Inspire Helsinki 2019 - Keynote Thorsten Reitz

INSPIRE 2030: A Successful
Open Platform
Thorsten Reitz
CEO & Co-founder, Wetransform
@tr_xsdi
Inspire Helsinki 2019
Keynote
24.10.2019
#inspirehelsinki2019

www.wetransform.to#2 INSPIRE 2030: A Successful Open Platform

www.wetransform.to
A brief intro to wetransform
#5 INSPIRE 2030: A Successful Open Platform

www.wetransform.to
Who are we and what do we do for you?
#6
- Begin of Operations 03/2015
- Located in Darmstadt at the Fraunhofer IGD
- More than 50 customers, 2.500+ Users
- Data harmonisation services (modelling, ETL)
- Open Source ETL Tool (hale studio)
- Open Platform Solutions for INSPIRE and other
data infrastructures (hale connect)
INSPIRE: Time for Action!
Simon Thorsten Eleazar Sven Florian
Akshat Johanna Kate ChristopherClaudia

www.wetransform.to
Our Values
#7
Mission: We make our customer’s data truly interoperable and
more valuable.
- We continuously grow as a team through open
communication and by sharing problems and knowledge.
- Through finding the right solution, we ensue happy and
satisfied customers.
- We build an organisation that integrates personal and
professional diversity and encourages functions to work
together.
- At wetransform, everyone knows what we do for our
customers and how they contribute to that.
- We simplify complex aspects of the work of our customers
through creative solutions.
- We connect domains through our commitment to open
standards and infrastructures.
INSPIRE 2030: A Successful Open Platform

www.wetransform.to
Why wetransform?
#8
- „Make Open Standards work“
- Improve Design and Implementation of Standards
- Effective Data infrastructures
- Next Generation of ETL tools

www.wetransform.to
What is an open platform?
… and what will make it successful?
INSPIRE 2030: A Successful Open Platform#9

www.wetransform.to
What is a Platform Model?
#10
Platforms enable Demand-driven Growth
Leverage underutilized resources
- AirBnB – Apartments
- Uber – Private Cars
- INSPIRE – Geospatial data?
Platforms provide value units of at least one type:
- AirBnB – Apartment Rental
- Amazon – Article that can be bought
- LinkedIn – Job Posts, Profiles, Group Posts
- INSPIRE – Spatial Datasets?

www.wetransform.to#11
Platforms are usually
two-sided or multi-
sided marketplaces,
such as Amazon
- Platform owner
- Sellers
- Buyers
- Partners
- One organization can
take multiple roles

www.wetransform.to
Value Generation in Platforms
#12
Platforms provide value to all actors, but there
are also…
- Positive Externalities:
- ParkNow - Lower environmental
disturbance due to less park space search
- Negative Externalities:
- AirBnB – Noise and disturbance for
neighbors, value of property goes down
- Uber – Taxi drivers lose income
Source: https://www.theguardian.com

www.wetransform.to
Balancing value capture in Platforms
#13
Platform value capture needs to
be balanced well
- Example Uber: Most risks and
costs lie with drivers, some
with passengers, basically none
with the platform operator
Source: https://www.telegraph.co.uk

www.wetransform.to
Characteristics of Platform Markets
#14
- Network effects
- Winner takes all tendencies
- Dynamics between roles
- Same-Side effects
- Cross-side effects
Indicators for disruption of a market by
platforms:
- Information Intensive
- Unscalable Gatekeepers
- Highly Fragmented
- Information Asymmetries

www.wetransform.to
Government (Spatial) Data Platforms
#15
Partial disruption due to regulatory
capture
- Open Street Map
- Private Data acquisition companies
Existing Platforms are still fragmented,
with little consolidation so far
- Every Data Provider has their own
Platform?
- How many users are there actually to
that platform?
Platform
Data Provider
Data User

www.wetransform.to
Closed versus open platforms
̶ Operator Monopoly
̶ Dependency to platform
̶ Low data ownership/control
̶ Compliance risks
̶ Unbalanced value capture
Fully Centralized Fully Distributed
̶ Ineffective operations
̶ Ineffective usage (interop/performance issues)
̶ Low tool re-use
̶ Low process re-use
̶ Low value capture overall
+ Highly effective operations
+ Highly effective usage
+ Maximum tool & process re-use
+ Maximum data ownership/control
+ Operator independency
+ Control over compliance

www.wetransform.to
New Architectures for open platforms
solid
social
linked
data
Source: https://ruben.verborgh.org/blog/2017/12/20/paradigm-shifts-for-the-decentralized-web/

www.wetransform.to
Platforms vs. Data Ecosystems
#18
Platform (Open) Data Ecosystem
Static Dynamic
Centralized, Homogeneous Distributed, Heterogeneous
Closed Open
Technology Focus Governance Focus
Elite usage (expert data
scientists)
Democratisation (Share, Self-
Service)
Based on: https://tdwi.org/articles/2017/04/11/4-recommendations-for-a-modern-data-ecosystem.aspx
Source: https://theodi.org/article/creating-ecosystem-maps-for-open-data/

www.wetransform.to
INSPIRE – An Open, Distributed Platform Model
#19
A set of open standards creates a
distributed, open platform
- Reasonable use conditions
- Use-specific license costs
- Non-Discriminatory access
- No controls over participation
- No insurmountable technical hurdles
INSPIRE
Data
Provider
Data
User
Service
User
Data
User
Service
User
Data
Provider
Data
Provider
Data
Provider

www.wetransform.to
Maturity of SDIs as Data Platforms
SDI Dimension accessible usable useful
Specification
• International: INSPIRE
• National: GDI-DE
• Regional: GDIS
• International: INSPIRE
• National: GDI-DE
• Regional: GDIS
• Defined use cases/stakeholders
• Optimized content/delivery
• Prioritisation
Implementation
• Metadata
• View & Download Services
• Realtime APIs (STA)
• Interoperable Data sets
• Validated Data sets
• Extensions
• Object-centric UX (Linked Maps)
• Analytic APIs
• AI/BI Data Optimization
Maturity
Annex I + II
National Level
Annex III
National Level
Annex I, II, III
State Level
Annex I, II, III
Municipal Level

www.wetransform.to
Usable, Standardised Data → Standardised Processes
#21
Today (Fragmented): In the future (Platform on Platform):
+ Effective Tool Development
+ Faster distribution of process enhancements
+ Lower Costs

www.wetransform.to
INSPIRE Value Generation: An Example
#22
Value Units
App Sale
Externality
+ Cleaner Beaches
Subscription Integrations
Platform Operator
Data License
Feedback
Data Provider
Easy Planning
Feedback
Vacationer
Vacationers
Control
Holiday Area
- Concentration
+ Improved
Infrastructure

www.wetransform.to
What Challenges
is INSPIRE facing?

www.wetransform.to
Increasing Connectedness - Challenges
#24
Complexity
Volume
Use Cases

www.wetransform.to
Increased Connectedness with Open Standards
#25
(Open)
Standard
High Risk
Expensive
Slow
Mismatches
Over- and
Underspecification

www.wetransform.to
Solving the challenges
#26
(Open)
Standard
Low Risks
Cost effective
Fast & Agile
Interactive and
iterative development,
re-useable solutions
Data-driven design for
better standards

www.wetransform.to
Transparent and effective Maintenance
…to keep INSPIRE specs up to date and relevant.
Observations:
- Bugfixes in specifications often take a very long
time to get resolved
- Unclear overall prioritisation
- Adoption of new standards and technology is slow
Potential Solutions:
→ Roadmap of development
→ Versioning of schemas and other specs
→ Move to GitHub as done for 2017.2 work

www.wetransform.to
Make Compliance easier…
#28
…while enhancing usability and usefulness
Observations:
- Compliance is a moving target
- There is no single, fully integrated, formal
testing suite to indicate compliance
- Flexibility/Variability vs. Compliance &
Interoperability
→ Central, stable compliance criteria
→ Versioning of compliance rules
→ True data-driven compliance testing
→ Fitness for Purpose improvements

www.wetransform.to
Better Harmonisation
…to lower the entrance hurdle for data providers.
Observations:
- Many organisations still don‘t harmonise their
data (perceived difficulty, limited direct
usefulness)
- Gaps in specifications decrease (semantic)
interoperability
→ More & Better Code Lists/Taxonomies
→ More Sharing & Re-Use of harmonisation projects
→ Increased adoption of regional/national standards
→ Higher automation and data-driven optimization
Minerva Intelligence ACE
wetransform hale connect

www.wetransform.to
Re-Use and Automation

www.wetransform.to
Full Harmonisation: Alexa, Transform!
„New component found"
„Analysing data source in new component"
"Applying Autotransform to integrate data source"

www.wetransform.to
Ensure robust, effective infrastructure
#32
Data and Usage Volume
ImplementationandOperatingCosts
SaaS
Open Source
Extension PS
Custom
Extension FS
In some scenarios more than 75% difference!

www.wetransform.to
Enable European SMEs/Start-Ups to contribute fully
#33
…to bring innovation to INSPIRE
Observations:
- Procurement costs and duration
- Selection criteria
- De-Facto Monopolies
- Ordering Services instead
of Solutions
→ Innovation procedure types
→ Partnerships with Start-Ups
→ Up-Front contracts
→ Long-term partnerships instead
of transactional business

www.wetransform.to
Enable Solutions
…to build an ecosystem of INSPIRE-based apps
and professional tools
Observations:
- Mismatch Data <> GIS
- Mismatch current data users <> future data
users
→ Provide Libraries to create news types of
visualisations from INSPIRE data
→ Fully leverage Linked Data
and Object Oriented Data
→ Provide Adaptive Data Services
and other APIs to make data accessible

www.wetransform.to
INSPIRE in 2030: The Architecture
Default Encoding
Additional & Alternative Encodings
Network Services, specific APIs
Solutions
Core Data Specifications Extensions Related Models Optimized Data
Clients (Web, Mobile, Pro)

www.wetransform.to
Leveraging other Standards
XPlan
XBau
SOSI
NEN3610
eCH
0118
3A/NAS
ISYBAU
CityGML
Green
Building
IFC
GeoSci
ML IFCTN-ITS
AIXM
…
SoilML

www.wetransform.to
What will INSPIRE 2030
enable us to do?
INSPIRE 2030: A Successful Open Platform#37

From INSPIRE implementation…
1.000
Private
Companies
9.000
Mapping
Authorities
2.600
Environment
Agencies
…to a central Platform for Reporting.
Air
Quality
Reporting
Natura
2000
Water
Framework
Directive
FHH-
Directi
ve
CDDA
UVP
Directi
ve
Noise
Energy
Efficien-
cy
IED

www.wetransform.to
XÖV
Standards
Data: The Fifth Freedom
DE: Online-
zugangs-
gesetz
2003 Public
Sector
Information
Directive
2019 Open Data
Directive
“All public sector content that can be accessed under
national access to documents rules is in principle freely
available for re-use. Public sector bodies are not be able to
charge more than the marginal cost for the reuse of their
data, […] . This will allow more SMEs and startups to enter
new markets in providing data-based products and
services. A particular focus is placed on high-value
datasets such as statistics or geospatial data. ”

www.wetransform.to
Major societal/global challenges

www.wetransform.to
Inform Public Debate with trusted facts

www.wetransform.to
Example 1: Finnish Geospatial Platform
#42
Direct and indirect benefits have been
estimated to be ~550 Million in 2025
- Central, automated quality assurance
for the regional authorities (“quality
guard”) regional land use plans fit in
with national schema etc
- For building information, land use
- Required fields for INSPIRE checked
- Makes it easier to find data
- Highest Benefit related to spatial
planning data

www.wetransform.to
Example 2: Spatial Planning in the Netherlands
#43
Spatial Planning Procedures based on
Open Data with INSPIRE Extensions
- Core business processes are migrated
to INSPIRE services with model
extensions
- All data is published in a unified
manner

www.wetransform.to
Example 3: Future Forests
#44 INSPIRE: Time for Action!
Using more than 10 INSPIRE Themes as
well as AI analytics to match forest types
to locations under changing conditions
- Usage of 30+ INSPIRE data sets
- Applicable to a wide range of forest
owners

www.wetransform.to
Example 4: Geohazards
#45
Usage of the INSPIRE Geology Theme to
identify geohazards and mitigation
strategies
- Unified vocabulary and data structures
- Unified analysis method
- Value added service for data providers

Accept and
Drive Change!

Inspire Helsinki 2019 - Keynote Thorsten Reitz

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Inspire Helsinki 2019 - Keynote Thorsten Reitz