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 ParkYeungNam University, S.Korea

Parallel Session 1 (1.3_Shaping creative economies through clusters)

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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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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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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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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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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

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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

Transportation8

Summary of 29 Geospatial Companies No Company name Year founded Company type Business ModelODC01 Azavea 2000 Private B2B, B2C, B2G, NGOODC02 Boundless 2013 Private B2BODC03 CityScan 2011 Private B2GODC04 Cloudmade 2007 Private B2BODC05 EarthObserver-App 2011 B2CODC06 Earthquake-Alert 2013 Public (Federal-USGS) B2CODC07 Esri 1969 Private B2B, B2C, B2GODC08 Garmin 1989 Public B2CODC09 Geofeedia 2011 Private B2BODC10 Google-Maps 2005 Public B2B, B2C, B2GODC11 HERE 2012 Private B2B, B2CODC12 indoors 2010 Private B2CODC13 Intermap-Technologies 1996 Public B2B, B2C, B2GODC14 Liquid-Robotics 2007 Private B2BODC15 Loqate-Inc 2009 Private B2B, B2CODC16 Mango-Transit 2011 Private B2CODC17 MapBox 2011 Private B2B, B2C, B2GODC18 Maponics 2001 Private B2BODC19 MapQuest 1967 Public B2B, B2CODC20 Marinexplore-Inc 2012 Private B2BODC21 Navico 2005 Private

ODC22 New-Media-Parents 2009 Private B2CODC23 OnStar 1995 Public B2BODC24 PolicyMap 2007 Non Profit B2B, B2GODC25 Rand-McNally 1856 Private B2CODC26 Stamen-Design 2001 Private B2B, B2C, B2GODC27 Telenav 1999 Public B2CODC28 Urban-Mapping-Inc 2006 Private

ODC29 Vizzuality 2011 Private B2BODC30 YourMapper 2005 Private B2B, B2C 9

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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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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Methods - Case Study

• Canvas Model for open data and public sector information (PSI) re-use (Ferro & Osella, 2012)

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Methods - Case Study

• Industrial Open Data: Case Studies of Early Open Data Entrepreneurs(Lindman, Kinnari, & Rossi, 2014)

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Framework1)Data Resource and Type A1. Ground

A2. AviationA3. OceanB1. Open dataB2. Extracted & transformed data, scraped data,B3. Private or Commercial data

2)Types of Data Elaboration C1. Data aggregationC2. Data structuring and classificationC3. Data referencingC4. Data validationC5. Data mash-upC6. Visual analytics

3)Price Mechanisms E1. Preminum / high-end product and ServiceE1-1. A la carteE1-2. Subscription feeE1-3. RoyaltiesE2. Freemium / Basically Free, pay for additional serviceE2-1. Feature limitedE2-2. Time limitedE2-3. Size limitedE3. FreeE3-1. Advertising poweredE3-2. Cross subsidizationE3-3. Zero marginal cost

4)Product/Service type D1. Final ProductF1-1. WebF1-2. MobileF2-1. LocalF2-2. GlobalF3-1. IndustryF3-2. PrivateF3-3. Government

* 29 Companies are manually coded by Researcher.

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Results : 1)Data Resource and Type

Company Name

Ground Azavea, Boundless, CityScan, Cloudmade, EarthObserver-App, Earthquake-Alert, Esri, Garmin, Google-Maps, HERE, Intermap-Technologies, Loqate-Inc, Mango-Transit, MapBox, MapQuest, Maponics, New-Media-Parents, OnStar, PolicyMap, Rand-McNally, Telenav,, YourMapper, indoors,

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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Azavea – Using ground data

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Garmin – Using Aviation data

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CityScan – Using extracted data

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Geofeedia – Connected SNS data

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Results :2)Types of Data

ElaborationCompany Name

Data aggregation Azavea, Boundless, CityScan, EarthObserver-App, Esri, Garmin, Geofeedia, HERE, indoors, Intermap-Technologies, Liquid-Robotics, Loqate-Inc, Mango-Transit, MapQuest, Maponics, Marinexplore-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, Navico, 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.20

Mango Transit - Data aggregation

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Onstar - Data aggregation

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Earthquake-Alert - Data structuring and classification

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Vizzuality – Visual analytics

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Results :3)Price Mechanisms

Company Name

Preminum Azavea, Boundless, CityScan, Cloudmade, EarthObserver-App, Esri, Garmin, 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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RandMcnally – Preminum price

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Google Map – Freemium price

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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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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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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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Thank you

JiYoung Parkheytree@ynu.ac.kr

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