1. THE CROWD AND THE CLOUD
THE NEXT EVOLUTIONARY STEP OF GEO-INFORMATION PROCESSING?
Frank O. Ostermann
GIP Research Meeting, 24.04.2014

2.  Introduction
 The Crowd
 The Cloud
 Past Research
 Future Research
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THE CROWD AND THE CLOUD
THE NEXT EVOLUTIONARY STEP OF GEO-INFORMATION PROCESSING?

3.  Mobile (Social) Internet
 Cloud Computing
 Internet of Things
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THREE DISRUPTIVE INNOVATIONS
INTRODUCTION

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… AND CORRESPONDING BUZZWORDS (& BUZZ-VIS)
INTRODUCTION

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BEYOND THE BUZZ
INTRODUCTION

6.  Real-time data input
through ubiquitous sensors
 Citizens as sensors
 Multi-layered, inter-
operable data sets
 Linked and open data
 Initiatives like GEOSS, Eye
on Earth, …
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THE BIG PICTURE: DIGITAL EARTH
INTRODUCTION

7.  Introduction
 The Crowd
 The Cloud
 Past Research
 Future Research
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THE CROWD AND THE CLOUD
THE NEXT EVOLUTIONARY STEP OF GEO-INFORMATION PROCESSING?

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WHO IS THE CROWD?
THE CROWD

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WHAT DOES THE CROWD WANT?
THE CROWD

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WHAT DOES THE CROWD DO? (GEOSPATIALLY, THAT IS)
THE CROWD

11.  Introduction
 The Crowd
 The Cloud
 Past Research
 Future Research
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THE CROWD AND THE CLOUD
THE NEXT EVOLUTIONARY STEP OF GEO-INFORMATION PROCESSING?

12.  Definition has changed often
 NIST uses 5 characteristics, 4 deployment models and 3 service models
 Key Characteristics
 On-demand self-service
 Broad network access
 Resource pooling
 Rapid elasticity
 Measured service
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WHAT IS THE CLOUD?
THE CLOUD

13.  Deployment models
 Public
 Private
 Community
 Hybrid
 Service models
 Infrastructure as a Service
 Platform as a Service
 Software as a Service
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WHAT KIND OF CLOUDS ARE THERE?
THE CLOUD

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WHAT ABOUT GEOCLOUDS?
THE CLOUD

15.  Introduction
 The Crowd
 The Cloud
 Past Research
 Future Research
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THE CROWD AND THE CLOUD
THE NEXT EVOLUTIONARY STEP OF GEO-INFORMATION PROCESSING?

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AUTOMATIC IMAGE GEO-TAG CREATION
PAST RESEARCH
Ostermann, F. O., Tomko, M., & Purves, R. (2013). User Evaluation of Automatically Generated
Keywords and Toponyms for Geo-Referenced Images. Journal of the American Society for
Information Science and Technology, 64(3), 480–499.

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GEO-SOCIAL MEDIA AND CRISIS MANAGEMENT
PAST RESEARCH
Social media offers… Crisis management needs…
rich up-to-date information up-to-date information
new paths of communication redundant paths of communication
noise, uncertain lineage and accuracy high-quality and reliable information
Crowd-sourced data curation faces limits of
 Sustainability
 Scalability

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GEO-SOCIAL MEDIA AND CRISIS MANAGEMENT
PAST RESEARCH
Source
Credibility Relevance
Context
Content
Location

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GEO-SOCIAL MEDIA AND CRISIS MANAGEMENT
PAST RESEARCH

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GEOCONAVI
PAST RESEARCH
1.1 Retrieval
Scheduled Java code
accessing APIs
2.1 Topicality
Scheduled PLSQL job
2.2 Geo-Coding
a) Scheduled PLSQL job
b) Scheduled Java code
2.3 Geographic context
Scheduled PLSQL job
3.1 Spatio-temporal
clustering
Scheduled Python script
calling SatScan job
2.4 Quality Assessment
Scheduled PLSQL job
1.2 Storage
Scheduled Java code
writing to DBMS
Oracle DBMS
3.2 Quality Re-Assessment
Scheduled PLSQL job
Twitter
Stream-
ing API
Flickr
Search
API
Dissemination
SMS, WFS, WMS, RSS, SES
EFFIS
Hotspot
Data
European Media Monitor
Geo-coding API

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FOREST FIRES IN FRANCE 2011
PAST RESEARCH

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FOREST FIRES IN FRANCE BY GEOCONAVI
PAST RESEARCH

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FRENCH FOREST FIRE SOCIAL MEDIA
PAST RESEARCH

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LOW-COST IN-SITU AND MOBILE SENSORS
PAST RESEARCH
Publiclaboratory.com
Mikrokopter.de
Libelium
Waspmote

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LOW-COST IN-SITU AND MOBILE SENSORS
PAST RESEARCH

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SOME PUBLICATIONS
PAST RESEARCH
 Craglia, M., Ostermann, F., & Spinsanti, L. (2012). Digital Earth from vision to practice: making
sense of citizen-generated content. International Journal of Digital Earth, 5(5), 398–416.
 Ostermann, F., & Spinsanti, L. (2012). Context Analysis of Volunteered Geographic Information
from Social Media Networks to Support Disaster Management: A Case Study On Forest Fires.
International Journal of Information Systems for Crisis Response and Management, 4(4), 16–37.
 Spinsanti, L., & Ostermann, F. (2013). Automated geographic context analysis for volunteered
information. Applied Geography, 43(9), 36–44.

27.  Introduction
 The Crowd
 The Cloud
 Past Research
 Future Research
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THE CROWD AND THE CLOUD
THE NEXT EVOLUTIONARY STEP OF GEO-INFORMATION PROCESSING?

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MY RESEARCH TRIANGLE
FUTURE RESEARCH
Methodology
ApplicationTheory

29. 1) Societal implications of new production and consumption
modes of geographic information.
2) Methods to assess and improve crowd-sourced and volunteered
geographic information quality.
3) Methods to increase interoperability through geographic data
integration and linking.
4) Applications to empower citizens, increase participation, and
improve quality of life.
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RESEARCH THEMES
FUTURE RESEARCH

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NEW SOURCES OF GEO-INFORMATION
FUTURE RESEARCH
Geography
Explicit Implicit
Participation
Explicit
Volunteered Geographic
Information (VGI)
Open Street Map.
Volunteered geographic content
(VGC)
Wikipedia articles about non-geographic
topics containing place names,
Foursquare
Implicit
User-generated geographic
information (UGGI) or
Contributed geographic information
(CGI)
Public Tweets referring to the
properties of an identifiable place.
User-generated geograhpic content
(UGGC)
Public Tweets containing a place name

31. Issues
 Crowd-sourced vs. volunteered
 Opportunistic vs. participatory sensing
 Open data and sharing
 Liability
 Privacy
Project proposal
 Identify factors that influence success and failure of collaborative or
crowd-sourced (software) projects
 Approach: Meta-data and usage data analysis, social network analysis
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NEW MODES OF GI-PRODUCTION
FUTURE RESEARCH

32. Issues
 Data quality (reliability, relevance, accuracy)
 Rapic decision-making
 Geographic information streams
Project Proposal
 Combine suitable quality assurance mechanisms for near real-time
processing of geo-information streams
 Approach: Geographic information retrieval, distributed processing, geo-
statistics
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NEW METHODS FOR GI-PROCESSING
FUTURE RESEARCH

33. Issues
 Syntactic heterogeneity
 Semantic heterogeneity
 Place-based vs. space-based perspective
Project Proposal
 Assess and adopt place-based approaches to improve GI semantic
interoperability
 Approach: Theoretical reasoning, information science
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INTEROPERABILITY OF GI
FUTURE RESEARCH

34. Issues
 Digital divide and uneven information geographies
 Lack of technical infrastructure and expertise
 Entrenched power structures
Project Proposal
 Cloud-based spatial data infrastructures and processing for volunteered
or crowd-sourced information to increase resilience in developing
infrastructures
 Approach: Political science, sociology, information science, computer
science
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APPLICATIONS OF CROWD AND CLOUD APPROACHES
FUTURE RESEARCH

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RESEARCH NETWORKS
FUTURE RESEARCH
Thank you!