On Building Better Mousetraps and Understanding the Human Condition

2015 ◽  
Vol 659 (1) ◽  
pp. 33-47 ◽  
Author(s):  
Jimmy Lin
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Scientific Reasoning ◽  
Explanatory Power ◽  
Data Use ◽  
Human Condition ◽  
Science And Engineering ◽  
Disruptive Technologies ◽  
The Past ◽  
Data Collection And Analysis

Over the past few years, we have seen the emergence of “big data”: disruptive technologies that have transformed commerce, science, and many aspects of society. Despite the tremendous enthusiasm for big data, there is no shortage of detractors. This article argues that many criticisms stem from a fundamental confusion over goals: whether the desired outcome of big data use is “better science” or “better engineering.” Critics point to the rejection of traditional data collection and analysis methods, confusion between correlation and causation, and an indifference to models with explanatory power. From the perspective of advancing social science, these are valid reservations. I contend, however, that if the end goal of big data use is to engineer computational artifacts that are more effective according to well-defined metrics, then whatever improves those metrics should be exploited without prejudice. Sound scientific reasoning, while helpful, is not necessary to improve engineering. Understanding the distinction between science and engineering resolves many of the apparent controversies surrounding big data and helps to clarify the criteria by which contributions should be assessed.

scholarly journals Thinking about police data: Analysts’ perceptions of data quality in Canadian policing

2021 ◽  
pp. 0032258X2110214
Author(s):  
Christopher D O’Connor ◽  
John Ng ◽  
Dallas Hill ◽  
Tyler Frederick
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Data Quality ◽  
Research Culture ◽  
Police Services ◽  
Police Data ◽  
Data Collection And Analysis ◽  
Quality Issues

Policing is increasingly being shaped by data collection and analysis. However, we still know little about the quality of the data police services acquire and utilize. Drawing on a survey of analysts from across Canada, this article examines several data collection, analysis, and quality issues. We argue that as we move towards an era of big data policing it is imperative that police services pay more attention to the quality of the data they collect. We conclude by discussing the implications of ignoring data quality issues and the need to develop a more robust research culture in policing.

The Undergraduate Marketing Research Course: Two Decades of Change

2020 ◽  
pp. 027347532096050
Author(s):  
Eileen Bridges
Keyword(s):  
Data Collection ◽  
Data Analytics ◽  
New Technology ◽  
Marketing Research ◽  
Customer Data ◽  
Critical Gap ◽  
The Past ◽  
Data Collection And Analysis ◽  
Marketing Data ◽  
Observational Techniques

This article looks back over the past two decades to describe how teaching of undergraduate marketing research has (or has not) changed. Sweeping changes in technology and society have certainly affected how marketing research is designed and implemented—but how has this affected teaching of this important topic? Although the purpose of marketing research is still to better understand target customer needs, the tools are different now: customer data are typically collected using technology-based interfaces in place of such instruments as mailed, telephone, or in-person surveys. Observational techniques collect more data electronically rather than requiring a human recorder. Similarly, sampling has changed: sample frames are no longer widely used. Many of these changes are not yet fully discussed in marketing research courses. On the other hand, there is increasing interest in and availability of courses and programs in marketing data analytics, which teach specialized skills related to analysis and interpretation of electronic databases. Perhaps even more importantly, new technology-based tools permit greater automation of data collection and analysis, and presentation of findings. A critical gap is identified in this article; specifically, effort is needed to better integrate the perspectives of data collection and data analysis given current research conditions.

Social Implications of Big Data and Fog Computing

2020 ◽  
pp. 1564-1619
Author(s):  
Jeremy Horne
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Social Complexity ◽  
Fog Computing ◽  
Point Of View ◽  
Social Implications ◽  
Collection Management ◽  
Half Century ◽  
The Past ◽  
Artificial Brain

In the last half century, we have gone from storing data on 5¼ inch floppy diskettes to the cloud and now use fog computing. But one should ask why so much data is being collected. Part of the answer is simple in light of scientific projects, but why is there so much data on us? Then, we ask about its “interface” through fog computing. Such questions prompt this article on the philosophy of big data and fog computing. After some background on definitions, origins and contemporary applications, the main discussion begins with thinking about modern data collection, management, and applications from a complexity standpoint. Big data is turned into knowledge, but knowledge is extrapolated from the past and used to manage the future. Yet it is questionable whether humans have the capacity to manage contemporary technological and social complexity evidenced by our world in crisis and possibly on the brink of extinction. Such calls for a new way of studying societies from a scientific point of view. We are at the center of the observation from which big data emerge and are manipulated, the overall human project being not only to create an artificial brain with an attendant mind, but a society that might be able to survive what “natural” humans cannot.

Regional Ways of Seeing: A Big-Data Approach for Measuring Ancient Visualscapes

2020 ◽  
Vol 8 (2) ◽  
pp. 174-191
Author(s):  
Natalie M. Susmann
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Natural World ◽  
Natural Landscape ◽  
Analysis Methodology ◽  
Data Collection And Analysis ◽  
Geospatial Analyses ◽  
Human Decision ◽  
Topographic Characteristics ◽  
Religious Landscape

AbstractArchaeologists have long acknowledged the significance of mountains in siting Greek cult. Mountains were where the gods preferred to make contact and there people constructed sanctuaries to inspire intervention. Greece is a land full of mountains, but we lack insight on the ancient Greeks’ view—what visible and topographic characteristics made particular mountains ideal places for worship over others, and whether worshiper preferences ever changed. This article describes a data collection and analysis methodology for landscapes where visualscape was a significant factor in situating culturally significant activities. Using a big-data approach, four geospatial analyses are applied to every cultic place in the Peloponnesian regions of the Argolid and Messenia, spanning 2800–146 BC. The fully described methodology combines a number of experiences—looking out, looking toward, and climbing up—and measures how these change through time. The result is an active historic model of Greek religious landscape, describing how individuals moved, saw, and integrated the built and natural world in different ways. Applied elsewhere, and even on nonreligious locales, this is a replicable mode for treating the natural landscape as an artifact of human decision: as a space impacting the siting of meaningful locales through history.

Survey Research

2018 ◽  
pp. 257-276
Author(s):  
Ernest W. Brewer ◽  
Geraldine Torrisi-Steele ◽  
Victor C. X. Wang
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Collection ◽  
Survey Research ◽  
Mobile Devices ◽  
Historical Perspective ◽  
Human Condition ◽  
The Core ◽  
Digital World ◽  
Core Issues

Survey research, in various forms, is the mainstay for social researchers and anyone interested in finding out about people's opinions, attitudes, beliefs, and experiences. Survey research evolved from simple data collection to a more sophisticated scientific method and has proved useful in describing various aspects of the human condition as a basis for further action. However, now survey research is being challenged by the digital world as defined by big data, social media, and mobile devices. In the chapter, the authors provide a historical perspective on survey research, along with a brief presentation of foundational elements of survey research. Then, with the intent of evoking reflective discussion, the authors identify some of the core issues and viewpoints surrounding survey research in the present digital world.

scholarly journals Museum ethnography: Researching punishment museums as environments of narrativity

2017 ◽  
Vol 10 (1) ◽  
pp. 205979911772061
Author(s):  
Hannah Thurston
Keyword(s):  
Data Collection ◽  
Cultural Identity ◽  
Significant Role ◽  
Narrative Analysis ◽  
The Public ◽  
Crime And Punishment ◽  
The Past ◽  
Practical Guide ◽  
Data Collection And Analysis ◽  
History Of

Like all museums, punishment museums and sites of penal tourism are inherently political and moral institutions, offering cultural memories of a collective past. As environments of narrativity, these are significant spaces in which the public ‘learn’ about the past and how it continues to inform the present. In line with recent studies about ‘dark’ tourist sites, this article argues that the crime/punishment museum and jail cell tour can – and should – be understood as an ethnographic opportunity for narrative analysis. Rather than focus on just the findings of such an analysis, this article seeks to provide a practical guide to data collection and analysis in the context of criminological museum research. Offering illustrative examples from a study of Texan sites of penal tourism, it demonstrates how the history of punishment – as represented in museums – is an important part of cultural identity more broadly, playing a significant role in how we conceptualise (in)justice, morality and the purpose of punishment. In short, this article discusses how we can evoke the ethnographic tradition within museum spaces in order to interrogate how crime and punishment are expressed through narratives, images, objects and symbols.

Big Data and corporate reporting: impacts and paradoxes

2017 ◽  
Vol 30 (4) ◽  
pp. 850-873 ◽  
Author(s):  
Khaldoon Al-Htaybat ◽  
Larissa von Alberti-Alhtaybat
Keyword(s):  
Big Data ◽  
Explanatory Power ◽  
Sampling Strategy ◽  
Content Type ◽  
Corporate Reporting ◽  
Data Collection And Analysis ◽  
State Of Mind ◽  
Two Stages ◽  
The Impact ◽  
First Time

Purpose The purpose of this paper is to investigate the phenomenon of Big Data and corporate reporting, and to determine the impact of Big Data and the current Big Data state of mind with regard to corporate reporting, what accountant and non-accountant participants’ perceptions are of the phenomenon, what the accountants’ role is and will be in this regard, and what opportunities and risks are associated with Big Data and corporate reporting. Furthermore, this study seeks to identify the inherent technological paradoxes of Big Data and corporate reporting. Design/methodology/approach The current study is qualitative in nature and assumes an interpretive stance, investigating participants’ perceptions of the phenomenon of Big Data and corporate reporting. To this end, interview data from 25 participants, video and text material, were analysed to enhance and triangulate findings. A four-fold sampling strategy was employed to ensure that any collected data would contribute to the findings. Data were analysed on the basis of open and selective coding stages. Data collection and analysis took place in two stages, in 2014 and in 2016. Findings Three topics, or categories, emerged from the data analysis, which have sufficient explanatory power to illustrate the phenomenon of Big Data and corporate reporting, namely the Big Data state of mind and corporate reporting, accountants’ role and future related to Big Data, and perceived opportunities and risks of Big Data. Features of a new approach to corporate reporting were identified and discussed. Furthermore, four paradoxes emerged to express inherent opposing positions of Big Data and corporate reporting, namely empowerment vs enslavement, fulfilling vs creating needs, reliability vs timeliness and simplicity vs complexity. Originality/value The original contribution of the study lies in the empirical investigation of the phenomenon of Big Data and corporate reporting as one of the most recent and praised developments in the accounting context. The dual communication flows of corporate reporting with Big Data is an important element of the findings, which can enhance the prospective financial statements significantly. Finally, technological paradoxes of Big Data and corporate reporting are discussed for the first time, two of which are based on the literature and the remaining two are inherent in the phenomenon of Big Data and corporate reporting.

Discursive approaches

2015 ◽  
Author(s):  
Elizabeth H. Stokoe ◽  
Sally Wiggins
Keyword(s):  
Data Collection ◽  
Qualitative Analysis ◽  
Analytic Approach ◽  
Discursive Psychology ◽  
The Past ◽  
Data Collection And Analysis

This chapter introduces a method of qualitative analysis that focuses on exploring and explicating language in use. The discourse analytic approach discussed has developed within psychology over the past fifteen years and is called ‘discursive psychology’ (DP). The chapter outlines its origins and foundations, its theory and approach to language, its questions and topics of investigation, its methods of data collection and analysis and, for the current purposes, its utility for clinical and health psychologists.

scholarly journals The Drone Revolution of Shark Science: A Review

Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Paul A. Butcher ◽  
Andrew P. Colefax ◽  
Robert A. Gorkin ◽  
Stephen M. Kajiura ◽  
Naima A. López ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Data Collection ◽  
Social Interactions ◽  
Cryptic Species ◽  
Wildlife Management ◽  
Survey Methods ◽  
Knowledge Gaps ◽  
The Past ◽  
Data Collection And Analysis ◽  
Multiple Species

Over the past decade, drones have become a popular tool for wildlife management and research. Drones have shown significant value for animals that were often difficult or dangerous to study using traditional survey methods. In the past five years drone technology has become commonplace for shark research with their use above, and more recently, below the water helping to minimise knowledge gaps about these cryptic species. Drones have enhanced our understanding of shark behaviour and are critically important tools, not only due to the importance and conservation of the animals in the ecosystem, but to also help minimise dangerous encounters with humans. To provide some guidance for their future use in relation to sharks, this review provides an overview of how drones are currently used with critical context for shark monitoring. We show how drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. We further detail the advancement in technology across sensors, automation, and artificial intelligence that are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety. An investigation of the shark-based research potential for underwater drones (ROV/AUV) is also provided. Finally, this review provides baseline observations that have been pioneered for shark research and recommendations for how drones might be used to enhance our knowledge in the future.

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