Future Perfect: Seven Data Types We’d Like to See

Categories: Big Data, SAGE Posts


While there is more data available at our fingertips today than ever before, the future promises to bring even more information into our reach. But what kind of data will it be? And what new doors will it open? As part of our Love Your Data Week 2017 celebration, SAGE Publishing asked a few of our journal editors and textbook authors about what data they would like to see in the future that can’t be obtained at present. Here’s what they said:

Is it possible to imagine guaranteeing citizen rights to data collected by app and platform owners along with secure and privacy protected repositories for donating their data for research? Together with built in systems for granting access and consent such platforms could contribute to research for collective benefit.

Evelyn S. Ruppert, editor, Big Data & Society


I would like to see the complete digital footprint and physical footprint of individuals and families in their consumption of media and communication content.

Louisa Ha, Ph.D., editor,  Journalism and Mass Communication Quarterly


In the future, I would like to see mixed methods data collection that routinely involves the collection and integration of both qualitative and quantitative data in a mixed methods program of research. While the philosophical, design, and data collection analytics, interpretation and presentation approaches have reached a high level of development, the reason mixed methods data cannot be collected now are less a technical issue than a mindset issue among researchers and funding organizations.

First, there is a relative lack of understanding by many researchers about the possibility of routinely collecting qualitative and quantitative data in a program of mixed methods inquiry. Second is the lack of understanding about the advances in mixed methods research methodology that make that possible. Third is a belief among some researchers that one form of data collection is superior to the other, i.e., qualitative are superior to quantitative, or quantitative are superior to qualitative. Fourth is a relative lack of willingness to accept or honestly accept the methodological limitations of the data collection methodology that one is most comfortable or familiar with. Researchers who honestly understand and recognize their methodological limitations are most open to mixed methods research.  Fifth is the lack of knowledge of funding agencies and of the advantages a mixed methods study can offer over a mono method approach.

Consequently, funding agencies need to encourage the conduct of mixed methods research studies. A great example of this need is illustrated by the common randomized controlled trial. For every RCT with a negative outcome, a post-trial qualitative arm could add immensely to an understanding of why the trial didn’t work, or why it worked only for subgroups. Even trials with a positive outcome can be enhanced by a post-trial qualitative arm for similar reasons. When you look at the cost of an RCT, and the relatively cheap price of adding in a post-trial qualitative evaluation, it really emphasizes the lack of will to use routinely procedures that would really add a lot of bang for the buck.

Michael Fetters, MD, MPH, MA, editor,  Journal of Mixed Methods Research


Anonymized linked data from multiple social media channels voluntarily provided by users with their own annotations related to the social context in which such data were created and their personal relevance.

Anabel Quan-Haase, co-editor, The SAGE Handbook of Social Media Research Methods


Facebook and its associated platforms (Instagram and WhatsApp) are central to much of what people do with digital technology, from activism to socializing. They enable social action at scale across the world and also shape it through their affordances, design decisions, and various forms of automated filtering. But how, and how much, is hard for scientists to understand, because there is little data available for researchers. It would be a major step for social science and by extension for the public understanding of digital media if Facebook and other platform companies found ways of sharing more data.

Rasmus Kleis Nielsen, Ph.D., editor-in-chief, The International Journal of Press/Politics


I would like to see the integration of community college student outcome data with labor market outcome data as the norm rather than the exception.

Mark D’Amico, associate editor, Community College Review


This post originally appeared on SAGE Connection as part of its series on Love Your Data Week (February 13-17, 2017), an annual international event created to foster conversation and build awareness for quality research data management. Join the data conversation on social media by using the official Love Your Data Week hashtags #LYD17 and #loveyourdata.

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