Abigail Leffler defines and explores the significance of open data used in new and social media in the context of development and social change.
That Gutenberg moment
‘We live in a Gutenberg moment,’ announces Nadine Schuurman, ‘in which we are migrating from book reading to Internet browsing’ (Schuurman: 2013, p. 372). And ever since Johannes Gutenberg and his printing press idea, adds Michael Mandiberg, ‘technological innovations have enabled the dissemination of more and more media forms over broader and broader audiences’ (Mandiberg: 2012, p. 1). Indeed the implications of the Internet phenomenon are far-reaching.
With the advent of Web 2.0 (O’Reilly: 2004, in Mandiberg: 2012, p.2), new forms of communication have emerged. New media (of which social media is a subset) is non-linear, interactive, peer-to-peer in nature. This means that we no longer live in a model where a few dictate what the rest consume: we have become both producers and consumers of online information, and social media in particular provides the infrastructure that facilitates this information sharing. Mandiberg notes that ‘at the end of this first decade of the twenty-first century, the line between media producers and consumers has blurred, and the unidirectional broadcast has partially fragmented into many kinds of multidirectional conversations’ (Mandiberg: 2012, p. 1).
A cacophony of voices
Media participation has thus become part of media consumption. This interactivity is ‘a necessary condition for social, political and cultural participation’ (Lievrouw: 2011, p. 13), making new media an ideal catalyst for social change. The result from this variety of inputs is, as expected, a cacophony of voices singing to us through instruments as diverse as Twitter, Facebook, blogs, the mobile Internet (mobile phones) and YouTube, to name a few. Cacophony may be a disturbing sound but it definitely sets the tone for development and social change. Acknowledgement of dissenting voices leads to democracy at least, and to social change at most.
How social media came to complement and displace traditional media
In view of governmental monitoring and restrictions over Internet use and pointing to the negative popular perceptions about government’s capitalization on big data, some protesters in the Hong Kong student-led movement for democracy, Occupy Central, have, for example, resorted to wireless mesh network applications such as Telegram (heavily encrypted SMS) or Open Garden’s FireChat (open source chatting without an Internet connection) to channel their communications, because ‘the information [so] exchanged is public, but authorities cannot shut it down[i].’ Further reasons for using and trusting alternative social media lean toward the use of open data, suggesting that the information that comes from friends is more reliable than that coming from traditional media sources. Other examples of use of social media in the context of development and social change include the Twitter campaign to educate and keep the public informed about the current Ebola outbreak (#Ebola)[ii] and the Copernicus Publications website[iii], one of many open access academic research journals.
Open data: the good, the bad and the ugly
Now having established the currency of new media/social media for diverse purposes, key words come into the equation: information (data) + sharing, remixing, republishing, copying, distributing, transmitting, adapting and even translating (itself a form of reproducing, transferring, co-authoring and adapting). And, with this, we open the gate to the ensuing herd of benefits, issues and concerns that come galloping behind open data. The ODDC[iv] (Open Data in Developing Countries) organization carries out research in the framework of emerging impacts of open data in developing countries. This research is currently ongoing, and below we summarize some of their provisional findings.
The Venn diagram circles overlap each other to indicate that some issues may be experienced as positive or negative, depending on which angle they are looked from. The ‘bad’ category encapsulates those issues that cause concern or may raise questions but can be resolved or circumvented (e.g. through the provision of aid or investment), whereas the ‘ugly’ category includes those issues that are really a problem (e.g. an undemocratic or corrupt government in power). For example:
- Low cost claims: can be both ‘good’ and ‘bad’. Open data is said to be available at low or no cost, but this low expense claim is relative and in relation to users, not to those who produce data or make it available in the public domain and maintain it. And what benefit is the relative low cost of data to countries with poor or no ICT (Information and Communication Technology) capacity? Cuba (a US-embargoed country) and Ethiopia[v] are examples of countries that, for different reasons, have deficient access to ICT infrastructure and information channels.
- Transparency claims: can be both ‘good’ and ‘ugly’. We could also argue that transparency of open data claims are useless where open data is manipulated by those who produce it or interpret it, e.g. if the intermediaries are working for a non-democratic government (the ODDC named the Republic of Indonesia as such an example) or where the government has been accused of corruption (such as is the case with the present administration in Argentina, whose published statistics on growth are being questioned by the IMF (International Monetary Fund)[vi]. Ultimately, whose ends would this ‘transparency’ serve? Data that is not properly reviewed by independent third-parties runs the risk of being biased, skewed or incorrect. Unfortunately, errors in data that gets so published and transmitted can be reproduced ad nauseam, and this can have misinforming and misleading effects.
- Access to knowledge/information overload claims: can be both ‘good’ and ‘bad’. Recent research has shown that a fivefold increase in choices leads to poorer, less rational decision-making (Jackson: 2008 in Schuurman: 2013, p. 374). It may sound contradictory in countries where there has not been enough information, but researchers may find that they do not know which information resources are available in the online medium. When they do find it, they may not know whether it is worth having. Very little guidance about quality and reliability is typically available with online resources and open online resources will have to be rigorous and dependable if they are to be worthwhile.
Dear readers and fellow bloggers, the ball is now on your court. Do you have any examples of or reflections on how open data is used in social media in development and social change? What is your take?
[i]Fernández de Castro, R., and Atencio, M., 2014. How protesters in Hong Kong stay connected on social media. Beta Fusion [online]. Available at http://fusion.net/story/19749/how-protesters-in-hong-kong-stay-connected-on-social-media/ [Accessed 4 October 2014].
[ii] #Ebola. Twitter [online]. Available at: https://twitter.com/hashtag/ebola [Accessed 4 October 2014].
[iii] Copernicus Publications [online]. Available at: http://publications.copernicus.org/ [Accessed 4 October 2014].
[iv] Open Data Research Network [online]. Available at: http://www.opendataresearch.org/project/2013/oddc [Accessed 5 October 2014].
[v] Gevaert, R., 2012. A sustainable model for ICT capacity building in developing countries [online]. Available at: https://www.usenix.org/system/files/conference/lisa12/lisa12-final-2.pdf [accessed 5 October 2014].
[vi] Romig, S., 2014. IMF Says Argentina Needs to Improve Data More. The Wall Street Journal [online]. Available at: http://online.wsj.com/articles/imf-says-argentina-needs-to-improve-data-more-1402091563 [accessed 5 October 2014].
Lievrouw, L., 2011. Alternative and Activist New Media. Cambridge and Malden: Polity Press.
Mandiberg, M. (ed), 2012. The Social Media Reader. New York and London: New York University Press.
Schuurman, N., 2013. Tweet Me Your Talk: Geographical Learning and Knowledge Production 2.0. The Professional Geographer, Vol. 65, Issue 3.