Introductory slides into Big Data in Geographic Information Science

S OME T HOUGHTS ON B IG D ATA IN GIS CIENCE ...

B IG D ATA GIS CIENCE ?

B IG D ATA GIS CIENCE ? K RZYSZTOF J ANOWICZ , UCSB (F EB . 03 2012)


I S B IG D ATA M ORE T HAN J UST A NOTHER B UZZWORD ?



D O T HESE B UZZWORDS SHARE A C OMMON C ORE ?

Digital Earth as a multi-thematic and multi-perspective
knowledge archive
e-Science as an infrastructure to share data and models
and to enable collaboration
Smart Dust as self-organizing, ubiquitous sensor networks
Linked Data as a global graph connecting raw data to make
them accessible and re-usable

Is Big Data a paradigm shift towards data-intensive,
collaborative science in which models and data are shared?



T HE T HREE V’ S OF B IG D ATA
Volume: The size of the involved data, their multi-dimensional
nature, as well as their inter-linkage which creates a global graph.
E.g., Volunteered Geographic Information, Location-based Social
Networks, sensor networks, high resolution remote sensing data,
complex transportation simulations. V
Variety: The number of sources and type of data is increasing as
well. Combining social media with authoritative sources and
integrating different formats such as video, audio, photo, and text
allows a more holistic analysis but raises new issues in data
integration. V
Velocity: Big Data is not only about large amounts of data but also
the speed at which data is created and updated. A rapidly
increasing number of data sources deliver near real-time data
which poses new challenges for stream reasoning and rule
systems, which data do we keep? V


K NOWLEDGE AS A N ETWORK ...

... The global Linked Data graph may be a promising knowledge
infrastructure for Big Data.



NSF E ARTH C UBE

’NSF seeks [...] approaches to create integrated data management
infrastructures across the Geosciences. [...] recognize the multifaceted
challenges of modern, data-intensive science and education and envision
an environment where low adoption thresholds and new capabilities act
together to greatly increase the productivity and capability of researchers and
educators [...].’ (http://www.nsf.gov/geo/earthcube/)



IARPA F INDER C HALLENGE

Estimate the location of pictures and videos without any explicit
geolocation information.



IM2GPS

’Estimating geographic information from a single image’
’Purely data-driven scene matching’ (low-level features)
Big Data Check
Volume: 6 million (out of 6 billion) of Flickr photos V
Velocity: in theory, new pictures every second V
Variety: single type of data V



D IA L OC : N EW D ATA S OURCES F OR O LD Q UESTIONS

’market food street narrow dense populated asia economy air conditioning
smog fog humid warm building construction skyscrapers skyline shipping
export channel harbor transportation tram city advertisement’
Variety: Plain text, not image features as data source V


D IA L OC : N EW D ATA S OURCES F OR O LD Q UESTIONS
0.5
Cape Norman
Santa Barbara

0.4

0.3

0.2

0.1

0

City

Lake

Valley

Mountain

HistoricPlace

Town

WorldHeritageSite

ProtectedArea

Village

Cave

Island

Museum

Stream

Park

Theatre

Lighthouse

Stadium

Hotel

Restaurant

Airport

Hospital
Volume: > 500,000 Wikipedia articles & travel blog entries. V
Velocity: in theory, new travel blog entries every minute V
IM2GPS and DiaLoc each exclude 99.9% of the land-surface of
the Earth, what if we combine them.


F UTUR ICT – A B IG S CIENCE P ROJECT

EU ﬂagship proposal
> 300 teams
10 years
1 billion Euro
Knowledge accelerator



F UTUR ICT – I NVOLVED S CIENTIFIC D OMAINS

G EOGRAPHY ?


G EOGRAPHY IS ABOUT I NTERDISCIPLINARITY !



S O M AYBE T HEY A RE JUST A DDRESSING O THER P ROBLEMS ?



S O M AYBE T HEY A RE JUST A DDRESSING O THER P ROBLEMS ?

... which role do we play?


T HE PANELISTS
Mark Gahegan, University of Auckland, New Zealand
Professor at the School of Environment

Mark Schildhauer, University of California, Santa Barbara, USA
Director of Computing at National Center for Ecological Analysis and Synthesis

Isabel Cruz, University of Illinois, USA
Professor of Computer Science

Werner Kuhn, University of Muenster, Germany
Professor for Geographic Information Science

Pascal Hitzler, Wright State University, USA
Assistant Professor of Computer Science

Mike Goodchild, University of California, Santa Barbara, USA
Jack and Laura Dangermond Professor of Geography

Big Data is a big topic, this panel will focus on the variety component.

Introductory slides into Big Data in Geographic Information Science

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Introductory slides into Big Data in Geographic Information Science