web observatories and e-research
DESCRIPTION
Web Observatories, e-Research and the Importance of Collaboration. WST 2014 Webinar series, 20th March 2014 See Web Science Trust http://webscience.org/TRANSCRIPT
Web Observatories, e-Researchand the Importance of Collaboration David De Roure
e-Research Centre, University of OxfordESRC Strategic Adviser for Data Resources@dder
Overview
1. Big Data for research (UK perspective)
2. Social Media Data is distinctive
3. Several shifts in how scholarship is conducted
4. And hence the context for Web Observatories
Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552
Innovative Technology Transforming Research
Big Data doesn’t respect disciplinary boundaries
Digital Social Research
theODI.org
Mandy Chessell
The Big Picture
More people
More
mach
ines
Big DataBig Compute
Conventional Computation
“Big Social”Social Networks
e-infrastructure
onlineR&D
Big Data Production& Analytics
deeplyaboutsociety
The f
utu
re
RCUK and Big Data▶ ‘Big data is a term for a collection of
datasets so large and complex that it is beyond the ability of typical database software tools to capture, store, manage, and analyse them. ‘Big’ is not defined as being larger than a certain number of ‘bytes’ because as technology advances over time, the size of datasets that qualify as big data will also increase’ (RCUK)
Research benefits of new data▶Undertaking research on pressing policy-related
issues without the need for new data collection
• Food consumption, social background and obesity
• Energy consumption, housing type and climatic conditions
• Rural location, private/public transport alternatives and incomes
• School attainment, higher education participation, subject choices, student debt and later incomes
▶New data such as social media enable us to ask big questions, about big populations, and in real time – this is transformative
Big Data Network
Phase 1 and 2
Research questions– Social and political
movements
– Political participation and trust
– Individual, group/community and national identities
– Personal, local, national and global security (including crime, law enforcement and defence)
– Rural development and ‘Urban Transformations’
– Crisis prevention, preparedness, response, management and recovery
– Education
– Health and wellbeing (including ageing)
– Environment and sustainability
– Economic growth and financial markets (including employment and the labour market)
http://www.theguardian.com/uk/series/reading-the-riots
E-i
nfr
ast
ruct
ure
Leaders
hip
C
ounci
l
Neil
Chue H
ong
Mandy Chessell
F i r s t
Interdisciplinary and “in the wild” *
* “in it” versus “on it”
Nigel Shadbolt et al
Real life is and must be full of all kinds of social constraint – the very processes from which society arises. Computers can help if we use them to create abstract social machines on the Web: processes in which the people do the creative work and the machine does the administration... The stage is set for an evolutionary growth of new social engines. The ability to create new forms of social process would be given to the world at large, and development would be rapid.
Berners-Lee, Weaving the Web, 1999 (pp. 172–175)
The Order of Social Machines
SOCIAM: The Theory and Practice of Social Machines is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EPJ017728/1 and comprises the Universities of Southampton, Oxford and Edinburgh. See sociam.org
A revolutionary idea…Open Science!
rstl.royalsocietypublishing.org
Join the W3C Community Group www.w3.org/community/rosc
Jun Zhao
www.researchobject.org
Web as
lensWeb as artefact
Web as
infrastructure
Web Observatorieshttp://www.w3.org/community/webobservatory/
Big data elephant versus sense-making network?
The challenge is to foster the co-constituted socio-technical system on the right i.e. a computationally-enabled sense-making network of expertise, data, models, visualisations and narratives
Iain Buchan
Pip WillcoxPip Willcox
From data to signal to understanding
Pip Willcox
@marstonbikepath
Datasets or dataflows?
The Observatory Context▶New forms of data enable us answer old
questions in new ways and to address entirely new questions– Especially about (new) social processes
▶There are multiple shifts occurring:– Academia and business– Volumes and velocity of data– Realtime analytics– Computational infrastructure– Dataflows vs datasets (and curation
infrastructure)– Correlation vs causation– Increasing automation and ethical implications– Machine-to-Machine in Internet of Things
Towards a socio-technicalsystem of observatories
Tech
nic
al an
d b
usi
ness
in
terf
ace
KnowledgeInfrastructure
KnowledgeObjects
Descriptivelayer
Observatories
WOW2014 Web Observatory Workshop at WWW2014
Keynote Professor Dame Wendy Hall The Web Observatory: A Web Science PerspectiveHuanbo Luan and Tat-Seng Chua, The Design of a Live Social Observatory SystemMatthew Weber, Observing the Web by Understanding the Past: Archival Internet ResearchMizuki Oka, Yasuhiro Hashimoto and Takashi Ikegami, Fluctuation and Burst Response in Social MediaGareth Beeston, Manuel Leon, Caroline Halcrow, Xianni Xiao, Lu Liu, Jinchuan Wang, Jinho Jay Kim and Kunwoo Park,Humour Reactions in Crisis: A Proximal analysis of Chinese posts on Sina Weibo in Reaction to the Salt Panic of March 2011Robert Simpson, Kevin Page and David De Roure, Zooniverse: Observing the World’s Largest Citizen Science PlatformPaul Booth,Visualising Data in Web Observatories: A Proposal for Visual Analytics Development & EvaluationMarie Joan Kristine Gloria, John S. Erickson, Joanne S. Luciano, Deborah McGuinness and Dominic Difranzo, Legal and Ethical Considerations: Step 1b in Building a Health Web ObservatoryIan Brown, Wendy Hall and Lisa Harris, Towards a Taxonomy for Web ObservatoriesPosters:Reuben Binns, Observation without Surveillance: Web Observatories and PrivacyBesnik Fetahu, Stefan Dietze, and Wolfgang Nejdl, What's all the Data about? - Creating Structured Profiles of Linked Data on the WebCaroline Halcrow, Jinchuan Wang, Xianni Xiao, Lu Liu, Scaling and geo-locating commonly used humour tags in WeiboShuangjie Li, Zhigang Wang and Juanzi Li, Observation on Heterogeneous Online Wikis of Different LanguagesPanel: Web Observatory interoperability and standards moderator David De RourePanellists: Wendy Hall (Web Science Trust), Jim Hendler (RPI), Thanassis Tiropanis (University of Southampton)
wow.oerc.ox.ac.uk
www.oerc.ox.ac.uk/people/dder
@dder
Slide and image credits: Fiona Armstrong, Christine Borgman, Iain Buchan, Mandy Chessell, Neil Chue Hong, Nigel Shadbolt, Pip Willcox, Jun Zhao, The Guardian, Royal Society
http://www.w3.org/community/webobservatory/
www.oerc.ox.ac.uk
[email protected]@dder