Geo know general presentation 2013

Creating Knowledge out of Interlinked Data

GeoKnow
Making the Web an Exploratory Place for Spatial Data
Collaborative Project 2012-2015
in Information and Communication Technologies

Project No. 318159
Start Date 01/12/2012

EU-FP7 LOD2 Project Overview . 02.09.2010 . Page 1

http://geoknow.eu
http://lod2.eu

Making the Web an Exploratory Place for Geospatial Data

The Spatial Data Web: Achievements and Challenges
 Web - a global, distributed platform for data, information and knowledge integration
 Exposing, sharing, and connecting pieces of data on the Semantic Web using RDF
 Large Spatial Databases (OpenStreetMaps, Google Maps etc.) integrated in many
applications
Achievements
Challenges
1. Extension of the Web
with a data commons
(currently amounting to
25 Bn. facts)
2. Vibrant, global RTD
community
3. Industrial uptake begins
(e.g. BBC, Thomson
Reuters, Eli Lilly)
4. Emerging governmental
adoption in sight
5. Establishing Linked Data
as a deployment path
for the Semantic Web.

EU-FP7 GeoKnow. 21.01.2013 . Page 2

1. Big Data: Large volumes of
frequently updated data
2. Coherence: Relatively few,
expensively maintained links
3. Quality: partly low-quality
data and inconsistencies
4. Data Consumption: largescale processing, schema
mapping and data fusion for
enterprises
5. Simplicity: easily create and
deploy spatial semantic web
applications

http://geoknow.eu


GeoKnow in a Nutshell
WP5

Metrics
Supply Chain
Management Data

WP3

Spatial Linked Data

Linked Data

WP6

Spatial Authoring / Browsing
Tools

Fusing
E-Commerce Data
Faceted Browsing

Interlinking
… further use cases …

Spatial Widgets
protected

public
Adaptive Authoring

Aggregation

Open Data /
LOD Cloud

WP4

SPARQL / GeoSPARQL

WP1

Linked
Data
Access

GeoKnow Generator

Spatial Knowledge Store & Co-Evolution
WP2

Triples Stores

RDF Views

GIS Databases


http://geoknow.eu


Work Packages
WP7:
Dissemination
community
building
Exploitation &
standards, fertili
sation

WP2: Semantics based
geospatial data
management

WP3: Spatial knowledge
aggregation, fusing & quality
assessment

WP4: Spatial-semantic
exploration, visualization, an
alysis & authoring interfaces

WP8: Project
Management

WP1: Requirements, design, prototyping, interfaces definition, component integration and
GeoKnow Generator

WP5:GeoKnow for Supply chain
management


WP6:GeoKnow for E-Commerce

http://geoknow.eu


Consortium

Institute for Applied Informatics
Germany

OpenLink Software
United Kingdom

Brox
Germany

Ontos
Switzerland

Unister
Germany

Athena Research and
Innovation Center
Greece


http://geoknow.eu


WP1: Requirements, Design, Benchmarking, Component Integration





Requirements collection and analysis
Continuous Benchmarking
GeoKnow Generator design and development
Component integration

GeoKnow Generator
 Different data sources:
private, pubic, RDF, nonRDF, static, streams.
 Performance monitoring
and Secured data in all
layers
 Data enrichment and
continuous quality
assurance
 New visualisation
paradigms


http://geoknow.eu


WP2: Semantics-Based Geospatial Information Management
Objective:
Develop the storage, query execution and optimization capabilities of the storage
engine to meet the Geospatial requirements of the project.
Tasks:
• Geospatial query optimization - The cost model for geospatial queries will merge
query optimization and execution by partially executing joins during optimization
• Geospatial clustering - adds geospatial clustering support for rearranging physical
storage according to geospatial criteria
• Distributed geospatial capabilities – Showcase advances in scale-out capabilities
with large geospatial data, e.g. all of OSM, with heavy online query load and
concurrent updates.
• Geospatial problem solving – Implementation of complex application logic coresident with the data, required for supply chain route planning.
• Exposing INSPIRE data as Linked Data - provide technical solutions and tools to
expose INSPIRE data and metadata as geospatial Linked Data.

http://geoknow.eu


WP3: Spatial Knowledge Aggregation, Fusing & Quality Assessment
Combine crowdsourced /open and closed spatial RDF data to produce data of
increased coverage, accuracy, semantic enrichment, timeliness and value
Leverage the wisdom of crowds in the geospatial Data Web
1. Spatial knowledge mapping
Motivation: How do we interlink spatial and non-spatial
RDF data?
Goal: Lift implicit geographic references in RDF data and
interlink with spatial and non-spatial data, transform
geospatial data to RDF with emphasis on
big, evolving, geospatial data
 e.g. interlink RDF data with DBpedia, Geonames
 e.g. transform typical shapefiles to RDF and interlink
with other data
 e.g. continuously process and transform
OpenStreetMap data (earth-scale, thousands
revisions/day) to RDF


http://geoknow.eu


2. Spatial knowledge fusion
Motivation: How do we combine different spatial RDF data, with
differences in RDF representation, metadata and geometries for the same
geographical features?
Goal: Develop algorithms to fuse geospatial RDF data: map different RDF
representations of geometry, merge metadata associated with spatial
objects, combine representations of relations between spatial objects
 e.g. identify same POIs from different data sets with differences in
location (e.g. coordinates), metadata (e.g. name, working hours), and
relations (e.g. within a mall, south of a square)
3. Quality-aware spatial knowledge aggregation
Motivation: Volunteers produce valuable spatial knowledge in the Web.
How can we guide them towards purposeful contributions without
restricting them, and consolidate their efforts?
Goal: Develop algorithms to semantically consolidate categories and
produce a community-driven consolidation process
 e.g. category cretan_cuisine becomes a subcategory of greek_cuisine
 e.g. OpenStreetMap users consolidate greek_cuisine with
greek_restaurant and cretan_menu

http://geoknow.eu


4. Metrics for volunteered (crowdsourced) geographic information
Motivation: Crowdsourced geoinformation can surpass the quality of official/commercial
/closed maps. How do we apply and leverage this knowledge source?
Goal: Define metrics to compare different maps from user-contributed geospatial
information modeled in RDF (coverage, precision, pertinence, timeliness)
 E.g. compare coverage of a specific category between two regions of a city

5. Quality assessment for geoinformation
Motivation: We have fused crowdsourced geoinformation with official/commercial/closed
maps. How do we measure the quality of this value added data source?
Goal: Define, extend, adapt quality metrics for spatial RDF, and develop methods to
detect/repair errors and enrichment.
 E.g. produce a map with more/accurate POIs based on OSM data

http://geoknow.eu


WP4: Spatial-semantic Browsing, Visualization, Authoring Interfaces
1. Spatial-semantic visualization and exploration
Motivation: Given spatial RDF datasets, how to quickly generate previews and easily
turn them into interactive, user friendly, visualizations and widgets (making use of
vector and raster data)?
Goal: Develop reusable user interface components for display of geographic feature
information on a map and as forms. Leverage re-use of vocabularies by means of
default and customizable presentations (e.g. for hotels, events, routes, SC network, …)
Furthermore develop library components for dealing with different RDF representations
and level of detail of geographic data. Offer keyword and facetted search.


http://geoknow.eu


2. Adaptive spatial-semantic authoring and curation
Motivation: There are many reasons for the need to edit RDF data, however without the
right tool this is often very cumbersome; Examples:
• After displaying recently geocoded data on a map errors become obvious.
• A use case requires introducing new labels to POIs that include country and ZIP code
Goal: Develop re-usable and composable widgets for supporting single
editing, batch editing as well as reconciliation of spatial RDF data.
The requirement for authoring can often stem from data quality issues. As such there
will also be UI components offering access to (some) of the functionality provided by
the quality assurance tools.
3. Spatial social networking
Motivation: Social networking is ubiquitous. Users and organisations need to be able
to register for relevant updates. This applies to both projects managed in the GeoKnow
Generator itself, as well as generated applications.
Goal: Enhance the GeoKnow Generator with subscription, filtering, and notification
mechanisms based on the Open-Social standard. Furthermore, implement adapters to
popular social networks, such as Facebook, Google+, Twitter, LinkedIn.


http://geoknow.eu


4. Public-private spatial data co-evolution
Motivation: Example: A tourism portal combines a private hotel database with public
OpenStreetMap data for becoming capable of answering queries such as “find all
hotels near beaches”. For convenience, users can fix mistakes on the portal.
However, when the hotel database or OpenStreetMap evolves (re-import or
incremental updates), how can the prior fixes be retained?
Goal: Identify types of enterprise RDF data synchronization workflows, define and
implement tools that support them. This will include ETL processes, query
federation, transformation/patching of data and change set propagation.


http://geoknow.eu


WP5: Spatial Linked Data in the Supply Chain
• Logistics companies face big-data challenges when dealing with
complex international tiered structures
• Information integration is critical for effective enterprise processes
• Geospatial linked data may help to derive a unified collaborative
spatial view on important parts of a logistic process
• Linked data applications make different private supply chain data
points available and connect these layers with intelligent and
secure APIs
• Close to real time observation of information flows (e.g.
materials, products, other supply chain assets)
• May improve supply chain performance
• Quick integration of additional supply chain partners and
information layers


http://geoknow.eu


WP6: GeoKnow for E-Commerce
Same Challenges of E-Commerce Applications and Semantic Web Community
• independent, different data providers
• integration of entities without unique identifiers
• data sets are growing rapidly
• match user demand with technology push
 Validation of GeoKnow results within e-Commerce scenario: this use case is the
perfect match for evaluation and research on semantic web challenges
Objectives: Answer central questions:
• What kind of new products is my customer likely willing to buy?
• Which geographical regions are most suitable for a special event?
• How to integrate internal data with the open linked data by interlinking with
geographical data, social network structures from many different sources?
• How to provide the information to a user via search applications?


http://geoknow.eu


WP7: Dissemination, Community Building, Exploitation & Standards
Dissemination
• www.geoknow.eu
• Flyer and stickers
• Social Networks
• Community Groups
• Conference presenting
• Web-based showcases
Exploitation
• Open source
• GeoKnow generator exploitation in further use cases
Standardization
• W3C SPARQL Working Group
• W3C Relational Data Bases to RDF Working Group
• W3C Semantic Web Deployment Working Group

http://geoknow.eu


WP8: Project Management
Project
 Instrument:

Collaborative Project (STREP)

 Objective:

Intelligent Information Management

 Call:

FP7-ICT-2011.4.4

 Duration:

12/2012 – 12/2015

Means
 Total Budget:

4,1 M€

 Total Funding:

2,95 M€

 Total Resources:

495 PM

 Partners:

6


http://geoknow.eu


Contact
Address

Coordinator

Institute for Applied Informatics
University of Leipzig
Neumarkt 20
04109 Leipzig
Germany

Dr Jens Lehmann
Scientific Project Leader
Phone:+49 (341) 97-32260
Fax: +49 (341) 97-32329
Email: lehmann@informatik.uni-leipzig.de
Web: http://jens-lehmann.org

Phone: +49 341 3928738 0
Fax: +49 341 3928738 9

Sandra Prätor
Project Manager
Phone:+49 (341) 97-32332
Fax: +49 (341) 97-32329
Email: praetor@informatik.uni-leipzig.de
http://aksw.org/SandraPraetor.html

Thanks for your attention!
LOD2 Title . 02.09.2010 . Page 18

http://geoknow.eu
http://lod2.eu

Geo know general presentation 2013

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