Collaboration & Big Data Research

Categories: Big Data, Focus Series, MentorSpace, Other, Research Roles

The focus for January is on researchers’ roles, including characteristics and skills critical to success. Read the whole series here.


Collaboration: Human Skills
in an Algorithmic World

Researchers rarely succeed alone. The ability to collaborate is essential.

Nowhere is the ability to reach across disciplines and professional fields more important than in Big Data research. 

SAGE Research Methods offers a succinct definition of Big Data: “Data sets so large or complex that traditional data processing tools are inadequate.” To our point: our data processing skills might be inadequate! These complex, and yes big projects can stretch even the most resourceful researcher to the limits of their knowledge and expertise.

Three kinds of collaborative partnerships in Big Data Research:

Data Researchers + Programmers

Some social science researchers have the training and background needed to work with enormous datasets. If not, collaborating with others who have the technical expertise can help. Here is an example from Carl Miller, Director of Research at the Centre for the Analysis of Social Media. He described how working with technologists allowed non-technical researchers to make use of Big Data. This excerpt is from a UK National Center for Research Methods newsletter article:

We established the Centre for the Analysis of Social Media that brought together social and policy researchers at Demos, and technologists from the University of Sussex with the explicit aim of confronting this challenge. The first layer of the challenge has been the technology itself. The tools of big data analysis needed to be put into the hands of non-technical researchers: the subject matter experts who have long understood social science, and now needed to be able to do it in a new way. We built a technology platform, Method52, which allowed non-technical users to use a graphical user interface, and drag-and-drop components to flexibly conduct big data analytics, rather than be faced with a screen full of code.

This example demonstrates ways today’s research calls on us to think about research as a team, rather than a solo, activity.

You can also listen to Dr. Miller discuss this project in SAGE Research Methods videos, listed below. Find a recent report from the CASM about technology and research here. 

Big Data Researchers + Qualitative Researchers

Researchers sometimes find that they want to dig into real-life stories that explain the trends or patterns discovered in Big Data studies. Here are two articles that discuss ways that researchers work together:

Big–Thick Blending: A method for mixing analytical insights from big and thick data sources (Bornakke & Due, 2018)

Big Data and Small: Collaborations between ethnographers and data scientists (Ford, 2014)

Big Data Researchers + Librarians

Libraries and librarians are taking new roles as research partners. Here are two articles that discuss these opportunities:

Advancing library cyberinfrastructure for big data sharing and reuse (Lawlor, 2017)

Research data management in the age of big data: Roles and opportunities for librarians (Federer, 2016)

These 

Want to learn more about Big Data and Research?

Find articles, blog posts, recorded webinars and other resources at SAGE Ocean. Learn the language with the Glossary of Big Data Terms. Get the basics with Data infrastructure literacy, an article from Big Data and Society (Gray, Gerlitz, & Bounegru, 2018)

Find articles and book chapters, videos and cases on SAGE Research Methods:

If your library doesn’t have a subscription, and you would like to access the materials listed here, explore SAGE Research Methods with a free trial. Learn more about Reading Lists, and create your own public or private lists! Feel free to share your list or other resources in the comment area.

 

Relevant MethodSpace Posts

References

Bornakke, T., & Due, B. L. (2018). Big–Thick Blending: A method for mixing analytical insights from big and thick data sources. Big Data & Society, 5(1), 2053951718765026. doi:10.1177/2053951718765026

Federer, L. (2016). Advancing library cyberinfrastructure for big data sharing and reuse. Information Services & Use,, 36(1-2), 35-43. doi:10.3233/ISU-160797

Ford, H. (2014). Big Data and Small: Collaborations between ethnographers and data scientists. Big Data & Society, 1(2), 2053951714544337. doi:10.1177/2053951714544337

Gray, J., Gerlitz, C., & Bounegru, L. (2018). Data infrastructure literacy. Big Data & Society, 5(2), 2053951718786316. doi:10.1177/2053951718786316

Lawlor, B. (2017). Advancing library cyberinfrastructure for big data sharing and reuse. Information Services & Use,, 37(3), 319-323. doi:10.3233/ISU-170853

Miller, C., & Krasodomski-Jones, A. (2017). Digital Social Research: Centre for the Analysis of Social Media (CASM). SAGE Research Methods: SAGE Publications.

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