This sounds great, and I agree, there is a MUCH needed discussion to be had on data literacy. It’s often brushed aside, but like I was discussing earlier here, there is much to be said about access to data, and the implications of data literacy globally. I think there’s also a large discussion to be had about generational assumptions, about racial and gender divides, and about multimodal implications for the consideration of data literacy which is the topic I’ll probably be writing about.
Details are below, see the full website here
Relevance, motivation and goals
Data literacy is a phrase which has been used with increasing frequency over the last decade in a wide range of contexts related to Web Science such as citizen science and the democratic divide. Recently it has been brought into particularly sharp focus by the open data movement. The aim of open data is that it is open to all – everyone should be able to reuse it. If users do not have the right skills, knowledge and attitudes then “open data” is effectively not open to them (Gurstein 2011), although little attention has been paid to the skills and education needed for open data (Huijboom and Broek 2011).
Despite this, data literacy has received very little academic attention, and what attention it has received is confined to isolated areas of study. For example, it is one consideration among others in addressing specific issues in the broader context of information literacy such as academic library services (Rader 2002) and undergraduate skills (Carlson et al. 2011; Stephenson and Caravello 2007). Other literature treats data literacy as related to information and statistical literacy but only for a limited section of the population or in terms of the competencies required in a limited context (Prado and Marzal 2013). There is very little published research treating data literacy as an object of study in its own right and placing it in a broad socio-technological context. This workshop aims to investigate the potential for coherent multidisciplinary research into what data literacy means for society as a whole, why it matters, and how it might be facilitated.
Such research should address questions such as:
What do we mean by data literacy? Is there one kind of data literacy or many? What skills, knowledge and attitudes does it include? How does it relate to other types of literacy (digital, numerical, statistical and linguistic)?
Why do we need data literacy? What are the social, political, economic, technical issues it can address?
How should it be achieved? Is it best done through education, training, or behaviour change or does it require better tools and support?
What are the broader political, social and philosophical implications?
- Should technology be driving such fundamental skills?
- How does this compare to other technologies such as the printing press that have created a need for new “literacies”?
- Does data literacy compound the digital divide at another level?
- Can it lead to open data having a more visible impact?
Who should be data literate? Should everyone become a data specialist by learning how to deal with raw data, or we assume that we need specialists in order to “translate” data to the society?
What are the practical implications? What should private and public sector organisations do about data literacy? How should data literacy participate in education and research?
All deadlines are midnight UK time on the date specified.
- Papers submitted by: 17th May
- Notification to authors: 26th May
- Workshop: 30th June
Submissions can be of two types:
- Completed long papers (8-10pp)
- Short papers experience related, position papers, research in progress (3-5pp)
In either case we encourage linking to other media such as video clips or software.
All accepted papers will be published on the workshop website. This will be done several days before the workshop in order to facilitate discussion in the plenary section of the workshop. The organizing committee will select the best papers to be presented at the workshop on the 30th of June. If papers reach the required standard but the authors are unable to attend the workshop, they will also be published.
Selection criteria for papers
The selection criteria are adapted from the Springer LNCS. Submissions should:
- Be written in English;
- Fit with the workshop theme;
- Have a clear motivation (why the problem is interesting theoretically and/or practically);
- Conceptual development and grounding in prior literature (given the nascent nature of the topic it is not expected that the prior literature is about data literacy);
- Methodological adequacy (if relevant);
- Adequate list of references to related work and grounding theories;
- Interesting findings;
- Well-structured and clearly written paper;
- Maximum length of paper: 10 pages for full papers, 5 pages for short papers; and
- Conform to Web Sci 2015 rules for formatting.
Papers will be subjected to double blind review by 2 reviewers for rigor, relevance, originality and clarity of presentation and then the accepted papers will be chosen by the organising committee based on the reviewers’ assessment. Papers should be anonymised, i.e. all information identifying the authors removed, and submitted via Easychair.