Innovations in Digital Research Methods. Группа авторов
social processes as they actually happen is bound to give researchers insights and interesting avenues to explore that are absent from the often post-hoc reconstructions of events that are available via traditional research instruments and datasets.
Big social data will inevitably force us to rethink the role of academic social scientists. One way forward would be for them to actively seek collaborations with groups, both professional and lay, involved in doing various kinds of ‘practical, everyday sociology’. An example of collaboration with professionals might include assisting journalists8 who increasingly find themselves needing to analyse large datasets in order to report news stories.9 Examples of collaborating with lay people include ‘citizen social science’ where members of the public can assist with research through crowd-sourcing data (as illustrated in Chapter 9), by participating in analytical work (Procter et al., 2013b), and even by taking a role in the setting of research agendas (Housley et al., 2014). These examples suggest possibilities for forging a new relationship between academic social science and society at large, a ‘public sociology’ (Burawoy, 2005), where social scientific knowledge is co-produced by a wide range of stakeholders (Housley et al., 2014) and is subject to greater public oversight and accountability. Initiatives in other discipline areas might provide models for how to proceed in the social sciences: see, for example, the Public Laboratory for Open Technology and Science (http://publiclab.org/), whose ‘goal is to increase the ability of underserved communities to identify, redress, remediate, and create awareness and accountability around environmental concerns.’
Finally, as is noted in several of the chapters that follow, big social data has given fresh stimulus to debates about research ethics (see e.g., boyd and Crawford, 2012), much of which focuses on the issue of people’s right to privacy but which also raises questions about the role and status of academic research. At the same time, we must not lose sight of the broader issue of the ethics of research and innovation (see e.g. Stahl, Eden and Jirotka, 2012, and Chapter 12 in this volume).
1.4.3 Collaboration
e-Research was conceived from the very beginning as a collaborative activity that would combine the abilities of distributed and complementary groups of researchers in order to achieve research goals that individual researchers or local groups could not hope to accomplish. With this in mind, the concept of the ‘virtual research environment’ (VRE), ‘collaboratory’ (cf. Olson, Zimmerman and Bos, 2008) or ‘gateway’ was another widely promoted element of the e-Research vision. VREs were seen as a way to support collaboration and provide integrated, shared access to resources throughout the research lifecycle, starting with literature searches and ending with the publication of results and curated datasets. In one system, accessible by all team members, a shared bibliography would be assembled. A joint laboratory notebook would be kept which would document all the research procedures undertaken. Data would be stored along with metadata recording the operations it had been subject to, and reports would be written collaboratively, with all versions archived, and publications prepared. Once again, experience has shown that the initial vision had to be tempered. VREs exemplify what happens when ‘top-down’ innovation programmes meet ‘bottom up’ processes through which individuals and groups of researchers experiment with whatever new technologies are at hand. They often prefer to work out their own – often ad-hoc, bespoke but nevertheless effective – solutions that match their needs and level of technical competence rather better than complex, all-embracing offerings whose adoption might lead to having to abandon favoured tools. A prosaic example is the use of an email list and attachments or freeware such as Dropbox10 to share documents, rather than struggle to implement a VRE across different institutions’ computer systems and seek local support in its use. Similarly, Web 2.0 has provided a host of applications that can be easily adopted to support various stages of the research cycle, such as switching from email attachments to an Internet file hosting and synchronizing service like Dropbox or Google Drive. Those VREs that have survived the turbulence of constant technological innovation and rapidly changing standards tend to be associated with ‘big science’ projects, such as climate change, and benefit from long-term funding arrangements.11
1.4.4 Scholarly Communications
Nowhere is this tension between top-down and bottom-up innovation processes in science more clearly evident than in scholarly communications. The past decade has seen the emergence of new ideas about the practice of scholarly communications, with talk of a ‘crisis in publishing’ and weaknesses in the peer-review system. One outcome is the notion of ‘Open Science’ (Neylon and Wu, 2009) with its advocacy of more open scientific knowledge production and publishing processes (Berlin Declaration, 2003; Murray-Rust, 2008). This has been inspired by discourses developed in ‘Free/Open Source Software’ and ‘Creative Commons’ movements (Lessig, 2004; Benkler and Nissenbaum, 2006; Elliott and Scacchi, 2008). Web 2.0 is widely seen as providing the technical platform to enable these new forms of scholarly communications and bring about a ‘re-evolution’ of science (Waldrop, 2008).
Web 2.0 brings the promise of enabling researchers to create, annotate, review, reuse and represent information in new ways, promoting innovations in scholarly communication practices – e.g. publishing ‘work in progress’ and openly sharing research resources – that will help realize the e-Research vision of improved productivity and reduced ‘time to discovery’ (Arms and Larsen 2007; Hey et al., 2009; Hannay, 2009; De Roure et al., 2010). However, despite this increasing interest in Web 2.0 as a platform and enabler for e-Research, understanding of the factors influencing adoption, how it is being used, and its implications for research practices and policy remains limited. Recent studies suggest that there is considerable reluctance – even suspicion – to adopt new forms of scholarly communications among many academics, who fear that this will mean the end of the ‘gold standard’ of peer-review and the undermining public trust in science (Procter et al., 2010a; Procter et al., 2010b). Equally, it would be a mistake to ignore the capacity of established academic publishers to shape the emerging scholarly communications landscape so as to preserve their role as gatekeepers (Stewart et al., 2012). The future of scholarly communications may, after all, not be so radically different from its recent past.
1.4.5 The Future
The vision that motivated the e-Science programme in the UK and analogous programmes elsewhere was that grid computing-based infrastructure comprising computer power, big data and collaborative teams would transform science. Over the past decade this has morphed into a much more complex e-Infrastructure made up of a plethora of only loosely related tools and services taken up to different degrees and in different combinations and with different levels of enthusiasm even within the same field, allied with rapidly accreting digital data of new types and old. The e-Research facilitated by this maelstrom is transforming social science research, but in unpredictable ways, with many socio-technical barriers to be overcome before its full potential is realized. The aim of this book is to whet the appetite of social researchers to encourage them to explore how innovations in digital research methods might enable their research to advance in ways not possible otherwise.
1.5 Online Resources
Many of the examples of e-Research methods presented in this book already have online resources associated with them. To make these more accessible to readers, we have created a companion website.12 This provides easy access to this content, including in-depth case studies, datasets, research workflows, tools and services, publications and links to the authors’ own websites.
1.6 Bibliography