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Earth Observation Data Sharing: Economic Issues
Moving Forward on Data Policy and Cooperation in Earth Observations
Bilateral U.S.-China CODATA Workshop National Academies of Science, Secure World Foundation
August 25, 2014
Mariel Borowitz, PhD Sam Nunn School of International Affairs
Georgia Institute of Technology
Outline
• Economic Attributes of EO Data • Conflicting Economic Views of Data – Public Good vs. Commodity – Key Uncertainties – Stakeholder Concerns
• Examples from U.S., Europe, Japan – Economic Models: Landsat
• Key Uncertainties Revisited • Conclusions
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Important Economic Attributes of Earth Observation Data
1. EO Data has significant economic value – Weather, climate, aviation, agriculture, mining, etc.
2. Non-rival in consumption – One person’s use of data does not diminish amount available for others
3. Excludability – Information often thought of as non-excludable – But satellite data can be kept secret, or put under copyright/ licensing
agreements 4. Increasing returns to use
– The more data is used, the greater the social returns – Kenneth Arrow, 1962, “Allocation of Resources for Invention”
5. Positive Externalities – Use of EO data provides benefits that extend beyond original user – Scientific understanding, value-added products
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Conflicting Economic Views of Data
Public Good • Key Attributes
– Non-rival, non-excludable – Positive externalities
• Implications for efficient use – Must be developed by gov’t
(industry will under-produce) – Share data as widely as
possible (maximize use/ social benefit)
– Charge marginal cost (generally zero)
Commodity • Key Attributes
– Economic value – Data can be excludable
• Implications for efficient use – Data can be efficiently
produced by private industry – Restrict access to data, charge
a fee for use, determined by supply and demand • Cost recovery • Commercialization
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Three Key Uncertainties 1. Is there a viable commercial market? – Is there sufficient demand to support a commercial
market? – Size/ form of the market: natural monopoly,
competitive? 2. What is the elasticity of demand? – How does demand react to changes in price
3. How can the benefits of EO data be quantified? – Revenues are easy to quantify (in dollars) – How to quantify other benefits (e.g. scientific
understanding)
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Stakeholders • Agency officials
– Best achieve agency mission – Maximize use/benefits -
science, knowledge • Free and open data sharing
• Legislative/ budget officials – Efficiency, budget pressures
• Cost recovery • Commercialization
• Commercial Industry – Profit
• Data sales • Government investment/
subsidies
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EO Data Policies in U.S., Europe, Japan
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NASA NOAA USGS ESA EUM JAXA JMA<1980
2000
2010
1980
1990
Unofficial)Sharing/)Bilateral)Agreements/)International)Ground)StationsCost)Recovery/)Commercial)Sales
Tiered)Policy
Nearly)All)Data)Freely)Available
Free)and)Open)Policy
Economic Models: Landsat • Data originally freely available
– Technology for sharing data lacking – Established value of data
• Efforts to sell data, commercialize program – Higher costs led to fewer sales
• Anecdotes of U.S. agencies purchasing similar, less expensive satellite data from another nation
– Profit model led to even higher costs, fewer customers – conflicts with public benefit goals of government
• Commercialization deemed impossible at that time, tiered policy adapted
• Data made freely available online in 2008 – huge increases in downloads, use – Product: medium-resolution, science-focused system – Substitutes: similar data available free/inexpensive from other sources – Compliments: increase of computing power, etc.
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Uncertainties Revisited: Is there a viable commercial market?
• Evidence suggests “no” in most cases – Dependent on specific product (resolution, etc.) – Particularly for low resolution data, data whose primary use
is science • Also depends on cost of supply – Could new low-cost start-ups change calculation?
• Importance of substitutes, complements – Data from non-satellite sources, satellite data from other
nations (decrease demand for commercial products) – Availability of computational capability, recognition of data
uses, GIS systems, growth of big data (may increase demand)
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Uncertainties Revisited What is the elasticity of demand?
• Relatively elastic • Change in price leads to
large changes in demand – Even low price leads many
to forgo use of the data – particularly science users
– Trend seen in tiered policies as well (related, non-monetary barriers)
• Rapid adoption of freely available data (e.g. Landsat)
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Uncertainties Revisited How can the benefits of EO data be quantified?
• Revenues are easy to
quantify (in dollars) – Often relatively low
• How to quantify other benefits (e.g. scientific understanding) – Value-added industry
seems to be much larger with free data
– Difficult to quantify science, societal benefits
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Conclusions • In practice EO satellite data seems to function more like
a public good than a commodity – Increasing returns to use, positive externalities
• Social benefit maximized when data made available free (maximizing use)
• Data under-produced by industry – Commercial industry not viable in most cases – Ethical concerns play an intervening role (e.g. weather,
natural disasters) • Future role for industry? – Providing data not already produced by government – Producing data at a lower cost
• Innovative arrangements to allow free data sharing
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Thank you Moving Forward on Data Policy and Cooperation in Earth Observations
Bilateral U.S.-China CODATA Workshop National Academies of Science, Secure World Foundation
August 25, 2014
Mariel Borowitz, PhD Sam Nunn School of International Affairs
Georgia Institute of Technology