We are all generating more and more data every day, which is creating a major challenge for government agencies looking to gain an active insight into a range of topics and better manage their growing data mountain with new technology solutions.

At the same time, there has been a major change in the way citizens expect to use the always-on 24/7 technology they have access to. This flexibility and freedom has put pressure on government to improve digital public services to meet demand.

This unprecedented variety and volume of data being produced provides a real opportunity for government to drive better decision-making around policies and programs and improve operational efficiency. But government faces the bigger problems of constricted budgets and staff shortages.

The answer could be in relational database software, which links information into searchable tables. Relational databases are easy to set up, access and extend, but they struggle to cope with the large amounts of data that are arriving and being produced by federal agencies.

What is required is technology that can uncover relationships: the connections between people, places and events that make up the real world. Public services depend on being able to spot these connections for improved service delivery in a region that might require extra mobile healthcare professionals to promote public health, for example. The tool that can help is the graph database.

Graph databases are navigated and searched by following relationships. This type of storage, navigation and search is not possible with relational databases as they are constructed from rigidly defined tables, so it is impossible to follow connections wherever they may lead.

With graph databases, civil servants can start to see patterns emerge by connecting multiple legal, welfare and demographic datasets. They can, for example, search how many children are on a school meals program in a certain neighborhood.

Real world example

U.S. Immigration and Customs Enforcement, with the help of visualized relationship connections in real time, could work on individual cases of potential interest to border control.

For example, one country we’re working with has a high rate of immigration, but doesn’t give working or residence rights to everyone crossing its borders. That means it can ask people to leave, but with them re-presenting with a slightly different name on their application. The question for the administrator, then is this really a new potential immigrant, or is it the rejected applicant trying their luck again?

Graph database technology can really help answer that question, as it can sift through the enormous number of duplicate names and IDs this kind of practice gives rise to — easily, and in real time.

Using the information produced by graph databases, governments are deriving insights that aren’t just helping them deal with immediate issues, but also can be used as a basis for informed policy creation. In our conversations with customers and prospects in the public sector, we are finding this is genuinely just the start. How about a system so knowledgeable about a population and its cellphone use that it can — in seconds — track back anyone who phones through a bomb warning, lighting them (and maybe their network) up on a law enforcer’s screen, for example?

Or another example of graph potential in the public arena: what about a deep, deep linkage between public sector citizen data and geographical data, so that social issues and problems get spotted and mapped before even the busiest social scientist does their fieldwork? Again, what about interactive maps of parts of your city where you don’t just see what crimes are being committed, but the causes of these crimes — enabling you to work up fact-based strategies for ameliorating these conditions?

Finally, consider being able to closely follow the money trail between people and their bank accounts in order to stop tax evaders, white-collar criminals — even terrorists — by unraveling their webs of deception, webs it has to be recognized will be likely too complex for relational approaches to manage.

In each and every one of these scenarios, it’s a graph database that is the tool policy makers and switched-on agencies are turning to.

PureThink is a provider of Neo4j Government Edition to U.S. federal, state, Defense Department and intelligence agencies. They have been working to unify different agencies that are focused on money laundering. One of the problems they’ve uncovered is that investigating active money laundering inside a country usually is easy because you have all the data and your different financial institutions report to you.

But when people start bouncing money outside of these countries, and they try to basically layer it in different ways to take advantage of the fact that data is not usually being shared, that’s where things fall through the holes.

PureThink are working to discover a way to centralize and actually provide a way for these different countries to provide data that can be put into a master graph that can be used to identify how money is flowing through to a specific system from one account to another.

Graph databases also provide a way for government to track and analyze social media to help with law and order, for example, or to target crime rings. By using graph databases, government agencies can work with top-level metadata to spot hidden patterns and groups of interest in social media networks. Graph databases use fuzzy logic, which is effective at spotting how slightly variant name spellings all refer back to the same person.

Graph databases: A route to improving public services

Judging by the conversations we have had with public sector, technology and policy professionals, graph databases could be the answer to driving cheaper, more integrated and more efficient digital public services.

The U.S. government, like others around the world, wants to move away from top-down bureaucracy to create digital offerings that encourage interaction between citizens and the state. At the same time, citizens are demanding more transparent and timely delivery of services.

The U.S. Digital Service, which provides consultation services to federal agencies on information technology, is already said to be delivering results, from making it easier for students and their families to compare college options to new arrivals filing of immigration forms. The graph database could be a very powerful tool to take make digital transformation in government a reality and deliver better services for American citizens.

Our advice is to start trialing graphs now, as the investment required to find out if your organization can benefit from using graph databases to supplement their RDBMS investment is quite small, but the potential benefit is very high. You might also speak to colleagues in other government agencies to find out what database technology has worked best where, as a graph databases makes sense for any government organization seeking to make the most of its connected data.

Finally, the number of graph databases available is growing. But be aware that some graph databases offer the graph database model, but the underlying implementation is backed by a traditional RDBMS database, which can impact performance. Be clear about what you are getting!

Emil Eifrem is the CEO and co-founder of NEO Technology, the company behind Neo4j, a graph database.

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