Community Research and Development Information Service - CORDIS

H2020

EDSA Report Summary

Project ID: 643937
Funded under: H2020-EU.2.1.1.4.

Periodic Reporting for period 1 - EDSA (European Data Science Academy)

Reporting period: 2015-02-01 to 2016-07-31

Summary of the context and overall objectives of the project

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. Declared by Harvard Business Review as the “sexiest job of the 21st century”, data science skills are becoming a key asset in any organization confronted with the daunting challenge of making sense of information that comes in varieties and volumes never encountered before. 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.

The European Data Science Academy (EDSA) is establishing 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

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. 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 attend two online meetings per year. These meetings provide opportunities to discuss developments in the project and to assess the relevance and appropriateness of outputs to industry, throughout the project’s duration. Additionally, the Advisory Board is kept updated on the progress of the project, through a short progress report produced by the Open Data Institute every three months. The report summarises developments from each work package in the project and includes areas that can be addressed at the bi-annual meetings.
Demand Analysis
One of the core objectives of EDSA is 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 seeks to answer 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?

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, serving a number of purposes, including:
1. to provide a structured framework for capturing the design space;
2. to guide data collection, linking to third party resources and reuse of both data and the results of analysis;
3. to guide the discovery of related information hidden within the demand data and aid navigation through the data as size and complexity increase;
4. to support translation of the input data into information and, subsequently, enriched, contextual knowledge, and therefore support effective answering of end users' questions.

The EDSA curriculum is driven by the demand analysis and provides the core framework for the development of the EDSA courses. Based on the EDSA curriculum, the project is developing a courses portfolio, which includes a wide range of Data Science 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. The EDSA courses employ different delivery channels and formats in order to maximise the impact of the EDSA learning materials on the community and bring them closer to as many students and practitioners as possible.
Learning Analytics
A variety of Learning Analytics methodologies have been deployed by the project in order to analyse the interactions of learners with the EDSA learning materials and reach conclusions about the effectiveness of learning from the EDSA courses, as well as shape the EDSA curriculum accordingly. Learning Analytics 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 (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 complement findings from Learning Analytics, thus allowing more informed decisions to be made in course and curricula design.

The Academy aims at ensuring a long-lasting, sustainable impact of the project, by building on five 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. An impartial and scientific approach to matching data science skills needs with a flexible curriculum.
2. The Curriculum Design Values the EDSA project uses to create high-quality training.
3. The Curriculum Delivery Values that the EDSA project has identified as the basis for impact-driven training.
4. Learning Analytics that help refine and improve training delivery.
5. The advice of the Advisory Board, incorporating insights from industry leaders.

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)

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.
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 intend 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.

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