This document analyzes the business models of 29 geospatial companies in the United States that utilize open data. It finds that most companies rely on publicly available ground data and focus on data aggregation. They generate revenue through premium business models that provide high-end products and services to customers. Visualization is also important for geospatial data services. The analysis uses frameworks to examine how companies source, process, and market data-driven products and aims to understand open data's potential for economic growth.

1. Uncovering the Characteristics of Business Model in Open Data
Companies and Their Relational Positions Using Webometrics Analysis
- Focusing on Geospatial Companies in United States
JiYoung Park (Doctoral Candiate)
YeungNam University, S.Korea
Han Woo Park
YeungNam University, S.Korea
Parallel Session 1 (1.3_Shaping creative economies through clusters)
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2. Introduction
• Open Data as public data, from government or other sources, that’s
available for anyone to access for personal or business use (Gurin, 2013).
* Different from Big Data - Open Data with a mission: designed to provide
free, open, transparent data that can transform the way we do business,
run government, and manage all kinds of transactions.
• Understanding the business model using Open Data variations in the
digital world is to be able to analyze them to address real world
problems that business faces (Zeleti, Ojo, & Curry, 2014).
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3. Introduction
• The Open Data policies developed by the U.S. and U.K. governments are
driven by a push for economic growth and job creation.
• This policy, which will make unprecedented amounts of federal data
available in highly usable forms, has a business agenda first and foremost
 The Chief Executive's political will is required (Robinson, Yu, Zeller &
Felten, 2009).
• The study of business models using Open Data have recently been
discussed in academic circles.
- Lindman, Rossi & Tuunainen (2013). Open data services: research agenda
- Lindman, Kinnari & Rossi (2014). Industrial open data: Case studies of early open data entrepreneurs
- Zeleti, Ojo & Curry (2014). Emerging business models for the open data industry: characterization and
analysis
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4. Open Data Industry 500 project
• The Open Data 500 study, directed by the GovLab at
New York University, be available online since early
2014.
- It give economists and other researchers a new
information base to help assess Open Data’s value.
- It include a comprehensive study of U.S companies
that use government Open Data in the health, finance,
education, energy, geospatial and other sectors.
- How they use government Open Data and how they think government
agencies can make their data more useful.
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5. Literature Review – Geospatial
• Geospatial Data (Korea Resources Corporation, 2010.12)
① Geographic feature: Information about the geographical location and
characteristics - Use in Geographic Information Systems.
② Geospatial attribute information with that object (e.g: The owner of
land, price of land etc.)
Example:
Geospatial data: Location of the suffrage
Non-geospatial data: Dimension, Population
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6. Literature Review – Geospatial
• Open Data (Good quality national data) enabled for use with various
service (the cost of building the geospatial map comprises 90% of the
total project)
• Even before the open API is activated, various geo-related data is used,
such as the mashup (Kang & Kim, 2014).
• Open APIs accelerate R&D processes and generate new means of
commercializing content, especially in niche segments otherwise
difficult to serve (Aitamurto & Lewis, 2011).
• Opportunities in individual sectors “Geospatial domain”
 USD 800 billion in revenue to service providers and value to consumer
and business end users (McKinsey Global Institute, 2011). 6

7. 7

8. Data
• ‘Geospatial/Mapping data’ with 29 Open Data Companies
are selected from Open Data 500 List
(excepted 1 duplicated company).
17 Data Category
Business & Legal services Governance
Data/Technology Healthcare
Education Housing/Real Estate
Energy Insurance
Environment & Weather Lifestyle & Consumer
Finance & Investment Media
Food & Agriculture Research & consulting
Geospatial/Mapping Scientific Research
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9. Summary of 29 Geospatial Companies
No Company name Year founded Company type Business Model
ODC01 Azavea 2000 Private B2B, B2C, B2G, NGO
ODC02 Boundless 2013 Private B2B
ODC03 CityScan 2011 Private B2G
ODC04 Cloudmade 2007 Private B2B
ODC05 EarthObserver-App 2011 B2C
ODC06 Earthquake-Alert 2013 Public (Federal-USGS) B2C
ODC07 Esri 1969 Private B2B, B2C, B2G
ODC08 Garmin 1989 Public B2C
ODC09 Geofeedia 2011 Private B2B
ODC10 Google-Maps 2005 Public B2B, B2C, B2G
ODC11 HERE 2012 Private B2B, B2C
ODC12 indoors 2010 Private B2C
ODC13 Intermap-Technologies 1996 Public B2B, B2C, B2G
ODC14 Liquid-Robotics 2007 Private B2B
ODC15 Loqate-Inc 2009 Private B2B, B2C
ODC16 Mango-Transit 2011 Private B2C
ODC17 MapBox 2011 Private B2B, B2C, B2G
ODC18 Maponics 2001 Private B2B
ODC19 MapQuest 1967 Public B2B, B2C
ODC20 Marinexplore-Inc 2012 Private B2B
ODC21 Navico 2005 Private
ODC22 New-Media-Parents 2009 Private B2C
ODC23 OnStar 1995 Public B2B
ODC24 PolicyMap 2007 Non Profit B2B, B2G
ODC25 Rand-McNally 1856 Private B2C
ODC26 Stamen-Design 2001 Private B2B, B2C, B2G
ODC27 Telenav 1999 Public B2C
ODC28 Urban-Mapping-Inc 2006 Private
ODC29 Vizzuality 2011 Private B2B
ODC30 YourMapper 2005 Private B2B, B2C 9

10. Research Question
RQ. What Business Model of Open Data Company in the U.S
using Geospatial data?
- What is Open Data Company’ utilization of data strategy?
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11. Methods - Case Study
• Constructing a Framework for Open Data Business Model
 Canvas Model for open data and public sector information (PSI) re-use (Ferro &
Osella, 2012)
- ‘Types of Data Elaboration, Value Proposition, Price Mechanisms’
 Industrial Open Data: Case Studies of Early Open Data Entrepreneurs (Lindman,
Kinnari, & Rossi, 2014)
- Data Resources and Type + Product/Service type
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12. Methods - Case Study
• Canvas Model for open data and public sector information
(PSI) re-use (Ferro & Osella, 2012)
12

13. Methods - Case Study
• Industrial Open Data: Case Studies
of Early Open Data
Entrepreneurs(Lindman, Kinnari, &
Rossi, 2014)
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14. Framework
1)Data Resource and Type A1. Ground
A2. Aviation
A3. Ocean
B1. Open data
B2. Extracted & transformed data, scraped data,
B3. Private or Commercial data
2)Types of Data Elaboration C1. Data aggregation
C2. Data structuring and classification
C3. Data referencing
C4. Data validation
C5. Data mash-up
C6. Visual analytics
3)Price Mechanisms E1. Preminum / high-end product and Service
E1-1. A la carte
E1-2. Subscription fee
E1-3. Royalties
E2. Freemium / Basically Free, pay for additional service
E2-1. Feature limited
E2-2. Time limited
E2-3. Size limited
E3. Free
E3-1. Advertising powered
E3-2. Cross subsidization
E3-3. Zero marginal cost
4)Product/Service type D1. Final Product
F1-1. Web
F1-2. Mobile
F2-1. Local
F2-2. Global
F3-1. Industry
F3-2. Private
F3-3. Government
* 29 Companies are manually
coded by Researcher.
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15. Results :
1)Data Resource and
Type
Company Name
Ground Azavea, Boundless, CityScan, Cloudmade, EarthObserver-App, Earthqu
ake-Alert, Esri, Garmin, Google-Maps, HERE, Intermap-Technologies, L
oqate-Inc, Mango-Transit, MapBox, MapQuest, Maponics, New-Media
-Parents, OnStar, PolicyMap, Rand-McNally, Telenav,, YourMapper, indo
ors,
Aviation EarthObserver-App, Garmin
Ocean EarthObserver-App, Garmin, Liquid-Robotics, Marinexplore-Inc, Navico
• ‘Ground’ data are highly utilized
• The Companies using ‘Aviation’ & ‘Ocean’ mostly have their own collecting data solutions.
• ‘Geofeedia’ analyzed SNS data related to specific places or geospatial points.
 Most used Open Data resource.
 Using extracted data – Cityscan, Geofeedia, here, Liquid-Robotics, Marinexplore-Inc, OnStar,
PolicyMap
 Using Private or Commercial data – Cloudmade, Loqate-Inc, Maponics, PolicyMap, YourMapper
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16. Azavea – Using ground data
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17. Garmin – Using Aviation data
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18. CityScan – Using extracted data
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19. Geofeedia – Connected SNS data
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20. Results :
2)Types of Data
Elaboration
Company Name
Data aggregation Azavea, Boundless, CityScan, EarthObserver-App, Esri, Garmin, Geofeedia, HERE, indoors, Inter
map-Technologies, Liquid-Robotics, Loqate-Inc, Mango-Transit, MapQuest, Maponics, Marinexp
lore-Inc, New-Media-Parents, OnStar, PolicyMap, Rand-McNally, Telenav, YourMapper
Data structuring and
classification
Earthquake-Alert, YourMapper
Data referencing CityScan,
Data validation Loqate-Inc,
Data mash-up Azavea, Cloudmade, Esri, Geofeedia, Google-Maps, HERE, Loqate-Inc, MapBox, PolicyMap,
YourMapper
Visual analytics Cloudmade, EarthObserver-App, Esri, Intermap-Technologies, MapBox, Marinexplore-Inc, Navic
o, PolicyMap, Rand-McNally, Stamen-Design, Vizzuality
• Most Companies included a Data Aggregation domain that analyzed or processed various
Open Data and Commercial data. Companies tend to provide API services that processed their
data.
• ’Earthquake-Alert’, ‘YourMapper’ – Providing Earthquake information
• ‘Loqate-Inc’ – Validate Address information (unique BM in U.S)
• The value of Geospatial data related to how it was visualized. - ‘Stamen-Design,
Vizzuality’  specialized in visualization.
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21. Mango Transit - Data aggregation
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22. Onstar - Data aggregation
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23. Earthquake-Alert - Data structuring
and classification
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24. Vizzuality – Visual analytics
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25. Results :
3)Price
Mechanisms
Company Name
Preminum Azavea, Boundless, CityScan, Cloudmade, EarthObserver-App, Esri, Garmi
n, Geofeedia, indoors, Intermap-Technologies, Liquid-Robotics, Loqate-Inc,
MapQuest, Maponics, Marinexplore-Inc, Navico, OnStar, PolicyMap, Rand-
McNally, Stamen-Design, Telenav, Vizzuality, YourMapper
Freemium Google-Maps, Loqate-Inc, New-Media-Parents, PolicyMap
Free Earthquake-Alert, YourMapper
• Preminum Price domain correlated Data aggregation (Blue)
 To make a profit, Geospatial companies put emphasis on Data aggregation
with a preminum strategy.
 Preminum – e.g: Service fee, made to order
 Freemium – e.g: basically Google map api is a limited size
 Free – e.g: YourMapper get Advertising revenue
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26. RandMcnally – Preminum price
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27. Google Map – Freemium price
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28. Results :
4)Product/Service type Contents
Final Product Analysis Software, Selling geospatial data(map, data),
Web/Mobile application, Data related to Vehicle(Navigation,
Managing Vehicle), Visualization
Web/Mobile Analysis Solutions based on Web.
Navigation service specified vehicle comprised with Sensor
system.
Local/Global Aim to Global Service / EarthObserver-App, Geofeedia, HERE,
Intermap-Technologies, Loqate-Inc, Mango-Transit, MapBox,
MapQuest, Navico, OnStar, Stamen-Design, Telenav,
Industry/Private/
Government
B2B(19), B2C(18), B2G(8)
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29. Conclusion
• 1) Using ground data companies are predominant. In addition,
Aviation and Ocean data companies tend to have their own data
solutions.
• 2) In terms of data elaboration, most companies included a Data
Aggregation domain and that companies tend to provide the API
services that processed their data.
• Also, data aggregating companies are related to Preminum price
strategy (High-end product and service).
• 3) The importance of visualization in geospatial data service.
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30. Future study
• We have applied a Webometric analysis.
- Considering how open data companies are constructed in
an online environment. Focus on Geospatial companies
connected other data types (in OD 500 list) such as
healthcare, housing, education etc.
• We expect this study to lead to economic growth using
Open Data Industry.
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31. Thank you
JiYoung Park
heytree@ynu.ac.kr
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