Making Sense of Sensor Data: How Local Environmental Conditions Add Value to Social Science Research

Recent advances in computing technologies have enabled the development of low-cost, compact weather and air quality monitors. The U.S. federally funded Array of Things (AoT) project has deployed more than 140 such sensor nodes throughout the City of Chicago. This article combines a year’s worth of AoT sensor data with household data collected from 450 elderly Chicagoans in order to explore the feasibility of using previously unavailable data on local environmental conditions to improve traditional neighborhood research. Specifically, we pilot the use of AoT sensor data to overcome limitations in research linking air pollution to poor physical and mental health and find support for recent findings that exposure to pollutants contributes to both respiratory- and dementia-related diseases. We expect that this support will become even stronger as sensing technologies continue to improve and more AoT nodes come online, enabling additional applications to social science research where environmental context matters.

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Transfer of Data using Raspberry PI

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.34264 ◽

2021 ◽

Vol 9 (VI) ◽

pp. 2298-2302

Author(s):

Prof. Martand Jha

Keyword(s):

Social Science ◽

Data Sharing ◽

Digital Literacy ◽

Data Exchange ◽

Low Cost ◽

Social Science Research ◽

Science Research ◽

Literacy Skills ◽

Raspberry Pi ◽

Science Literature

Data sharing is not a new thing. Individuals, have been sharing the data between organizations and governments even before computers and networks were invented. However, advancements in digital literacy, skills, technology, and the adaptation of regulatory systems to the digital space over the last decade have allowed data to be exchanged more quickly and on a larger scale than ever before. We've started gathering examples of data sharing practice. The process of making research data accessible to other researchers or organizations for the purposes of social science research is known as data sharing. Informal data exchange among researchers and formal data exchange through data archives and repositories are both viable options for data sharing. Data exchange was first discussed in the social science literature. The advancement of computational technology for handling machine readable data, as well as the increased use of sample surveys as a primary mode of data collection, shaped the literature in the early 1960s. The Raspberry Pi is a simple embedded device with a small footprint and low cost that is used to minimize system complexity in terms of speed and area in real time applications.

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The Methodological Potential of Scrapbooking: Theory, Application, and Evaluation

Sociological Research Online ◽

10.1177/1360780420909128 ◽

2020 ◽

pp. 136078042090912

Author(s):

Ros Walling-Wefelmeyer

Keyword(s):

Social Media ◽

Social Science ◽

Social Science Research ◽

Science Research ◽

Social Media Platform ◽

Making Sense ◽

The Social ◽

The Everyday ◽

Theory Application ◽

Media Platform

The methodological possibilities of scrapbooking have hitherto been largely neglected in social science research. This article provides much needed theoretical and empirical insights into its potential, positing it as a practical and conceptual process of saving, sharing, and making sense(s) of the everyday and ephemeral. Scrapbooking highlights both the contingency and partiality of the scraps themselves and its own performance of giving them form. Research into how women experience and interpret ‘men’s intrusions’ over the course of 1 week put these ideas into practice. The study used both physical and digital scrapbooks, for which the social media platform Tumblr was employed. An evaluation of scrapbooking’s methodological potential produced three characteristic ‘tensions’: between freedom and constraint, between the raw and the processed, and between the therapeutic and the intrusive. These three tensions necessitate further exploration.

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“Poem is What?” Poetic Inquiry in Qualitative Social Science Research

International Review of Qualitative Research ◽

10.1525/irqr.2009.1.4.541 ◽

2009 ◽

Vol 1 (4) ◽

pp. 541-568 ◽

Cited By ~ 21

Author(s):

Monica Prendergast

Keyword(s):

Qualitative Research ◽

Social Science ◽

Social Science Research ◽

Science Research ◽

Critical Survey ◽

Federally Funded ◽

Poetic Inquiry ◽

Self Study ◽

Found Poetry ◽

Affective Dimensions

This paper articulates the findings of a two-year Canadian federally-funded postdoctoral study — Poetic inquiry in qualitative research: A critical survey — on the use of poetry in social science qualitative research practices. Based on a 1000+ page annotated bibliography gathered into a critical anthology as the data for this project, the discoveries emerged that are expressed below. The bibliography consists solely of poems included in over 230 studies found for this multidisciplinary project, supported by abstracts and brief contextual notes. Selection criteria for included studies were peer-reviewed journal contributions only, bracketing out anything that had appeared in book form, in ‘Poet's Corners’, and also excluding poems appearing in theses or dissertations. Some of these excluded poems are cited in a separate Appendix. These criteria were made simply to limit the scope of the study to a manageable scale. Most of this poetically-informed scholarship has appeared in the past decade, although some entries date as far back as the 1970's and 80's. Conclusions are that poetic inquiry most often addresses topics with clear affective dimensions, and can be distinguished between participant-based and self-study foci, with occasional examples of theoretical studies. Participant-based studies generally draw on the literary tradition of found poetry to represent participant data. Self-studies may address more philosophical, phenomenological and/or poststucturalist opportunities that present themselves through the use of poetry in social science contexts.

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