The project consortium developed a desk research in order to assess a need analysis about data literacy competences and skills around Europe. This desk research was conducted by all partners of the consortium, for 18 European countries and Tunisia, which aimed to analyse the state of data literacy in each country, by answering some pertinent questions: How is data literacy (Data Literacy) perceived? Who are the stakeholders? How is it integrated in Higher Education Institutions (HEI) or enterprises? What are the most important competences for a literate person? And other relevant questions, whose answers are summarized below.
The multidisciplinary approach used in this research allows us to obtain the best representative data about Data Literacy in the target countries, how it is known by the general public, the Universities (students, staff, and professors), and in the enterprises/private companies. The whole process has been managed by Universidade NOVA de Lisboa, under the coordination of Institute for Educational Technology of the Italian National Research Council. The desk research consists in the analysis of different sources, by all partners of the DATALIT consortium, for 19 countries. The multidisciplinary approach of this research allows us to observe how data literacy status is in each country. Although, some countries provide more information than others, we could still retrieve important information, which main conclusions are as follows.
How is the concept of "Data Literacy" perceived in Europe?
The term ‘data literacy’ isn’t well known in most of the countries analysed. The most widely used terms are ‘digital literacy’, ‘information literacy’, ‘data competence’, ‘media literacy’, ‘statistical literacy’, ‘computer/IT literacy’, among others. In most countries is closely related to digital skills. Some countries, like Belgium or Serbia, don’t even recognize or have a direct translation of the term itself. Although, all countries agree that ‘data’ is very important and how people use, analyse, and perceive that data is essential for today’s job market and decision making. Every desk research agrees with the existence of different stakeholders related to Data Literacy, namely individuals, business, universities, government, media, NGOs, research institutes, and others (i.e. all those who work with data). Relative to Data Literacy stakeholders’ statistics, in the different countries, the information is scarce. For example, in Lithuania there is a vast and various information about Data Literacy stakeholders; in Portugal there is statistical information about digital literacy stakeholders, not Data Literacy; and other countries have little to no statistics on Data Literacy stakeholders.
Universities are not Alone in the Educational Offer
Universities are still the main providers of Data Literacy related courses, but there are other organizations that also provide Data Literacy courses or Data Literacy related courses. Each country has specific private companies/NGOs/government entities, that provide these courses, like, for example, DigitYser is the Digital Innovation Hub of Brussels (Belgium), or Digital Serbia Initiative (Serbia). At an international level, there are a few companies that deliver specific Data Literacy courses/programs/certifications and are the greater players in this field, namely Qlik (with the ‘Data Literacy Program’), Microsoft (with the ‘Microsoft Data Science’ program), Data Literacy Project (from Qlik, with several courses on Data Literacy), and online providers, like Coursera, edX, Udemy, etc. Learning Management Systems are widely used in most countries, especially Moodle, also e-portfolio Mahara, and other proprietary tools. In some countries there is support from public and private institutions for the acquisition and validation of Data Literacy related competences, like IEFP in Portugal, or the Department of work in Belgium, for example. In HEIs/Universities, there is a great range of Data Literacy related degrees (bachelor, masters, PhD, and others), that include courses in data science, big data, business intelligence, artificial intelligence, and other IT related subjects, but there seems to be an increase in interest on Data Literacy related subjects in non-IT degrees, like marketing, tourism, journalism, social sciences, etc. In HEIs we can see that Data Literacy is always part of a degree, or course, not exactly the whole course. Many universities have partnerships with private companies/institutions, that in one way or the other influence the path of these HEIs courses, and help with students’ internships, mentoring and projects.
Data-Centric Job Vacancies
In the enterprise domain, several job websites were analysed, and the research shows that for the specific term ‘Data Literacy’ there isn’t many offers, but when it comes for the terms data, data science, big data, AI, and other IT related subjects, there is a great demand for professionals that are data literate, and have great programming skills. Other offers, like administrative roles, HR, accountant/finance roles, also demand professionals with some sort of data literacy, like managing databases, using MS Office, and other kind of programs/software/tools. Many different hard skills are asked in these job announcements, but overall the soft skills are more or less the same: motivation, flexibility, leadership, team player, problem solving capacity, proactive attitude, strong interpersonal skills and cross-cultural competence, empathy, attention to details, communication skills, independent worker, English fluency, etc. It seems to be a rise in demand for professionals that know how to work with data.
Competences Certifications at Glance
In terms of Data Literacy related competences and validation many of the countries in this research don’t have a validation approach to Data Literacy, other than formal education. Most validation processes include certifications delivered by private institutions/NGOs (e.g. The Data Literacy Project), ECTS delivered in universities, and certifications delivered by government/public entities (e.g. Portuguese Agency for Qualifications (ANQEP), in Portugal for competences related to Data Literacy, but not Data Literacy exactly). Most Data Literacy competences are recognized in the business sector and internally validated, but there isn’t quite a structured system/tool or framework to assess these competences for the general public. Some countries (e.g. Serbia) don’t have institutes or organizations, involved in working on Validation of Informal and Non-Formal Learning (VINFL), others (e.g. Spain) use European frameworks for this, like DigiCom 2.0.
Key Findings
The main conclusions in this desk research are that there is a lack of understanding of what ‘Data Literacy’ is and what a data literate person knows and does. There is a clear confusion between different kinds of literacy, specially between digital literacy and data literacy. In many countries data literacy = digital literacy, and this is a false statement. It becomes necessary to clarify the meaning of each type of literacy - data, digital, information, media, statistical, and others - and how they interact with each other, because none of them is totally independent of the other. In every country there is a qualification system or framework for different Data Literacy related competences, but specifically for Data Literacy this is non-existent. Data Literacy involves different soft skills, that are appreciated and recognized by the business sector and are validated in an internal level, but there isn’t a way to assess these skills for the general public or validate them. Although there are private entities/NGOs that offer different types of validation and assessment and some governments are involved in different projects with this in mind, there a shortage of tools and frameworks to properly do this at a national level. ‘Data literacy’ is a term that is not well known, but everyone uses Data Literacy competences/skills, within those who work with data, so a strong structure of the concepts and of the technical and non-technical skills is needed to help identify a data literate person and create more competent professionals.