Paper by Chitu Okoli: “The ongoing debates in the information systems (IS) discipline on the nature of theory are implicitly rooted in different epistemologies of the social sciences and in a lack of consensus on a definition of theory. Thus, we focus here on the much-neglected topic of what constitutes the bare minimum of what can possibly be considered theory—only by carefully understanding the bare minimum can we really understand the essence of what makes a theory a theory. We definitionally define a theory in the social sciences as an explanation of the relationship between two or more measurable... (More >)
A Computational Inflection for Scientific Discovery
Paper by Tom Hope, Doug Downey, Oren Etzioni, Daniel S. Weld, and Eric Horvitz: “We stand at the foot of a significant inflection in the trajectory of scientific discovery. As society continues on its fast-paced digital transformation, so does humankind’s collective scientific knowledge and discourse. We now read and write papers in digitized form, and a great deal of the formal and informal processes of science are captured digitally — including papers, preprints and books, code and datasets, conference presentations, and interactions in social networks and communication platforms. The transition has led to the growth of a tremendous amount... (More >)
How does research data generate societal impact?
Blog by Eric Jensen and Mark Reed: “Managing data isn’t exciting and it can feel like a hassle to deposit data at the end of a project, when you want to focus on publishing your findings. But if you want your research to have impact, paying attention to data could make a big difference, according to new research we published recently in the journal PLOS ONE. We analysed case studies from the UK Research Excellence Framework (REF) exercise in 2014 to show how data analysis and curation can generate benefits for policy and practice, and sought to understand the... (More >)
Accelerating ethics, empathy, and equity in geographic information science
Paper by T. A. Nelson, F. Goodchild and D. J. Wright: “Science has traditionally been driven by curiosity and followed one goal: the pursuit of truth and the advancement of knowledge. Recently, ethics, empathy, and equity, which we term “the 3Es,” are emerging as new drivers of research and disrupting established practices. Drawing on our own field of GIScience (geographic information science), our goal is to use the geographic approach to accelerate the response to the 3Es by identifying priority issues and research needs that, if addressed, will advance ethical, empathic, and equitable GIScience. We also aim to stimulate... (More >)
Opening Up to Open Science
Essay by Chelle Gentemann, Christopher Erdmann and Caitlin Kroeger: “The modern Hippocratic Oath outlines ethical standards that physicians worldwide swear to uphold. “I will respect the hard-won scientific gains of those physicians in whose steps I walk,” one of its tenets reads, “and gladly share such knowledge as is mine with those who are to follow.” But what form, exactly, should knowledge-sharing take? In the practice of modern science, knowledge in most scientific disciplines is generally shared through peer-reviewed publications at the end of a project. Although publication is both expected and incentivized—it plays a key role in career... (More >)
Citizen science and environmental justice: exploring contradictory outcomes through a case study of air quality monitoring in Dublin
Paper by Fiadh Tubridy et al: “Citizen science is advocated as a response to a broad range of contemporary societal and ecological challenges. However, there are widely varying models of citizen science which may either challenge or reinforce existing knowledge paradigms and associated power dynamics. This paper explores different approaches to citizen science in the context of air quality monitoring in terms of their implications for environmental justice. This is achieved through a case study of air quality management in Dublin which focuses on the role of citizen science in this context. The evidence shows that the dominant interpretation... (More >)
Time to recognize authorship of open data
Nature Editorial: “At times, it seems there’s an unstoppable momentum towards the principle that data sets should be made widely available for research purposes (also called open data). Research funders all over the world are endorsing the open data-management standards known as the FAIR principles (which ensure data are findable, accessible, interoperable and reusable). Journals are increasingly asking authors to make the underlying data behind papers accessible to their peers. Data sets are accompanied by a digital object identifier (DOI) so they can be easily found. And this citability helps researchers to get credit for the data they generate.... (More >)
Measuring costs and benefits of citizen science
Article by Kathy Tzilivakis: “It’s never been easy to accurately measure the impact of any scientific research, but it’s even harder for citizen science projects, which don’t follow traditional methods. Public involvement places citizen science in a new era of data collection, one that requires a new measurement plan. As you read this, thousands of ordinary people across Europe are busy tagging, categorizing and counting in the name of science. They may be reporting crop yields, analyzing plastic waste found in nature or monitoring the populations of wildlife. This relatively new method of public participation in scientific enquiry is... (More >)
Should we get rid of the scientific paper?
Article by Stuart Ritchie: “But although the internet has transformed the way we read it, the overall system for how we publish science remains largely unchanged. We still have scientific papers; we still send them off to peer reviewers; we still have editors who give the ultimate thumbs up or down as to whether a paper is published in their journal. This system comes with big problems. Chief among them is the issue of publication bias: reviewers and editors are more likely to give a scientific paper a good write-up and publish it in their journal if it reports... (More >)
Decoding human behavior with big data? Critical, constructive input from the decision sciences
Paper by Konstantinos V. Katsikopoulos and Marc C. Canellas: “Big data analytics employs algorithms to uncover people’s preferences and values, and support their decision making. A central assumption of big data analytics is that it can explain and predict human behavior. We investigate this assumption, aiming to enhance the knowledge basis for developing algorithmic standards in big data analytics. First, we argue that big data analytics is by design atheoretical and does not provide process-based explanations of human behavior; thus, it is unfit to support deliberation that is transparent and explainable. Second, we review evidence from interdisciplinary decision science,... (More >)
