The document discusses open geo-spatial data and spatial data infrastructures. It provides an overview of key concepts including open data, geographic information systems (GIS), spatial data formats and standards, and spatial data infrastructure initiatives like INSPIRE which aim to make spatial data interoperable across Europe. The document also discusses global open data efforts like the Group on Earth Observations (GEO) and GEOSS, as well as principles for open data and how data can be made more open and accessible.

1. Open geo-spatial data
Lorenzino Vaccari
lorenzino.vaccari@jrc.ec.europa.eu
28th November 2014
www.jrc.ec.europa.eu
Serving society
Stimulating innovation
Supporting legislation

2. Summary
Open Data
Geo Data
GIS
SDI
Geo (Open) Data

3. http://www.webmapp.it/maps/http://www.webmapp.it/maps/ddoolloommiittii//mmaapp..hhttmmll

4. HHOOTT:: HHuummaanniittaarriiaann OOppeennSSttrreeeettMMaapp TTeeaamm
http://http://hhoott..ooppeennssttrreeeettmmaapp..oorrgg

5. “OpenStreetMap is
a free map of the
world, created by
someone like you
OpenStreetMap project creates
and provides geographical data,
such as road maps, freely available
to anyone. Behind the
establishment and growth of the
project have been restrictions on
use or availability of map
information across much of the
world and the advent of
inexpensive portable satellite
navigation devices.
http://www.http://www.ooppeennssttrreeeettmmaapp..oorrgg//

6. “Is data that can be freely used, reused and
redistributed by anyone – subject only, at
most, to the requirement to attribute and
use
reuse
sharealike.
“open” = redistribution
commercial reuse
derivative works
BUT, may require:
attribution
share alike

8. “Open data can
help unlock $3
trillion to $5
trillion in
economic value
annually across
seven sectors…”
http://www.mckinsey.com/insights/business_technology/open_data_unlocking_innovation_and_performance_with_http://www.mckinsey.com/insights/business_technology/open_data_unlocking_innovation_and_performance_with_lliiqquuiidd__iinnffoorrmmaattiioonn

11. 5 Stars principles (Tim Bernes Lee)

12. 5 Stars principles (Tim Davies)
Be demand driven
Put data in context
Support
conversation
around data
Build capacity, skills
and networks
Collaborate on
data as a com-mon
resource
•Data structured, tools and support based on community needs and
demands
•Ways of listening to people’s requests for data, and responding with
open data?
• Provide metadata (e.g. frequency of updates, data formats and data
quality)?
• Include qualitative information such as data creation, or data manuals?
• Link from data catalogue pages to analysis of the data?
• Can people comment on datasets, or create structured conversation around data?
• Do you join the conversations?
• Easy ways to contact the individual ‘data owner’?
• Offline opportunities to have conversations that involve your data?
• Tools for people to work with your datasets?
• How To guidance on using open data analysis tools?
• Do you go out into the community to run skill-building sessions?
• Do you sponsor or engage with capacity building?
• Have feedback loops so people can help you improve your datasets?
• Collaborate with the community to create new data resources?
• Provide support to people to build and sustain useful tools and services?
• Work with other organisations to connect up your data sources.

13. GGeeooggrraapphhiicc DDaattaa
hhttttpp::////lliibbrrooddiiggiittaall..oouuppee..eess//
Represent either geographical
features or phenomenoms:
georeferenced &
multidimensional, at least two
coordinates must be specified
to define a location

14. Geographical coordinates
hhttttpp::////eenn..wwiikkiippeeddiiaa..oorrgg//wwiikkii//GGeeooggrraapphhiicc__ccoooorrddiinnaattee__ssyysstteemm

15. Spatial relationships
hhttttpp::////eenn..wwiikkiippeeddiiaa..oorrgg//wwiikkii//SSppaattiiaall__rreellaattiioonn

16. HHooww ttoo mmaannaaggee GGeeoo--DDaattaa:: GGIISS
HOW TO MANAGE GEOGRAHICAL DATA
GIS: a geographic
information system
(GIS) is any
manual or
computer based
system designed to
store and
manipulate
spatially
referenced data.

17. Computer based GIS
A geographic information system (GIS)
integrates hardware, software, data
and services to capturing managing,
analyzing and displaying
geographically referenced information

18. Specific Interdisciplinary Knowledge
GGeeooggrarapphhyy
Computer
Science
AArcrchhitietecctuturere Computer
Science
GGIISS
MMaaththeemmaatitcicss CCivivili lE Enngginineeeerr
Measurement
Measurement
and Surveying
Statistics and Surveying Statistics
Close range
and remote
sensing
Close range
and remote
sensing

19. Voluminous, Unique analysis methods and
data integration
http://http://wwwwww..ttuuffllooww..ccoomm//

20. Data Representation
GIS Data represents real world
objects (e.g. roads, land use,
elevation, trees, waterways,
etc)
There are 2 broad methods used
to store data in GIS
– Vector data Model
– Raster Data Model

21. Vector Data Representation
A coordinate based data model that represents
geographic features as points, lines, and polygons
1. Points (location of wells,
schools, points of
interests, etc
2. Lines (road centerlines,
rivers, trails, streets,
etc
3. Polygons (parcels,
boundaries of cities,
lakes, land use, etc)

22. Raster Data Representation
A spatial data model that defines space as an array of
equally sized cells arranged in rows and columns. Each
cell contains an attribute value and location coordinates

23. Most Common Spatial Data Formats
Vector
– Shape (ESRI)
– GML (Geographic Markup Language)
– RDF (Resource Description
Format)
– KML (Keyhole Markup
Language)
Raster
– Geo TIFF (Geo Tagged Image Format)
– ASCII GRID (ESRI)
– TIN (ESRI)
– NETCDF

24. WWhhaatt iiss aa SSppaattiiaall DDaattaa IInnffrraassttrruuccttuurree ((SSDDII))??
“The SDI provides a basis for spatial data discovery,
evaluation, and application for users and providers
within all levels of government, the commercial sector,
the non-profit sector, academia and by citizens in
general”
-- The SDI Cookbook
http://www.gsdi.org
Douglas Nebert
U.S. Federal Geographic
Data Committee Secretariat

25. SDI: Network & spatial data services
architecture

26. Europe needed a SDI
Natural Disasters and as well as
other environmental phenomena
do not stop at national borders!
20% of the EU citizens
(115 million) live within
50 Km from a border
70% of all fresh water bodies
in Europe are part of a trans-boundary
river basin !!

27. Building a European SDI is complex
Europe is a patchwork of several
countries with different traditions,
cultures and socio-economic
models
This is reflected in the different
ways in which geo-spatial data
is managed

28. INSPIRE Directive
• General rules to establish an
Infrastructure for Spatial
Information in Europe for
• Community environmental policies
• Policies or activities which impact on the
environment
• INSPIRE is built on the SDIs
established and operated by the
Member States
• Spatial data held by/on behalf of public
authorities
• Does not require collection of new
data
• INSPIRE is a Framework Directive
– Detailed technical provisions in
Implementing
Rules

29. Implementing Rules vs. Technical
Guidelines

30. Cross-sector data interoperability
EL:Elevation
TN: T r a ns por t n e t wo r k s
BU:Buildings
SO:Soil
PF:Production and
industrial facilities
AF:Agricultural and
aquaculture
facilities
ER:Energy
Resources
HB:Habitats and biotopes
SD:Species distribution
AM:Area management/ restriction/
regulation zones & reporting units
PD: Population
Distribution
US: Utilities and
Governmental Services
(Waste Management)
Waste
Urban Planning
Waste Management
Plans
Environmental Impact
Assessment
Risk Management
…
PRTR
SEVESO
INSPIRE data
Data from other
sectors

31. Making data sets interoperable
• Problem: Users may not be able to
understand or correctly interpret the used
data model or symbology
• Solution: Data is made available according to
common interoperability specifications
 Common (cross- domain) data models
 Common encodings (formats)
 Common symbologies
• Reference: INSPIRE
Directive, Art. 7-10, IRs on interoperability
of spatial data sets and services & INSPIRE
data specifications
 known
 shared
 documented
 accessible
 interoperable
• Timing: Annex I since Dec 2012 (if newly collected), Dec
2017 (all other data), Annex II+III: Oct 2015/Oct 2020

32. INSPIRE thematic scope
Annex I
1. Coordinate reference
systems
2. Geographical grid
systems
3. Geographical names
4. Administrative units
5. Addresses
6. Cadastral parcels
7. Transport networks
8. Hydrography
9. Protected sites
Annex II
1. Elevation
2. Land cover
3. Ortho-imagery
4. Geology
Implementation 2012/2017
Implementation 2015/2020
Annex III
1. Statistical units
2. Buildings
3. Soil
4. Land use
5. Human health and safety
6. Utility and governmental
services
7. Environmental monitoring
facilities
8. Production and industrial
facilities
9. Agricultural and
aquaculture facilities
10.Population distribution –
demography
11. Area management/
restriction/regulation
zones & reporting units
12. Natural risk zones
13. Atmospheric conditions
14. Meteorological
geographical features
15. Oceanographic
geographical features
16. Sea regions
17. Bio-geographical regions
18. Habitats and biotopes
19. Species distribution
20. Energy Resources
21. Mineral resources

33. Key pillars of data interoperability
Conceptual data
models Registers
• objects types,
properties &
relationships
• cross-domain
harmonization
• based on a
common
modelling
framework
• managed in a
common UML
repository
Harmonised
vocabularies
• achieve better
interoperability
than free-text
and/or multi-lingual
content
• allow additional
terms from local
vocabularies
• 400 code lists &
almost 5000
values in central
register
Encoding
• conceptual
models
independent of
concrete
encodings
• standard
encoding: GML,
but also
possible to
derive other
encodings (e.g.
based on RDF)
• provide unique
and persistent
identifiers for
reference to
resources
• allow their
consistent
management
and versioning

36. • Key infrastructure component
 provide unique and persistent identifiers for resources
 allow their consistent management and versioning
 allow unambiguous references to items

37. The INSPIRE Report
http://
www.eea.europa.eu/publications/midterm-evaluation-report-on-inspire-implementation
http://
www.eea.europa.eu/publications/midterm-evaluation-report-on-inspire-implementation

38. GGeeoo ((OOppeenn)) DDaattaa ((aatt GGlloobbaall lleevveell))
21th Century Challenges
hhttttpp::////wwwwww..ssliliddeesshhaarree..nneett//aannggeelleedd//ggeeoossss

39. The Group of Earth Observation (2005)

40.  GEOSS promotes scientific
connections and interactions
between the observation systems
that constitute the system of
systems, and addresses some of
the 21st Century Challenges
 GEOSS also promotes the
introduction of innovative
scientific techniques and
technologies in the federated
observing systems.
The Global Earth Observation System of Systems
(GEOSS) provides the fundamental framework to
integrate the earth observation efforts of the 84 GEO
members and 61 Participating organizations on 9
Societal Benefit Areas

41. GEOSS Data Sharing Principles
• Full and Open Exchange
of Data, recognizing
Relevant International
Instruments and National
Policies
• Data and Products at
Minimum Time delay and
Minimum Cost
• Free of Charge or minimal
Cost for Research and
Education
http://www.geoportal.or http://www.geoportal.orgg//wweebb//gguueesstt//ggeeoo__hhoommee

42. 393 Resources
Documentation
GGeeoo ((OOppeenn)) DDaattaa ((aatt JJRRCC))
hhttttpp::////ddaattaa..jjrrcc..iitt//

43. Harvesters
JRC Geo Catalog
Other
souOrtcheesr
sOotuhrecre sJRC
sources
JRC Data Catalog (CKAN)
EU Open
Data
Catalog
JRC Geo
Providers
CNR Broker
(INSPIRE) Geo Proxy
CSW
Virtual
EndPoints
CCSSWW
Open Data Portal
Other
souOrtcheesr
soOuthrecre JsRC
GEO sources
DRSDI
CID
Repository

44. http://www.w3.org/TR/vocab-dcat/

45. http://www.w3.org/TR/vocab-dcat/

47. https://https://ooppeenn--ddaattaa..eeuurrooppaa..eeuu

49. http://http://ppuubbliliccddaattaa..eeuu//ddaattaasseett

50. **SSoouurrccee:: EEuurrooppeeaann CCoommmmiissssiioonn PPuubblliiccaattiioonn OOffffiiccee

51. Data are MINE !

52. NOT exactly…

53. THANKS!!!!
Juan Pane, Maurizio Napolitano (FBK), Michael Lutz (JRC),
Robin Smith (JRC), Andrea Perego (JRC), Anders Friis-Christensen (JRC)
Credits:
• https://okfn.org/
• https://unsplash.com/
• https://www.rd-alliance.org/
• http://pantonprinciples.org/
• http://br.freepik.com/
• http://epicgraphic.com
• http://www.prescribinganalytics.com/
• http://global.census.okfn.org/
• http://tt.spendnetwork.com/map.html
• http://www.prescribinganalytics.com/
• https://opencorporates.com/
• http://www.socrata.com/blog/economic-impact-open-data/
• http://www.wallpapermania.eu
• http://montcomediation.org/images/MCMC_MyWayYourWay.jpg
• http://www.icsu.org/
• http://img.gawkerassets.com/img/182n8vzdlg1iojpg/original.jpg
• http://netdna.webdesignerdepot.com/uploads/photo_manipulation/manipulation-9.jpg
• http://www.geoportal.org/web/guest/geo_home
• https://opensource.com/education/14/8/open-source-deep-academia?
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