Our goal

The project aims to enhance the quality and relevance of education in the field. It aims to equip future professionals in governance, security and political science with the right tools to understand, correlate in an ethical manner and expand data knowledge for social good. It brings together experts from different fields (IT, law, intelligence, communication sciences) and it creates synergies between their different areas of competence in order to:

  • share the theory and applications of multi-use big data solutions;
  • increase awareness of both their usefulness and ethical implications;
  • deliver an integrated training course specifically tailored to the needs of targeted professionals.

While the project partners have a highly developed expertise in each of these fields, their integration will provide a specifically unique profile with added value to the courses to be delivered.

Objectives

The project does not intend to deliver a training on big data software, but rather to help professionals understand the working principles and processes of big data, so as to develop adaptive models of action, employing not (necessarily) big data, but the right (amount of) data, information and knowledge, so as to develop the ability to extract useful knowledge.

In this sense, it aims:

  1. To develop an innovative course package consisting of 4 teaching modules on data analysis
  2. To enhance key-competences and skills of the target groups in terms of data organization and analysis
  3. Development of a conceptual framework which can transform data analysis from an implicit process occurring within the organization to an explicit procedural process, by providing a common understanding.
  4. Development of a set of transferable skills, independent on the software solution at use.
  5. Awareness of the legal framework at national and European level which regulates the collection, storage and processing of data;

Target Groups

The target groups addressed by the project are:

  • (Future) security and law enforcement practitioners;
  • (Future) policy makers, applied and academic social scientists – main faculties and departments to be addressed are Political Science, Governance and Public Administration, Sociology, Security Studies;

The practitioners targeted by the project carry great responsibility in ensuring a sustainable development. Any mistake in providing decision-support and/or actionable insight affects not only the organization, but society at large.

Both target groups generally consist of social sciences, governance or security graduates, lacking a specific technical preparation, that work with large amounts of data and whose activities are intertwined.

The activities of the policy-makers, security and law-enforcement can be defined as informational – operative sequential processes. The quality of the policy/decision depends on the quality of data collected and analyzed by the security community and a common ground in understanding the type of data and methodologies applied to it ensure an added value to the overall process. We consider that by providing common ground for understanding, ethically using big data with social relevance in policy making, the course facilitates communication between the target groups.

Challenges

The target groups carry out great responsibility at social level. Ill-informed decisional processes in national security and policy-making, based on incomplete, inaccurate or incorrectly correlated data generate negative impact, affecting society at large. Although practitioners targeted by the project work with large amounts of data, their background is mostly in social science or security studies, lacking a very specific technical training. Such (future) professionals need to better understand what and how big data can be capitalized so as to ethically and lawfully improve the overall efficiency of their organization. At the moment, a preliminary survey of curricula and faculty members in non-technical organizations shows that analysis is being performed intuitively, ad-hoc and in a highly segmental manner, based on an individual’s skills, rather than on a strategic training perspective.

Expected results

  • Two intellectual outputs:
    1. The detailed course syllabus which will provide
      • textual content of the course, background readings and references, as well as
      • detailed information required for implementation of the course such as the minimum duration of the course, learning outcomes and performance indicators required for evaluation.

It will consist of 4 training modules:

  1. defining the conceptual framework, so as to understand how data fits in an organization and enable a data-analytic thinking,
  2. Collection of Data, with a special focus on the legal framework, information policies and data security policies,
  3. Processing, taking into account potential errors and
  4. Analysis of Data

This last module will address the target groups in a differentiated manner, so as to emphasize the use and relevance of using big-data analytics on real-world problems adapted to the institutional objectives of the target groups.

  1. The interactive training resource which will reflect the content of the detailed course syllabus in an interactive manner.

Developed as an online course, the interactive training resource will add value to the detailed course outline by offering the trainees the possibility to experiment with real data and observe the results of their queries. The theoretical knowledge provided by the first output will be structured in short explanatory videos/ interactive lectures, followed by practical exercises and applications on real-world problems. It encourages experimentation, learning by doing and creative learning, while making possible for the student to retrieve and review the material at any time. Both the detailed course syllabus and the interactive training resource capitalize on the expertise and on-field experience of the project members.

  • The project will also produce other intellectual outputs, such as an article submitted to a peer-reviewed publication and a conference presentation, which will describe the project and its implementation, as well as the notable results it achieves. This will account for the project’s summary, the main activities carried out during the project and the feedback of the trainees in relation to the trainings carried out within the framework of the project.
  • Dissemination outputs:

Within the project, several dissemination outputs will be produced – a dedicated website, presenting the progress of the project and its results, leaflets, brochures, newsletters. Two simultaneous multiplier events will be organized to further disseminate the intellectual outputs of the project to the target groups and to facilitate a further transfer of knowledge.