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The community dedicated to the discussion and advancement of Big Data Analysis

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Sweet Sound of Big Data in the Music Industry

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Fifteen years ago, Steve Jobs introduced the iPod. Since then, most music fans have understood this has radically changed how they listen to music. Less understood are the ways that raw information – accumulated via downloads, apps and online searches – is influencing not only what songs are marketed and sold, but which songs become […]

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Big Data and Social Research Roundup No. 10

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What is computational social science? This question underpins the first of four videos synthesizing themes covered at last year’s International Conference on Computational Social Science. Among the academics and practitioners venturing answers, Princeton’s Matthew Salganik stresses that the explosion of data and the ability to harness it represent a “fundamental transition that’s occurring whether social […]

Categories: Big Data, SAGE Posts

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Emma Uprichard: Big Data and ‘Methodological Genocide’

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As the final entry in the LSE Impact of Social Science blog’s Philosophy of Data Science series, Emma Uprichard tells interviewer Mark Carrigan that big data has serious repercussions to the kinds of social futures we are shaping — and those that are supporting big data developments need to be held accountable. Uprichard, associate professor and […]

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Can Big Data Analysis of Police Activity Overcome Bias?

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In early 2017, Chicago Mayor Rahm Emanuel announced a new initiative in the city’s ongoing battle with violent crime. The most common solutions to this sort of problem involve hiring more police officers or working more closely with community members. But Emanuel declared that the Chicago Police Department would expand its use of software, enabling […]

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Encouraging Authors to Share Their Data with Reviewers for ‘Psychological Science’

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The journal Psychological Science is taking steps to encourage would-be authors to give reviewers easy access to the data underlying the analyses reported in their manuscripts. This is part of a wider effort to promote transparency and replicability in works published in the journal. I discussed the rationale for encouraging authors to share data and […]

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How Will Big Data Affect Evolution of Social Science?

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Social scientists have, overall, been slower to tap into the ever-increasing flow of “big data” than their peers in the physical and medical sciences. That lethargy is a tad ironic given that so much of the big data available, whether it be government administrative data or social media feeds like Twitter, don’t have to be […]

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Video: ‘Big Data New Skills’ Panel at RC33

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How will innovations in research methods and the new data environment impact teaching and research? That was the underlying question during a panel discussion hosted by SAGE Publishing at the 9th International Conference on Social Science Methodology. The conference, held every four years under the auspices of the International Sociological Association  Research Committee RC33 on […]

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DataKindUK DataDive: A Quick Look at the Hackathon

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In late September SAGE Publishing sponsored DataKindUK’s DataDive, a hackathon bringing volunteer data scientists and social non-profits and social enterprises together for a weekend of social change through data analysis. A ‘data dive’ is a focused hacking weekend that works with a selected non-profit or social enterprise to help them improve their understanding of their […]

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UK Data Service: Data driven research – Access, analyse, evidence

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10 December 2014 London School of Economics This free half-day workshop offers an introduction to the data, resources and support available from the UK Data Service. The workshop is aimed at researchers in the social sciences and related disciplines, research methods teachers and librarians who wish to learn more about the resources and support offered […]

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Big Data – interesting reads

This is a group for anyone interested in big data research who wants to share links of interest on the topic.

Public Group / 14 members

Actor Network Theory

Discussion and application of ANT

Public Group / 22 members

Advanced Visualisation Group

There is well – forgotten way of visualization of Big Data usually used by applied mathematicians in natural sciences. In comparison with popular Visual Story Telling,this kind of  mathematical visualization assumes an e

Public Group / 4 members

Big Data – interesting reading

This is a group for anyone interested in big data research who wants to share links of interest on the topic.

Categories:

Actor Network Theory

Discussion and application of ANT

Categories:

Advanced Visualisation Group

There is well – forgotten way of visualization of Big Data usually used by applied mathematicians in natural sciences. In comparison with popular Visual Story Telling,this kind of  mathematical visualization assumes an existence of some Platonic mathematical structures and objects behind Data. Hence,we always can reduce Data to equation, theorem and thus to deduce real prediction of […]

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Census.ac.uk

A group for those interested in discussing the reuse of UK census data.

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Getting Comfortable with Big Data

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Date/Time
Date(s) - 05/27/2017
4:00 pm - 5:30 pm

Location
Sheraton Boston Hotel

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This session at the annual meeting of the Association for Psychological Science in Boston, Massachusetts follows up from a white paper on ‘Who is doing computational social science?’ released last year by SAGE Publishing, and will look at the back story of Big Data social science and the fast-paced evolution of entice opportunities and methods to confront those challenges. Who is doing computational social science, and why? Among social scientists and humanities scholars, there is a clear appetite to engage with data at an accelerated rate. And while a recent study suggests that a majority of researchers who hadn’t yet used Big Data would like to, the challenge of the new remains.

Panelists 

  • Nick Beauchamp, assistant professor, Department of Political Science, NULab for Texts, Maps and Networks, Network Science Institute, Northeastern University
  • Ryan Kling, economist and senior associate at Abt Associates’ Health Division. Abt is a mission-driven, global leader in research, evaluation and program implementation in the fields of health, social and environmental policy, and international development.
  • Kenny Joseph, postdoc at LazerLab at the Network Science Institute at Northeastern University and a fellow at Harvard’s Institute for Quantitative Social Science.
  • Kris-Stella Trump, political scientist and policy researcher – currently a research specialist at the Center for Healthcare Delivery Sciences at Brigham & Women’s Hospital and Harvard Medical School, with a joint appointment to the Office of Evaluation Sciences at the General Services Administration.

The session occurs at Back Bay C Room in the Boston Sheraton at 4 p.m. on May 27.

Improving the Reproducibility of Computational Research

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Date/Time
Date(s) - 03/29/2017
11:00 am - 12:30 pm

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As the data collection ability of nearly every area of science has ballooned, so has the potential for problematic research practices that can lead to irreproducible results.  In this National Science Foundation Directorate for Computer & Information Science & Engineering Distinguished Lecture, Russell Poldrack of Stanford University will discuss a set of approaches that we are developing to address this reproducibility crisis in the context of human neuroimaging research. These include an integrated platform for the analysis and open sharing of neuroimaging data, frameworks for the description of data and metadata, and the use of software containers and virtual machines to enhance computational reproducibility.  Poldrack will show how these approaches have the potential to enable a new era of reproducibility in science.

The lecture will be held at Room 110 of the NSF campus at 4201 Wilson Boulevard in Arlington, Virginia. It will also be webcast; to view the free webinar please register at: http://www.tvworldwide.com/events/nsf/170329/

Poldrack is the Albert Ray Lang Professor in the Department of Psychology at Stanford, and director of the Stanford Center for Reproducible Neuroscience.  His research uses neuroimaging to understand the brain systems underlying decision making and executive function.  His lab is also engaged in the development of neuroinformatics tools to help improve the reproducibility and transparency of neuroscience, including the OpenfMRI.org and Neurovault.org data sharing projects and the Cognitive Atlas ontology.

For more information, click here.

Webinar: Linking Data to Understand People in Context

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Date/Time
Date(s) - 02/27/2017
9:00 am - 10:00 am

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Drawn from scholarship appearing in the current issue of The ANNALS of the American Academy of Political and Social Science, this free webinar explores the nexus of actionable analysis and big data from public, private and research sources.

Four researchers in the thick of tapping a broad array of information from disparate sources like administrative data, social media, smartphones, the Census, and experiments, and using that data to promote good policies for individual and communities, are panelists for this event: sociologist Christopher R. Browning of The Ohio State University; Barbara Entwisle, Kenan Professor of Sociology at the University of North Carolina at Chapel Hill; Elizabeth Fussell of the Population Studies and Training Center at Brown University; and Emilio F. Moran, John A. Hannah Distinguished Professor at Michigan State University and co-guest editor of the ANNALS volume.

The webinar, “The New Big Science: Linking Data to Understand People in Context,” is scheduled for 9 a.m. PT/noon ET on February 27. It is free, but attendees are urged to register in advance because online space is limited.

To register, CLICK HERE.

Hacking Big Data and Open Data in San Diego

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Date/Time
Date(s) - 02/18/2017
All Day

Location
San Diego State University

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February 18 will see the first round of the Big Data Hackathon/San Diego. Your challenge is to create an app, platform, and/or technology that can tie into the public health theme using datasets provided via the hackathon’s special GitHub site.

Bring your ingenuity, creativity, imagination, a laptop and a charger! Anyone is welcome to participate.
Students, engineers, developers, programmers, journalists, scientists, public officials, and community members are just a few people who may find this big data event of interest. Consider attending if you have:

  • Journalistic, creative or innovative ideas
  • Business or marketing savvy
  • Data sense or math/statistics concepts
  • Public health domain knowledge
  • Computational Linguistics or Digital Humanities skills
  • Mapping or programming skills

No need to have all the skills, since teamwork is one of the hallmarks of a hackathon. Plus organizers will help you to find team members during the first day. (There’s also a role if you just want to be a volunteer.) Teams will also have access to lots of free and open San Diego datasets! The event is free, and food and beverages will be provided. Teams will have an opportunity to win awards, and cash prizes, for the best overall project.

The hackathon has been organized by:

Food and beverages will be provided as courtesy

Judges are four professors at San Diego State University: Amy Schmitz Weiss, associate professor of journalism and media studies; Roger Whitney, professor of computer science; Atsushi Nara, assistant professor of geography; and Adam Hammond, assistant professor of English and comparative literature. Projects will be judged based on quality of the idea, innovativeness/creativeness, practicality/readiness; technical difficulty, and quality of the presentation.
For more information, or to register, click here.

Data Science Pop-Up, Domino Data Lab

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Date/Time
Date(s) - 02/22/2017
8:00 am - 8:00 pm

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Bringing together data science leaders for a day-long exploration of emerging practices and technologies.

Domino Data Lab created the Data Science Pop-up series to bring together quantitative researchers who are passionate about asking the right questions and identifying problems worth solving. Our goal is to present real stories about the cutting edge work being done today. The event is a is a day-long forum where people share ideas, develop best practices, and network with others in their field. We welcome anyone working in the field of data science to join us for this one-of-a-kind event.

One full packed day

We’re honored to host the most cutting edge industry experts, talent and companies in San Francisco and beyond. Featuring speakers from all over the globe.

 Location

Hosted at Galvanize HQ in the heart of San Francisco. Galvanize local campuses offer beautiful coworking space, data science classes and amazing event space.

Free food and drink!

Complimentary light breakfast, gourmet lunch, coffee, tea and topshelf cocktail hour

Accommodation

We have a special rate at the W in San Francisco, walking distance from Galvanize. Mention Domino Data Science Popup to receive a special rate.

WHAT PEOPLE SAY

They love it! To read what previous attendees had to say and for more information click  HERE

CONTACT INFORMATION

email: datapopup@dominodatalab.com

Domino Data Lab

548 4th Street

San Francisco, Ca 94107