2018
DOI: 10.17705/1jais.00526
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Data-Driven Meets Theory-Driven Research in the Era of Big Data: Opportunities and Challenges for Information Systems Research

Abstract: The era of big data provides many opportunities for conducting impactful research from both datadriven and theory-driven perspectives. However, data-driven and theory-driven research have progressed somewhat independently. In this paper, we develop a framework that articulates important differences between these two perspectives and propose a role for information systems research at their intersection. The framework presents a set of pathways that combine the datadriven and theory-driven perspectives. From the… Show more

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Cited by 79 publications
(64 citation statements)
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References 60 publications
(64 reference statements)
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“…For this project, a data-driven research approach was followed using proteomics to generate an overview regarding the potential molecular effects of OmEO therapy, instead of a solely theory- or hypothesis-driven research approach [ 61 ]. Initially, 1224 proteins were identified in the rat brain tissue containing hippocampi ( Supplemental File 3 ), which were ranked according to their relative abundances in the Aβ1-42 group (II) ( Figure 2 ).…”
Section: Resultsmentioning
confidence: 99%
“…For this project, a data-driven research approach was followed using proteomics to generate an overview regarding the potential molecular effects of OmEO therapy, instead of a solely theory- or hypothesis-driven research approach [ 61 ]. Initially, 1224 proteins were identified in the rat brain tissue containing hippocampi ( Supplemental File 3 ), which were ranked according to their relative abundances in the Aβ1-42 group (II) ( Figure 2 ).…”
Section: Resultsmentioning
confidence: 99%
“…Complete sets of data describing study and workflow (segment) designs are essential for the repeatability of study setups and the potential reproducibility of results. This includes all types of research projects and studies with theory-driven and data-driven study design and research perspectives ( 37 ).…”
Section: Abstract Model For Analysing and Describing Fair Digital Objmentioning
confidence: 99%
“…Due to the development of recent technologies and practices such as crowdsourcing (participatory systems that involve publics in collaborative projects; Lukyanenko & Parsons, 2012) and data science (a set of techniques and theories that help distil insight from data; Provost & Fawcett, 2013), the collection and organising of large amounts of data has become commonplace. This brings us to an important tension (see Maass et al, 2018). Larger, more complex data-driven models are likely to be more representative as they capture more perspectives and nuances than simpler models and as their representations can be tested through the simulations and analysis of systems dynamics.…”
Section: Finding Leverage In Systemic Designmentioning
confidence: 99%