https://andreashellander.se/wp-content/uploads/2016/01/1-s2.0-S0306437914001288-main.pdf

The rise of big data on cloud computing

This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society. It is argued that: (1) Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and (2) there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology.

https://journals.sagepub.com/doi/pdf/10.1177/2053951714528481

Big Data, new epistemologies and paradigm shifts:

Metadata and data have become a regular currency for citizens to pay for their communication services and security—a trade-off that has nestled into the comfort zone of most people. This article deconstructs the ideological grounds of datafication. Datafication is rooted in problematic ontological and epistemological claims. As part of a larger social media logic, it shows characteristics of a widespread secular belief. Dataism, as this conviction is called, is so successful because masses of people — naively or unwittingly — trust their personal information to corporate platforms. The notion of trust becomes more problematic because people’s faith is extended to other public institutions (e.g. academic research and law enforcement) that handle their (meta)data. The interlocking of government, business, and academia in the adaptation of this ideology makes us want to look more critically at the entire ecosystem of connective media.

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Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology

Big data has the potential to revolutionize the art of management. Despite the high operational and strategic impacts, there is a paucity of empirical research to assess the business value of big data. Drawing on a systematic review and case study findings, this paper presents an interpretive framework that analyzes the definitional perspectives and the applications of big data. The paper also provides a general taxonomy that helps broaden the understanding of big data and its role in capturing business value. The synthesis of the diverse concepts within the literature on big data provides deeper insights into achieving value through big data strategy and implementation.

How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study

The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of "Big Data," including the recent announcement from the White House about new funding initiatives across different agencies, that target research for Big Data. While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is no clear consensus on what is Big Data. In fact, there have been many controversial statements about Big Data, such as "Size is the only thing that matters." In this panel we will try to explore the controversies and debunk the myths surrounding Big Data.

/pdf/challenges-and-opportunities-with-big-data-3y1bgwksol.pdf

Challenges and opportunities with big data

ZusammenfassungMit “Big Data” werden Technologien beschrieben, die nicht weniger als die Erfüllung eines der Kernziele der Wirtschaftsinformatik versprechen: die richtigen Informationen dem richtigen Adressaten zur richtigen Zeit in der richtigen Menge am richtigen Ort und in der erforderlichen Qualität bereitzustellen. Für die Wirtschaftsinformatik als anwendungsorientierte Wissenschaftsdisziplin entstehen durch solche technologischen Entwicklungen Chancen und Risiken. Risiken entstehen vor allem dadurch, dass möglicherweise erhebliche Ressourcen auf die Erklärung und Gestaltung von Modeerscheinungen verwendet werden. Chancen entstehen dadurch, dass die entsprechenden Ressourcen zu substanziellen Erkenntnisgewinnen führen, die dem wissenschaftlichen Fortschritt der Disziplin wie auch ihrer praktischen Relevanz dienen.Aus Sicht der Autoren ist die Wirtschaftsinformatik ideal positioniert, um Big Data kritisch zu begleiten und Erkenntnisse für die Erklärung und Gestaltung innovativer Informationssysteme in Wirtschaft und Verwaltung zu nutzen – unabhängig davon, ob Big Data nun tatsächlich eine disruptive Technologie oder doch nur eine flüchtige Modeerscheinung ist. Die weitere Entwicklung und Adoption von Big Data wird letztendlich zeigen, ob es sich um eine Modeerscheinung oder um substanziellen Fortschritt handelt. Die aufgezeigten Thesen zeigen darüber hinaus auch, wie künftige technologische Entwicklungen für den Fortschritt der Disziplin Wirtschaftsinformatik genutzt werden können. Technologischer Fortschritt sollte für eine kumulative Ergänzung bestehender Modelle, Werkzeuge und Methoden genutzt werden. Dagegen sind wissenschaftliche Revolutionen unabhängig vom technologischen Fortschritt.Abstract“Big data” describes technologies that promise to fulfill a fundamental tenet of research in information systems, which is to provide the right information to the right receiver in the right volume and quality at the right time. For information systems research as an application-oriented research discipline, opportunities and risks arise from using big data. Risks arise primarily from the considerable number of resources used for the explanation and design of fads. Opportunities arise because these resources lead to substantial knowledge gains, which support scientific progress within the discipline and are of relevance to practice as well.From the authors’ perspective, information systems research is ideally positioned to support big data critically and use the knowledge gained to explain and design innovative information systems in business and administration – regardless of whether big data is in reality a disruptive technology or a cursory fad. The continuing development and adoption of big data will ultimately provide clarity on whether big data is a fad or if it represents substantial progress in information systems research. Three theses also show how future technological developments can be used to advance the discipline of information systems. Technological progress should be used for a cumulative supplement of existing models, tools, and methods. By contrast, scientific revolutions are independent of technological progress.

Big Data: Eine interdisziplinäre Chance für die Wirtschaftsinformatik

Abstract“Big data” describes technologies that promise to fulfill a fundamental tenet of research in information systems, which is to provide the right information to the right receiver in the right volume and quality at the right time. For information systems research as an application-oriented research discipline, opportunities, and risks arise from using big data. Risks arise primarily from the considerable number of resources used for the explanation and design of fads. Opportunities arise because these resources lead to substantial knowledge gains, which support scientific progress within the discipline and are of relevance to practice as well.From the authors’ perspective, information systems research is ideally positioned to support big data critically and use the knowledge gained to explain and design innovative information systems in business and administration – regardless of whether big data is in reality a disruptive technology or a cursory fad. The continuing development and adoption of big data will ultimately provide clarity on whether big data is a fad or if it represents substantial progress in information systems research. Three theses also show how future technological developments can be used to advance the discipline of information systems. Technological progress should be used for a cumulative supplement of existing models, tools, and methods. By contrast, scientific revolutions are independent of technological progress.

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1297&context=bise

Big Data - An Interdisciplinary Opportunity for Information Systems Research

Durch die Digitalisierung von Wirtschaft und Gesellschaft ist ein rasantes Anwachsen von Datenbest?nden zu beobachten. In fast allen Unternehmens sowie Wissenschaftsbereichen werden bereits heute schon Unmengen an Daten erzeugt, deren Gr??e, Erfassungsgeschwindigkeit oder Heterogenit?t die F?higkeiten g?ngiger Datenbanksoftwareprodukte zur Verwaltung und zur Analyse ?bersteigt. Dieses Ph?nomen, welches unter dem Schlagwort ?Big Data? popularisiert wurde, stellt eine gro?e Chance f?r Unternehmen, Wissenschaft und Gesellschaft dar. Allerdings ergibt sich aufgrund der neuen Komplexit?t der Daten und Analysen eine Vielzahl an Herausforderungen technischer, wirtschaftlicher und rechtlicher Natur. Diese Studie analysiert die Chancen und Herausforderungen von Big Data insbesondere im Hinblick auf eine nachhaltige Wettbewerbsf?higkeit Deutschlands.

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Christoph Buchmüller

Papers

Big Data: Eine interdisziplinäre Chance für die Wirtschaftsinformatik

Big Data - An Interdisciplinary Opportunity for Information Systems Research

Innovationspotenzialanalyse für die neuen Technologien für das Verwalten und Analysieren von großen Datenmengen (Big Data Management)