European Data Science Academy

Project Information

EDSA

Grant agreement ID: 643937

DOI

10.3030/643937

Project closed

EC signature date 12 December 2014

Start date 1 February 2015

End date 31 January 2018

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Total cost

€ 2 976 189,75

EU contribution

€ 2 976 189,75

Coordinated by

THE OPEN UNIVERSITY
United Kingdom

Periodic Reporting for period 2 - EDSA (European Data Science Academy)

Reporting period: 2016-08-01 to 2018-01-31

Summary of the context and overall objectives of the project

Problem addressed and importance to society
The 'Age of Data' continues to thrive, with data being produced from all industries at a phenomenal rate that introduces numerous challenges regarding the collection, storage and analysis of this data. Data scientists are, however, still a rare breed. Beyond the occasional data-centric startup and the data analytics department of large corporations, the skills scarcity is already becoming a threat for many European companies and public sector organizations as they struggle to seize Big Data opportunities in a globalized world.

Project objectives
The European Data Science Academy (EDSA) has established a virtuous learning production cycle for Data Science, in order to meet the following objectives:
- Analyse the sector specific skillsets for data analysts across Europe’s main industrial sectors;
- Develop modular and adaptable curricula to meet these Data Science needs; and
- Deliver training supported by multiplatform and multilingual learning resources based on these curricula.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Advisory Board
EDSA has established an Advisory Board to oversee the project and ensure that project activities continue to meet changes in the demands on data science across Europe. Industry related Board members have been appointed to represent both the supply and demand of data science training in Europe. Members of the EDSA Advisory Board together with representatives from the EDSA consortium have attended a number of meetings over the course of the project, and have been kept updated on the progress of other project related activities, through a short progress report produced by the Open Data Institute every three months. These progress reports and meetings have provided opportunities to discuss developments in the project and to assess the relevance and appropriateness of outputs to industry.
Demand Analysis
One of the core objectives of EDSA has been to progress Europe’s competitiveness in data science. Uncovering industry trends and skills needs is essential to this objective, as is integrating the discovered demand into EDSA’s modular training framework. The EDSA Demand Analysis has answered three consequential research questions:
1. What is the current demand for data skills in different European industry sectors?
2. What training should be offered in order to accommodate this demand?
3. Which options exist for EDSA to develop a sustainable offer for high-impact data science training?
Dashboard
In order to get a real-world impression of the current data science job demand, we have collected extensive job posting data from a variety of online sources. The EDSA dashboard offers users a self-explorative view of this job posting data. Users of the EDSA dashboard are able not only to explore the current market demand, but also find learning materials and training relevant to the skills they need to secure a specific job position. Users are also supported in building personalised learning pathways, consisting of courses and learning materials that will help them reach their learning goals.
Curriculum and Courses
The EDSA curriculum has been driven by demand analysis and provides the core framework for the development of the EDSA courses. Based on the EDSA curriculum, the project has developed a courses portfolio, which aggregates a wide range of high quality learning resources, either offered by project partners or by third parties. This portfolio includes courses adopting a variety of pedagogical models, as well as employing different delivery channels and formats in order to address different learning contexts and audiences.
Learning Analytics
A variety of Learning Analytics methodologies have been deployed by the project in order to analyse the interactions of learners with EDSA learning materials and reach conclusions about the effectiveness of learning from our courses, as well as shape the EDSA curriculum accordingly. Learning Analytics also offers us the means to derive information on the effectiveness of course content and delivery and the impact of student demographics (individual and group), as well as additional factors such as motivation on course completion and grades. By demonstrating the (relative) importance of selected skills to a role or job type and optimal paths to follow to these, analysis results from the demand analysis task have complemented findings from Learning Analytics, thus allowing more informed decisions to be made in course and curricula design.
The Online Institute
The EDSA Online Institute aims at ensuring a long-lasting, sustainable impact of the project, by building on three crucial resources developed during the EDSA project. Together, these form the framework of excellence for our sustained offer and impact beyond the project end:
1. A dashboard offering a snapshot of demand in the field of data science,
2. A practical tool supporting the construction of Data Science curriculum
3. A set of High-quality Data Science courses developed by the project partners as well as directing users towards equivalent courses from other institutions

Finally, following the successful outcomes of the EDSA project, the exploitation of the EDSA brand to provide an accreditation/certification programme is currently being explored by some project partners.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Progress beyond the state of the art
Novel methodologies have been developed and deployed for the collection, harmonisation and analysis of diverse datasets, consisting of qualitative and quantitative data gathered from stakeholders across a range of sectors and countries. In order to offer new ways for the visual exploration and manipulation of the large volumes of datasets collected, we have developed a number of visualisation techniques driven by Semantic Web technologies. We have also established a virtuous learning production cycle by producing open educational resources as reconfigurable course components that can be adapted and customised for different learning contexts, targeting the acquisition of skills matching the outcomes of the project’s demand analysis. Finally, we have established a Learning Analytics framework for the collection and analysis of datasets originating from diverse learning platforms and contexts.

Expected potential impact
EDSA aims at bridging the data science skills gap across Europe, thus impacting the digital economy within the European borders and beyond. The activities of the EDSA project have been intended to offer an understanding of the data science landscape across industrial sectors and improve the employability of data scientists through the provision of high quality, industry-fit training. This work has the potential to revolutionise business, government, and society, as Data Science methods provide instruments to create economic and social value. By combining both internally owned and external sources of data, organisations can learn about their processes, accurately plan and target operations, and achieve significant cost savings and productivity gains. This applies for any type of organisation, public or private.

Figure 1: Screenshot of the online survey available from the EDSA website

Figure 2: Skills that a data scientist should have according to the EDSA Demand Analysis

Figure 3: The EDSA dashboard

Figure 4: The EDSA dashboard data acquisition process

Figure 6: Analysis of the viewing behaviour throughout the duration of an EDSA MOOC

Figure 5: The EDSA courses portal