however, so will the need for interoperability between them. The inability to do this will result in more silos of information, and further integration challenges. NIEM was designed to create the means to seamlessly exchange information electronically between multiple governmental agencies. As comprehensive as NIEM is, such flexibility and extensibility can cause inconsistencies between how states implement the “standard”. In addition, as information sharing capabilities are enabled, it is vitally important to allow each organization the ability to maintain ownership and control of their data and continue to have the autonomy to decide what business, reporting and investigative applications they use. It is also critically important that each organization have the ability to pursue – or continue moving forward with – its own information exchange effort, and not be required to “rip and replace” existing systems. And, lastly, the task of bridging hundreds of formerly stove-piped systems is enormous. Every system has its own way of formatting data and defining the meaning of database terms. For instance, one system may use the term “FirstName” and another the term “FName” to specify a person’s first name in a database. In other cases, different systems may use an identical label to represent different data. “CNum” may mean “case number” in one system and “catalog number” in another. In order for this information to be shared, a process of discovering and identifying where relevant relationships exist between data sources must occur. Human effort and intuition is required to associate these fields and as a result the “mapping” process is traditionally a very resource intensive, error-prone, lengthy and costly process. Now, consider the fact that any data sharing effort will require potentially linking hundreds and thousands of databases and fields, and it is easy to see how cumbersome the task really is.

This session will describe best practices in jump-starting cross-agency data sharing and intelligence efforts while conforming to the National Information Exchange Model (NIEM), including one leading state’s proven approach. Specifically, participants will learn proven approaches to:

• Jump start cross-agency information sharing while conforming to and leveraging the NIEM standard.
• Accelerate the discovery and identification of relationships across disparate systems.
• Enable agencies to preserve their investments in existing technology and systems and secure future grant funding.
• Enable data flexibility for use in future data-sharing initiatives.
• Leverage available technology to virtually access various disparate data sources as if from a single query, to more quickly enable and support intelligence initiatives such as fusion centers.