3. Public Sector
3.5.4 Predictive policing using open data
Description: Open data initiatives make datasets freely available to the public, so data can be used without restrictions from copyright or patents. Governments around the world have started open data initiatives to make public sector data available to the public for sake of transparency and to allow third parties to offer services based on the data. One such service can be described as predictive policing where historical crime data is used to automatically discover trends and patterns in the data. Such patterns help in gaining insights into crime related problems a city is facing and allow a more effective and efficient deployment of mobile forces (Wang, Rudin, Wagner, & Sevieri, 2013).
Example Use Cases: The real world effectiveness of predictive policing has currently not been evaluated by any independent researchers. However, the commercially successful company PredPol has received a lot of media coverage and has installed their system in numerous cities in the United States, including Los Angeles and Seattle. They claim crime decreased by 13% in
1 http://www.prnewswire.co.uk/news-releases/agt-international-raises-the-bar-for-safe-city-solutions- 201069651.html 2 https://www.agtinternational.com/wp-content/uploads/2013/11/AGT-Connected-City-Solution- Brochure.pdf
the four months following the rollout of their system in a district of Los Angeles, compared to an increase of 0.4% in the rest of the city.
User Value:
User Impact: significant decrease in crime, efficient use of mobile forces.
Maturity: some commercial solutions available.
Financial Impact: not evaluated, optimization of security resources. Prerequisites
Availability of digitalized historical crime data for the area where the system is deployed Data Sources: Historical crime data.
Type of Analytics: Pattern recognition.
Required Big Data Technologies: Data extraction, ETL tools, Machine learning. Sources: (Wang, Rudin, Wagner, & Sevieri, 2013), (Main page, PredPol)
3.6. Requirements
The situation in public sector is that there are not many requirements for the development of specific technologies with direct application in the sector, rather the requirements are for the lack of political willingness to regulate and effectively use the Big Data technologies. Many challenges are foreseen in the application of these high potential technologies in the public sector, so it is required to address such issues to pave the way for the successful development of Big Data in the sector. Most of the conclusions presented here have been extracted from the specific BIG survey and from the surveys performed for the formulation of the European Big Data Value Partnership.
Interoperability. It is the main obstacle to exploit data assets for the application of Big Data solutions in public sector because the lack of standardization of data schemas. The lack of interoperability is boosted by the fragmentation of data ownership that leads to the data silo problem. It is an issue that can only be solved from public sector itself with a willingness to harmonize and integrate. In this sphere it is also the lack of interoperability among EU member states.
Legislative support and political willingness. There is a lack of legislation granting the access to data not generated by public sector, here the Intellectual property rights is an issue that should be tackled, as it creates uncertainty and is a hinder to the reuse of the data. In some cases the licenses for public sector data available are not always clear. The process of creating new legislation is often too slow to keep up with fast-moving technologies and business opportunities. Another dimension is the regulation for the use of cloud computing, so public sector can trust cloud solutions. Furthermore, the lack of European based Big Data cloud computing operators within the European market is also a barrier for the adoption.
Privacy and security issues. The aggregation of data across administrative boundaries in a non-request-based manner, is a real challenge as this information combined may reveal highly sensitive personal and security information, not only compromising individual privacy but also civil security. Access rights to the required data sets for an operation must be justified and obtained. Whenever comes to a new operation a notification or a license must be obtained from the Data Privacy Agency. Anonymity is an issue in those cases, so data dissociation to keep privacy is required. Individual privacy and public security concerns must be addressed before governments and society actors can be convinced to share data more openly, not only publically but sharing in a restricted manner with other governments or international entities. Big Data skills. There’s a lack of skilled data scientists and technologist to be able to capture and process these new data sources. As far as it will be massively adopted in business it will
become harder to find skilled Big Data professionals. In the public sector areas where Big Data is more actively pursued –at research and intelligence agencies– there are currently workers with such skills available to manage Big Data projects. However, in a few years’ time, when there will be a high demand in Big Data skills across the government agencies and in the industry in general. Public body Agencies could go a fair distance with the skills they already have, but then they’ll need to make sure those skills advance (1105 Government Information Group). Besides the most technical oriented people, there is a lack of knowledge in business oriented people, so they must be aware first in what Big Data can help them to solve public sector challenges and also preparing the regulatory framework for succesful development of Big Data applications.
Other requirements. Legacy technologies and technology adoption. For existing and old technologies, lack of compatibility and vendor lock in, are the most important challenges. For the introduction of new Big Data technologies there is the natural uncertainty and learning curve.
Lack of a clear strategy for Big Data, therefore the identification of problems that can be solved with Big Data and searching for the right data is a real challenge. Willingness to supply and to adopt, and also to know how to use it.
Common national or European approaches. Need of common national or European approaches (policies) – like the European policies for interoperability and open data. Lack of leadership in this field.
A general mismatch between business intelligence in general and Big Data in particular in the public sector. Decision-making in the private sector has been slowly adopting business intelligence as a real tool but in the public sector, where the decision mechanisms are much different, this has not occurred.
As showed in Figure 13 from the answers to the BIG survey, the non-technical challenges are those rated higher, like the adoption process, the lack of skilled people and the security threats.
From a generic cross sectorial Big Data opportunities survey report, on the specific question on which are the business barriers for developing Big Data, a large segment, 43%, say the lack of budget holds them back, while 35% are also concerned with a lack of skills. About a third mention both data governance issues as well as lack of urgency from business management, two highly inter-related issues. The ability to help business users connect with the data that is available to them is an important emerging role for data professionals, as can be seen in Figure Figure 13: What are the most important key challenges you would face for adopting Big Data?
14 (McKendrick, 2013). This generic picture is alligned in many issues with the requirements in public sector, skills, data governance (leadership and legislative support)
Figure 14: Big Data Business Barriers (McKendrick, 2013)
3.7. Implementation of Research Methodology
The implementation of the research methodology for the collection of requirements for public sector was done following the research methodology with these specific actions.
For the first step is was performed a literature review to identify the main sector stakeholders and identification of those use case applications already deployed in the public sector. Likewise, potential improvement areas in the sector and the analysis of users’ needs and the characteristics of the sector in Europe were identified.
Second step.
For the second step a survey with 15 questions clustered into three parts designed to collect the understanding of the state of the art as far as Big Data adoption is concerned:
I – Identification of Organization
II –Relevance of Big Data for your organization III –Big Data in your organization
The survey was distributed to 28 public administrations, five of them answered, two of them through an interview. The template of the survey can be found at Annex 1 Big Data Questionnaire for Public Sector.
Third step
For the third step, two validation workshops were organised. On the 16th April 2013, the First workshop Building Europe’s roadmap for Big Data in the Public Sector was held in Madrid. During this workshop additional questionnaires were distributed, and a total of 8 answers were collected. On the 3rd July 2013, the Second workshop Building Europe’s roadmap for Big Data in the Public Sector was held in Bratislava. During this workshop additional questionnaires were distributed, and a total of 9 answers were collected.
Additional information was collected as part of the BIG DATA VALUE interviews conducted by Atos during February 2014. A total of 9 interviews were performed.
The inputs collected from the surveys have been also taken into consideration for the elaboration of the final version of this report. All the inputs collected in the interviews and the surveys have been integrated in this requirements report.
3.8. Conclusion and Recommendations
It can be said that public sector it is more or less aware of the potentials of these technologies, but the path to success is not currently clear due to some uncertainties, the most important of which are:
Lack of political willingness to make public sector take advantage of these technologies, It is required a change in mindset of public sector senior officials.
Lack of skilled people, business oriented people, aware of where and how Big Data can help to solve public sector challenges, and who may help to prepare the regulatory framework for the successful development of Big Data solutions.
New General Data Protection Regulation and the PSI directives display some uncertainties about the impact on the implementation of Big Data and Open Data initiatives in the public sector. Specifically, Open Data is set to be a catalyst from the public sector to the private sector to establish a powerful data industry.
It needs to gain momentum. Today, there is more marketing around Big Data in public sector than real experiences from which to learn which applications are more profitable and how it should be deployed. This requires the development of standard sets of Big Data solutions for the sector.
There are many bodies in public administration (especially in those which are widely decentralized), so much energy is lost and will remain so until a common strategy is realised for the reuse of cross technology platforms.
The recommendation is that in order to take advantage of these technologies, the sector should:
Set up a European leadership that establishes generic strategies and approaches as a guidance for the implementation of Big Data solutions in the European public sector.
Reuse the experience from successful implementations in the sector, and those applicable from other sectors.
Launch heterogeneous task forces (legal, business and IT people) for the development of solutions with solid legal and regulatory foundations.
Solve the fragmentation of the public data ownership in an optimal way.
3.9. Abbreviations and acronyms
DG Directorate General
EC European Commission
ETL Extract, Transform, Load
EU European Union
EU28 European Union – 28 countries GDP Gross Domestic Product
ICT Information and Communication Technologies IoT Internet of Things
OECD Organisation for Economic Co-operation and Development PSI Public Sector Information
ROI Return of Investment
SME Small and Medium Enterprises