scholarly journals Stepping into the Era of Personal Big Data: a Roadmap to the Design of a Personal Digital Life Coach (Preprint)

2016 ◽  
Author(s):  
Nuno M. Garcia ◽  
Nuno Pombo ◽  
Torsten Braun ◽  
Francisco Flórez-Revuelta ◽  
Ivan Chorbev ◽  
...  
Keyword(s):  
Big Data ◽  
Position Paper ◽  
Hardware Platform ◽  
Distant Future ◽  
Individual Level ◽  
Training Tool ◽  
Networking Tool ◽  
Software And Hardware ◽  
The Individual ◽  
And Training

UNSTRUCTURED The increased availability of devices that can record every aspect of a person’s life will allow the recording of a large amount of data that will be primarily useful for that particular user. These devices and their data will place each and every one of us at the doorstep of the era of personal big data. Using this data, in a not so distant future, we will be able to set a personal digital life coach, a digital platform that will act at an individual level, but also considering a global interaction, not only as a social networking tool, but as a platform that will profit from the individual experiences of its users. This position paper focuses on the identification of the milestones that will mark the creation of such a software and hardware platform, by exploring the opportunities and challenges that it poses to the computer science researchers, and how such a solution can be designed to be a user-adoptable lifestyles monitoring and training tool.

scholarly journals Stepping into the Era of Personal Big Data: a Roadmap to the Design of a Personal Digital Life Coach

2021 ◽  
Author(s):  
Cheyanne Mari Yanez
Keyword(s):  
Big Data ◽  
Computer Science ◽  
Position Paper ◽  
Hardware Platform ◽  
Distant Future ◽  
Individual Level ◽  
Training Tool ◽  
Software And Hardware ◽  
The Individual ◽  
And Training

The increased availability of devices that can record every aspect of a person’s life will allow the recording of a large amount ofdata that will be primarily useful for that particular user. These devices and their data will place each and every one of us at thedoorstep of the era of personal big data. Using this data, in a not so distant future, we will be able to set a personal digital lifecoach, a digital platform that will act at an individual level, but also considering a global interaction, not only as a socialnetworking tool, but as a platform that will profit from the individual experiences of its users. This position paper focuses on theidentification of the milestones that will mark the creation of such a software and hardware platform, by exploring theopportunities and challenges that it poses to the computer science researchers, and how such a solution can be designed to be auser-adoptable lifestyles monitoring and training tool.

scholarly journals Women in Blue: Structural and Individual Determinants of Sex Segregation in Blue-Collar Occupations

2019 ◽  
Vol 33 (3) ◽  
pp. 410-438 ◽  
Author(s):  
Margarita Torre
Keyword(s):  
Social Reproduction ◽  
Blue Collar ◽  
Gender Composition ◽  
Vocational Education And Training ◽  
Individual Level ◽  
Parental Background ◽  
Individual Determinants ◽  
Nationally Representative ◽  
The Individual ◽  
And Training

The number of women occupying male-dominated blue-collar jobs continues to be very low. This study examines segregation in the blue-collar trades, taking into consideration both structural and individual factors. Using nationally representative data for 25 countries, the study shows that segregation in the blue-collar sector does not vary with the strength of vocational education and training programs. At the individual level, findings reveal higher degrees of social reproduction among working-class families, but parental background alone does not fully account for the gender composition of the sector in which children end up working. Overall, the findings point to the existence of a socializing mechanism that entrenches horizontal segregation in the blue-collar sector. The study indicates that to reduce segregation in the blue-collar fields, policies must address this prior mechanism, both at the structural and individual level.

scholarly journals Personalization as a promise: Can Big Data change the practice of insurance?

2020 ◽  
Vol 7 (1) ◽  
pp. 205395172093514 ◽  
Author(s):  
Laurence Barry ◽  
Arthur Charpentier
Keyword(s):  
Big Data ◽  
Predictive Analytics ◽  
Special Focus ◽  
New Paradigm ◽  
Individual Level ◽  
Big Data Technologies ◽  
State Of Research ◽  
The Individual ◽  
Homogeneity Hypothesis ◽  
The Impact

The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanisms adopted the same aggregate viewpoint. It made visible regularities that were invisible at the individual level, further supporting the classificatory approach of insurance and the assumption that all members of a class are identical risks. The second part focuses on the reversal of perspective currently occurring in data analysis with predictive analytics, and how this conceptually contradicts the collective basis of insurance. The tremendous volume of data and the personalization promise through accurate individual prediction indeed deeply shakes the homogeneity hypothesis behind pooling. The third part attempts to assess the extent of this shift in motor insurance. Onboard devices that collect continuous driving behavioural data could import this new paradigm into these products. An examination of the current state of research on models with telematics data shows however that the epistemological leap, for now, has not happened.

scholarly journals SleepOMICS: How Big Data Can Revolutionize Sleep Science

2019 ◽  
Vol 16 (2) ◽  
pp. 291 ◽  
Author(s):  
Nicola Luigi Bragazzi ◽  
Ottavia Guglielmi ◽  
and Sergio Garbarino
Keyword(s):  
Developing Countries ◽  
Big Data ◽  
Sleep Disorders ◽  
Real Life ◽  
The Elderly ◽  
Sleep Medicine ◽  
Sleep Research ◽  
Profound Impact ◽  
Individual Level ◽  
The Individual

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. “Real-life” behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level (“sleepOMICS”), thus paving the way for a targeted, “one-size-does-not-fit-all” management of sleep disorders (“precision sleep medicine”).

Gamifying with badges: A big data natural experiment on Stack Exchange

First Monday ◽  
2017 ◽  
Author(s):  
Benny Bornfeld ◽  
Sheizaf Rafaeli
Keyword(s):  
Big Data ◽  
Effect Size ◽  
Natural Experiment ◽  
User Behavior ◽  
Online Systems ◽  
Individual Level ◽  
The Individual

Badges are a common gamification mechanism used by many crowd-sourced online systems. This study provides evidence to their effectiveness and measures their effect size using a big data natural experiment in three large Stack Exchange online Q&A sites. We analyze the introduction of 22 different badge-launch events and the resulting changes in user behavior. Consistent with earlier studies, we report that most badge introductions have the desired effect. Going beyond traditional findings on the individual level, this study measures overall badge effect size on the service.

scholarly journals Establishing a Dementia-Inclusive Community: The Evaluation of Dementia Friends in Cleveland Heights

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 514-514
Author(s):  
Jennifer Cardellini ◽  
Sarah Nicolay ◽  
Jessica Bibbo
Keyword(s):  
Education And Training ◽  
Community Member ◽  
Community Living ◽  
Community Members ◽  
National Network ◽  
Individual Level ◽  
On Line ◽  
The Individual ◽  
Two Sectors ◽  
And Training

Abstract Cleveland Heights, in northeast Ohio, is currently working towards becoming a member of the Dementia Friendly America National Network. Utilizing the Dementia Friends curriculum to raise community members’ awareness of issues related to dementia is a key component of this initiative. Our initial efforts toward this goal targeted two sectors, namely community member and libraries. Participants completed on-line surveys at the beginning and end of each session. The surveys include the Brief Tool for Dementia-Friendly Education and Training Sessions developed by the Administration for Community Living. Of the 22 participants, nine had not previously attended a Dementia Friends session and completed both pre- and post-session surveys. Results indicated participants felt more confident interacting with people living with dementia at post-session compared to pre-session (t = -2.83, p=.022). Changes at the individual level may create more inclusive communities for people living with dementia and those who care for and about them.

scholarly journals A big data analysis of the relationship between future thinking and decision-making

2018 ◽  
Vol 115 (8) ◽  
pp. E1740-E1748 ◽  
Author(s):  
Robert Thorstad ◽  
Phillip Wolff
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Population Level ◽  
Future Thinking ◽  
Individual Level ◽  
The Future ◽  
The Individual ◽  
Near Future ◽  
The Relationship ◽  
Far Future

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people’s thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people’s tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people’s tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.

scholarly journals O6E.2 Exposure assessment for a study of cognitive impairment in former professional footballers in england

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A59.2-A59
Author(s):  
Damien Mcelvenny ◽  
Ioannis Basinas ◽  
Richard Graveling ◽  
John Cherrie ◽  
Valeintina Gallo ◽  
...  
Keyword(s):  
Exposure Assessment ◽  
Study Cohort ◽  
List Type ◽  
Head Impacts ◽  
Individual Level ◽  
Video Footage ◽  
Predictive Variables ◽  
Increased Risk ◽  
The Individual ◽  
And Training

Evidence is accumulating on the possible increased risks of neurodegenerative disease in former (professional) sportspersons. This study will assess the associations between a history of repetitive low-level head trauma and general and neurological health in retired professional footballers aged 50+in England. The main exposure measures are concussions and cumulative lifetime repeated sub-concussive head impacts (RSHIs), either from heading footballs or other forces applied to the head. Information on factors associated with concussions and RSHIs will be collected via a structured questionnaire during face-to-face interviews.Our approach will include:Literature search to identify potentially important proxy measures of RSHI during training and matches;Developing a model of cumulative RSHIs, based on the more strongly predictive variables, which may include playing position, the frequency of heading, the number of games played and training sessions attended, decade of play and the type of ball used.The model will be developed from analyses of head contacts from video footage of matches and training, at the individual level and in general, and from statistics on playing career. We will also consult a panel of former professional footballers on the exposure assessment.The exposure data will be crucial to assess whether those with higher exposure within the study cohort are at increased risk compared to those with lower exposure.

Towards a clean slate: Attempting to preserve civil liberty in the post-Snowden age

2015 ◽  
Vol 57 (3) ◽  
Author(s):  
Alexander von Gernler
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Mobile Computing ◽  
Civil Liberty ◽  
Democratic Society ◽  
Single Individual ◽  
Individual Level ◽  
Diffusion Of Technology ◽  
The Individual

AbstractWide adoption of mobile computing, smartphones, social networks and big data techniques have brought undoubtable advantages to society as such, as well as to its individuals. The downside of this diffusion of technology throughout society has already been well discussed. Single authors also pointed out the threats not only to the single individual, but to democratic society as a whole. However, suggestions or even practical approaches of how to mitigate these threats not only at the individual level (

scholarly journals Orchestrating privacy-protected big data analyses of data from different resources with R and DataSHIELD

2021 ◽  
Vol 17 (3) ◽  
pp. e1008880
Author(s):  
Yannick Marcon ◽  
Tom Bishop ◽  
Demetris Avraam ◽  
Xavier Escriba-Montagut ◽  
Patricia Ryser-Welch ◽  
...  
Keyword(s):  
Big Data ◽  
Epidemiological Studies ◽  
Individual Level ◽  
Data Analyses ◽  
Level Data ◽  
Data Integration System ◽  
R Packages ◽  
Legal Constraints ◽  
Online Book ◽  
The Individual

Combined analysis of multiple, large datasets is a common objective in the health- and biosciences. Existing methods tend to require researchers to physically bring data together in one place or follow an analysis plan and share results. Developed over the last 10 years, the DataSHIELD platform is a collection of R packages that reduce the challenges of these methods. These include ethico-legal constraints which limit researchers’ ability to physically bring data together and the analytical inflexibility associated with conventional approaches to sharing results. The key feature of DataSHIELD is that data from research studies stay on a server at each of the institutions that are responsible for the data. Each institution has control over who can access their data. The platform allows an analyst to pass commands to each server and the analyst receives results that do not disclose the individual-level data of any study participants. DataSHIELD uses Opal which is a data integration system used by epidemiological studies and developed by the OBiBa open source project in the domain of bioinformatics. However, until now the analysis of big data with DataSHIELD has been limited by the storage formats available in Opal and the analysis capabilities available in the DataSHIELD R packages. We present a new architecture (“resources”) for DataSHIELD and Opal to allow large, complex datasets to be used at their original location, in their original format and with external computing facilities. We provide some real big data analysis examples in genomics and geospatial projects. For genomic data analyses, we also illustrate how to extend the resources concept to address specific big data infrastructures such as GA4GH or EGA, and make use of shell commands. Our new infrastructure will help researchers to perform data analyses in a privacy-protected way from existing data sharing initiatives or projects. To help researchers use this framework, we describe selected packages and present an online book (https://isglobal-brge.github.io/resource_bookdown).

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