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Exploring Data Complexity: Insights and Strategies from Various Sectors

Discover the intricacies of data-intensive research across different disciplines. Hear from experts in social science, biology, informatics, and more. Engage in sessions on analyzing time series data, linked data, and programming paradigms. Connect with peers and explore innovative approaches to handling large volumes of diverse data sets.

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Exploring Data Complexity: Insights and Strategies from Various Sectors

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  1. Welcome to Day 3in theBig Data House

  2. Today’s theme • It's not just the scale and volume of data that characterises data-intensive research, but also the complexity within and across datasets • May be in one discipline or across many • Some of today’s talks come from Social Science...

  3. PolicyGrid m NCRM phase 2 Current Nodes Rural communities DAMES DE Hubs Social Inclusion NeISS Highwire Genesis CQeSS Original Nodes m MoSeS Obesity e-Lab HUB m Horizon DReSS Creative Industries DE DTCs Finance mmm Healthcare MiMeG Media Genesis OeSS m eStat GeoVUE m m Entertainment LifeGuide ncrm Web Science

  4. 09:00 Mario Caccamo, BBSRC TGAC Centre Big Data Bioinformatics • 09:30 Jason Swedlow, University of Dundee, Wellcome Trust Centre for Gene Regulation and Expression The Open Microscopy Environment: Informatics and Quantitative Analysis for Biological Microscopy, HCAs, and Image Data Repositories • 10:00 Paul Lambert, Stirling University Handling social science data: Challenges and responses • 10:30 Coffee break

  5. 11:00 Chris Williams, School of Informatics, University of Edinburgh The complexity dimension in data analysis • 11:30 Mark Birkin, School of Geography, University of Leeds Spatial microsimulation for city modelling, social forecasting and urban policy analysis • 12:00 Hugh Glaser, Seme4 Ltd Linked Data: Making things more accessible • 12:30 Jim Austin, Department of Computing Science, University of York Using search for engineering diagnostics and prognostics

  6. Afternoon Schedule • 2.15 plenary to identify breakouts • 2.30 breakouts (coffee available throughout) • 4pm poster session (take coffee up to Atrium) • 4.30 report back from breakouts

  7. 1. Arts, Humanities and Qualitative Data Intensive Research • The talks have been quite focused on quantitative research, but what about Data Intensive Research using other forms of data - e.g. text, audio, video, transcriptions of in-depth interviews? • Is there a "computational turn" set to change research practice and methods in these disciplines? • Possible leader: Sheila Anderson

  8. 2. New forms of Social Sciences Data • There is a growing movement that argues that social science research could better be based on the growing body of "social transactional" and "naturally occurring" data sources; e.g. supermarket loyalty cards, administrative records, traffic cameras, facebook, smart electricity meters - including realtime data. • Which data intensive research methods need to be used or developed to successfully harnessing this data deluge for social research that has impact? • Possible lead: Mark Birkin

  9. 3. What were you thinking when Hugh was talking? • a.k.a. “Look Hugh’s Talking” • When Hugh Glaser presented Linked Data, were you thinking "this is interesting, it solves a problem for me" (if so what?) or were you thinking "this isn't going to work for me?" (if so why not?) • Possible lead: Hugh Glaser 

  10. 4. What to tell your government • You are about to meet someone in the ministry that funds research and higher education and you have the opportunity to tell them in a few succinct phrases how they should support data-intensive research in the next funding round. • You can have at most 5 priority items if you want to be taken seriously; what are they? • Possible lead: Carole Goble (need rapporteur)

  11. 5. Biological and Image Data • Following on today's talks and integrating with the wide variety of biomedical challenges and strategies. • Possible lead: Jano van Hemert

  12. 6. Analysing time series data • Several of today's talks have discussed the analysis of time series data...

  13. 7. Programming Paradigms • The aim of this session will be to take a mid-workshop stock of how the exchanges, discussions and proceedings so far, have influenced our perception of Programming Paradigms for data-intensive research. • Many of the issues laid out in Geoffrey Fox's opening talk will be revisited. • Possible leader: Shantenu Jha

  14. Spare breakouts from yesterday • Look: a wheel! • David and Goliath • Your blessing, my curse • Who's chasing who? • See... http://wiki.esi.ac.uk/Wednesday_DIR_Breakouts

  15. Breakout Rooms • Arts, Humanities and Qualitative Data Intensive Research – Swanson Rm • New forms of Social Sciences Data – CramondRm • Linked Data (Look Hugh’s Talking) – Circulation area outside CramondRm • What to tell your government - Atrium • Biological and Image Data – Newhaven Lecture Rm • Analysing time series data • Programming paradigms – Chapterhouse

  16. Afternoon Schedule Revisited • 2.15 plenary to identify breakouts • 2.30 breakouts (coffee available throughout) • 4pm poster session (take coffee up to Atrium) • 4.30 report back from breakouts Organise your own meals, then... • 9pm The Malt Shovel • 11-15 Cockburn Street, EH1 1BP

  17. The Malt Shovel 11-15 Cockburn St EH1 1BP Carlton Radisson Meeting for drinks at theMalt Shovel from 9pm

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