The future of satellite data sharing policies will depend on whether the current trends continue and on which new trends may emerge. Will nations that currently make data freely available continue to do so, or will this data become more restricted? Will nations that restrict access to data begin to instead make it open? How will new actors entering this sector treat their data? Understanding these trends is not only of academic interest—it also shapes the options that interested actors have to influence these changes.
One of the reasons that agencies don't share data is that they don't view data sharing as a key part of their mission, and hence don't view it as a priority in requesting and allocating resources. This is important—it means that there are not overriding security, economic, or normative arguments for restrictions or a strong cultural bias within the agency against open data. In fact, if asked directly why they do not share data, these agencies are likely to respond that they do share (just in ad hoc or technically limited ways) or that they would like to share their data, but can't afford it.
This has important implications for the future of data sharing in these agencies, and the types of developments or arguments that might prompt changes. Academic arguments about the economic or normative effects of satellite data sharing, as have been highlighted in multiple reports and meetings in the past, are unlikely to be convincing on their own, as these agencies often do not disagree with these assessments; they just “can't afford” to act on them. Instead, actors who wish to increase data sharing would need to focus on showing these agencies how data sharing can support their mission and/or on providing the resources needed to undertake these activities.
The agency priorities and culture that underlie these arguments do not change easily. For agencies to view data sharing as a priority worthy of an investment of time and resources there need to be clear benefits to doing so. For example, reputational benefits gained through national and/or international recognition of open data sharing policies, by government leaders or in organizations such as GEO or WMO, can help provide an incentive for sharing. Negative attention brought to the lack of data sharing may also be effective, but would be risky, as nations receiving criticism may reduce their involvement in these voluntary organizations, rather than change their data sharing policies.
Systems that allow agencies to document and receive credit for the ways in which their data is used—in research, value-added products, or other programs—can also provide reputational benefits and incentives. International organizations and interest groups can help to make this easier by promoting technical methods and professional norms that enable this, such as the use of persistent identifiers that ensure the original data source can be tracked, and expectations for data sources to be properly cited. Collection and presentation of metrics showing which countries are contributing most to global science, perhaps on a per capita basis, could provide additional recognition and benefit.
Argentina provides an interesting model for small space programs that wish to maximize their international impact and reputation. The country has only has only developed three Earth observation satellites, but each was designed to fulfill a particular scientific need not already addressed by the international community. Partnership with larger space programs, particularly NASA, made it possible to design and launch advanced Earth observing systems. Argentina made data from these satellites freely available, providing an important contribution to global environmental monitoring, and increasing its standing in international organizations, with only a relatively small investment.
Some of the agencies do not make data available because they don't believe the data would be useful. If there was a demonstrated demand for the data, they would be more inclined to invest time and resources in providing it. The lack of demand may be due to low utility of the data, but it may also be due to a lack of awareness of the data's existence, or perceived difficulties of accessing the data. International organizations and interest groups could help to determine potential users of these datasets. They can publicize the existence of the data to appropriate user groups and even assist as a conduit in requesting and accessing the data by providing appropriate contact information.
The decrease in the cost of computing technology and increasing spread of the Internet can also be factors in increasing satellite data sharing among smaller programs. As this technology becomes less expensive and more widely available, it lowers the barriers to data sharing. Combined with reputational benefits and other trends, decreasing costs for making data available will increase the likelihood that it is shared. For agencies that are interested in sharing data, but still feel they can't afford it, resource assistance can be a relatively simple answer. If national-level decision-makers are supportive of open data sharing, this could come in the form of additional national funding directed towards data dissemination systems. If not, international organizations and others can provide resource assistance in a variety of direct and indirect ways, as described below.
International organizations can share technical and logistical solutions that lower the costs and other barriers to data sharing for these nations. Sharing data portal technology, design, and lessons learned could help lower the time and resources needed to develop a new portal. Sharing best practices for collecting and presenting usage statistics is another area of potential benefit. Already, GEO has helped to provide some guidance to agencies on how to implement standard creative commons usage licenses. These types of assistance improve the situation for data users, who gain access to more data with systems that are more standardized, and data producers, who face reduced challenges to implementing a data sharing system. In the case of developing nations, this assistance could go beyond knowledge sharing, to include provision of ground station or computing equipment and hands-on training, perhaps in partnership with aid organizations such as USAID or the World Bank. These types of programs would help build capacity in developing nations while also benefiting users worldwide by increasing data availability.
Agencies could also undertake direct cooperation or assistance in developing data sharing technologies and policies. Following the example of the DMCii and the PanGeo Alliance in the commercial sector, a nonprofit or international organization could develop a data portal that would host data from multiple countries—focused around small satellites, satellites from a particular region, satellites of developing nations, or university satellites, for example. These cooperative data portals would provide an easier experience for data users, who only need to visit one location to access data from many countries, and provide a cost effective solution for satellite operators, who could take advantage of economies of scale in data distribution systems, even if they operate only one or two small satellites. The satellite-owning agencies would only need to transmit the data to this central body, with no need to invest in the development or maintenance of a user-friendly data portal of their own. If the central body was equipped with an adequate receiving station, data could be collected directly from the satellites, with no effort on the part of the satellite-owning nation. With multiple agencies funding this central portal, the costs of data distribution would be quite low for each agency, while each would still gain the reputational benefits associated with sharing their satellite data.
Rather than building a new data portal, agencies such as NASA, ESA, or JAXA with well-developed data portals could offer to host data collected by foreign satellites in their existing portals, acting as a worldwide host for smaller agencies that would like to make their data available but feel they can't afford it. ESA already hosts external, third-party satellite data, although this data is typically acquired by ESA through special purchases or agreements and access is limited in accordance with these arrangements. Data hosted as a free service for a foreign nation would be provided on an open basis, following the data policy of the hosting agency.
This type of cooperation would provide many of the same benefits as the international consortia described above, with almost no resource investment required on the part of the satellite-owning agency, and very little required on the part of the larger agency, as well. It would benefit the satellite-owning agency, which could promote awareness of its capabilities, and its open data contribution. The system would also benefit the reputation of the agency hosting the data, as it would increase their overall offerings. The Landsat Global Archive Consolidation (LGAC) program provides a successful example of this type of arrangement. International Landsat ground station operators were willing to provide their data free of charge for inclusion in the US Landsat archive in exchange for the United States’ willingness to recover the data from outdated media and process it into standard products.
The organizations hosting data would not need to be governmental or even nonprofit organizations. Google, Amazon, and others have demonstrated an interest in hosting environmental satellite data on their cloud computing forums, typically providing free access to users (who then have an incentive to purchase further storage or processing capabilities through these providers). Smaller space agencies could potentially work with these organizations to increase the amount of data available online. Once again, such an agreement would require a smaller investment than developing a dedicated data portal and would increase the range of offerings on these commercial sites.
The second major reason that nations choose not to share is based on economic attributes of the data. Nations hope to benefit from data sales that offset government costs or to promote the development of a commercial remote sensing sector that will contribute to national innovation and economic growth. However, after decades of experimentation with a variety of remote sensing technologies, to date, no commercial remote sensing endeavor has been able to survive without government support. By the definition in chapter 4, there is no viable commercial market for satellite data. Further, there are broad noncommercial uses for Earth observation satellite data. The framework in chapter 4 suggests, and nations have found in practice, that under these conditions, economic benefits are maximized by providing the data on a free and open basis. This realization largely explains the trend toward free and open policies seen among space programs in the past two decades.
However, this trend is not absolute. Existing free and open policies are regularly questioned, particularly by national-level policy-makers wondering if these expensive activities can be conducted more efficiently. As noted above, many nations, even those that have largely adopted free and open policies, continue to attempt data sales and commercialization. Some new commercial remote sensing companies are advocating for government to turn certain types of data collection over to the private sector. How can the government address these emerging issues?
Economic theory and decades of experience with data sales and commercialization efforts have shown that in practice, just as in theory, open data provision is the most economically efficient method of distributing data for all, or nearly all, Earth observation satellite data. Government data collection and free and open distribution maximize net social benefits. Governments that make their Earth observation satellite data openly available will generate the greatest benefits for themselves, for their citizens and for people around the world.
When data is made openly available, without restrictions on access or redistribution, its use is maximized. It can be used by scientists, nonprofits, entrepreneurs, or the general public. Use of the data results in improved scientific understanding that benefits everyone, in more efficient or effective programs to serve the public, and in the creation of new value-added products that increase offerings for consumers and generate tax revenue for the government. Often the full breadth of applications is not realized by the original developers, and may not be discovered until years after the data has been collected, as new technologies, new scientific questions, or new markets create new opportunities for data use. Open data is more easily combined with other data, making it even more likely that the data will be used in new and productive ways.
Experience over the past two decades has shown that this is the case in the Earth observation satellite sector. However, efforts to further study, document, and publicize these effects will be important to sustaining support for these policies among agencies, and the national-level policy-makers that influence them. The benefits of commercial activity are easy to demonstrate in monetary terms and descriptions of international sales that everyone can understand. It is important for metrics on the benefits of open data to also be collected, shared, and explained to make their benefits clear, as well.
As mentioned above, none of the existing commercial remote sensing efforts can survive without government support. However, public-private partnerships for data collection may be more economically efficient than open data, even if the commercial market for the data is not viable on its own, if the decrease in costs achieved through these arrangements exceeds the decrease in benefits caused by restrictions on data access and redistribution. Therefore, it is useful to examine the extent to which this is the case for the existing public-private partnerships.
Any policy that places restrictions on data access and redistribution, as is necessary to facilitate commercial sales, will decrease data use compared to an open data policy. However, this decrease in use is likely to be relatively low if there are only narrow noncommercial uses of the data. For example, if high-resolution SAR and visible imagery is primarily of use for intelligence and defense purposes, it can be purchased by these agencies at a cost lower than would be necessary to develop the satellites themselves. Since meteorologists, for example, do not have a need for this data, the fact that they cannot access the data does not cause a loss in benefits. However, there are some indications that this data may have broader uses. Under the current NGA-negotiated license, other federal agencies can access the data. Some NASA scientists have taken advantage of this, finding the high-resolution imagery to be particularly useful in studies of the cryosphere. NASA's short-lived Science Data Buy program also showed that the research community would find the high-resolution imagery useful, particularly with some adjustments to ensure careful calibration. However, with low-cost access to the data only available for five years under the program, researchers did not find it prudent to undertake a long-term research portfolio that would depend on this data. In 2001, the National Research Council review stated that SAR data was “one of the most exciting remote-sensing technologies” for scientists.1 Such a statement does not imply narrow, security-related uses.
Given this situation, governments may be able to increase economic efficiency by adopting arrangements that increase access to the data, particularly for noncommercial users. Licenses that allow the data to be shared freely with other government agencies, as is the case with the US data purchases, are a good start. Governments should look to expand this access, perhaps negotiating for a license that allows government-purchased data to be used for noncommercial purposes by any user—not just those in federal agencies. This is unlikely to have a significant effect on commercial revenues, as nongovernment, noncommercial users typically make up a very small portion of their customer base. If the license conditions on the data could be made clear—perhaps with persistent identifiers—it may even be possible to allow free redistribution of the data among noncommercial users. ESA has done this to some extent. In 2006, the agency signed a three-year contract that would give it access to 12,000 images from the SPOT-2 and SPOT-4 satellites, which could then be provided for free to research and education users.
Data sharing agreements in public-private partnerships can also differentiate other attributes of the data. In the case of remote sensing satellites, timeliness can be particularly important. Many commercial uses of the data rely on it being acquired quickly, and very old data is typically less commercially viable. France's arrangement to provide archived SPOT data will provide a good test of the potential benefits of this type of arrangement, demonstrating whether there is significant demand for this type of data and the range of noncommercial uses that may be possible.
In considering the economic efficiency of these endeavors, governments should remember that the cost savings are those stemming from general commercial efficiency—the idea that a commercial entity can develop and operate a satellite more efficiently than the government—and from decreased reliance on general taxation, and the subsequent reduction in deadweight loss, needed to fund the satellite system. The first benefit may not be as large in the commercial remote sensing sector as in some other cases. With high fixed costs to build and launch a satellite, and low marginal costs of data distribution, commercial remote sensing is a natural monopoly. This has led to significant consolidation in the remote sensing sector, resulting in one, or very few, commercial remote sensing companies in each country or region. The lack of competition decreases normal market incentives to innovate and keep prices low. However, it is still true that commercial entities can operate with less bureaucracy and red tape than the government, and although governments tend to favor domestic industry, international commercial remote sensing companies do compete with one another to some extent.
With respect to efficiency benefits from decreased reliance on general taxation, it is important to make a distinction between savings that occur due to sales to the commercial sector and savings due to sales to foreign governments. If the vast majority of data sales are to governments, this does not reduce the reliance on general taxation—just shifts it from one country to another. In these cases, collaboratively built and operated satellites might be more efficient. Taking high-resolution imagery in the United States as an example, if the United States were to pay 60 percent of the cost, and two or three other governments paid the remaining 40 percent, the cost of the program would be the same from the perspective of the governments involved, but as a fully government-owned program, the data could be provided on a free and open basis, maximizing social benefits. From a global economic perspective, this would likely be a more efficient arrangement. This type of shift—from commercial provision to government provision—is rare, however. The Copernicus program in Europe provides the only example, with its plans to collect and openly share medium-resolution imagery of a type currently collected and sold by some private companies, and even that plan has yet to be implemented.
Transition from commercial to government control is also not without drawbacks. It may be challenging for the United States to convince other nations to participate—the government would essentially be taking on the marketing role currently undertaken by the commercial entity. Returning to the theoretical example above, if raising the remaining 40 percent of costs requires the participation of many other governments, rather than two or three, this is an even greater challenge. Further, due to the need for international negotiations and government participation, a cooperatively developed international satellite is likely to be more expensive than one built by the commercial sector. Nations will need to be convinced that it is worthwhile to increase their investment, at least slightly, to get the benefits of free data provision. Effort will be required to maintain this international effort, particularly if it is to continue to support a series of satellites, rather than a single satellite. If any nation decides to decrease or end its support for the program, sustainability is in question for all others. For the example given, which included a 60/40 cost-sharing arrangement, as time goes on, agency officials and policy-makers not involved in the original planning may ask why the United States pays more than half of the cost of a system that benefits all partners equally (since the data is freely available to all). These practical considerations and transaction costs must be factored into efforts to increase economic efficiency.
One possible compromise between international cooperation and commercial provision would be an international open data buy. Rather than cooperating to jointly build a satellite, nations could negotiate to jointly purchase data from a commercial entity under an open license. The result would be the same—data could be freely shared with all, maximizing social benefits, but countries would not need to reinvent the wheel, and could benefit from existing commercial efficiencies. There may even be some opportunities for offsetting costs raised by general taxation if the company also sells specialized datasets or value-added products to commercial users, although governments should expect such commercial cost sharing to be minimal.
This type of open data buy procurement would be the most efficient approach for some emerging commercial remote sensing activities, as well. GPS Radio Occultation (GPS-RO) data provides the most immediate candidate. GPS-RO data has proven to be very valuable for meteorology, significantly improving the accuracy of weather forecasts when combined with data from traditional weather satellites and other weather observation systems. Currently, the only dedicated GPS-RO constellation is the COSMIC-1 system, developed as a joint effort between the United States and Taiwan and launched in 2006. Data from this constellation has been freely shared internationally, and has been incorporated into weather forecasting systems in many countries. Planning for the follow-on COSMIC-2 system is underway.
GPS-RO technology is well understood and relatively inexpensive. In recent years, a number of companies have announced plans to develop commercial GPS-RO constellations. These organizations have lobbied the US government to purchase GPS-RO data from commercial entities rather than continuing government development. US decision-makers, particularly in Congress, are eager to promote the growth of US commercial remote sensing activities and to benefit from cost decreases promised by these commercial entities. However, NOAA officials question whether the US government will truly save money by purchasing commercial data, given that Taiwan is paying more than half the cost of the existing and planned government systems. They also worry about the impact of ending free international sharing of this data that has proven to be of such value to weather forecasting, and the implications of doing so for US commitments to share data under WMO Resolution 40 and on the norm of free international exchange of meteorological data in general. A move by the United States from free data distribution to a commercial model that restricts access could lead other nations to do the same. Right now, the United States (and every other nation) receives much more free data from the WMO World Weather Watch than it puts in. If nations begin restricting access to data to allow commercial purchases, this situation could change, and all nations would be worse off than before.
The framework from chapter 4 further illustrates why such an arrangement would be unlikely to provide significant benefits to the United States. GPS-RO data is primarily useful to governments for use in numerical weather forecasting models—there is not significant commercial demand for the data. As such, this data falls into quadrant I or II in Table 17.1, and the government should not expect to achieve significant cost savings or economic efficiency gains from commercial sales. If GPS-RO data is narrowly useful for the meteorological sector, it may belong best in quadrant I. In this case, a data purchase that allowed the data to be freely shared for official meteorological use and perhaps also for research uses may be efficient. However, it seems likely that the data would also have important uses for climate and other environmental studies, in which case it would more appropriately be placed in quadrant II. In this instance, free and open data provision would maximize net social benefits. If the US government could arrange to share the costs of purchasing the data under a global open data license with other nations—Taiwan, at least, and perhaps others—it could capture the savings of commercial development and operation while maintaining the significant benefits of open data sharing. At least one of the emerging GPS-RO companies has expressed a willingness to engage with the government in this type of arrangement.
Table 17.1 Commercial Remote Sensing and Economic Efficiency
| Narrow Noncommercial Uses Less benefit to open data |
Broad Noncommercial Uses Greater benefit to open data | |
| Nonviable Commercial Market (government funding required) Less savings from data sales |
I Open data policy or tiered data policy Existing remote sensing companies (e.g., DigitalGlobe, Airbus Defence and Space, e-Geos) |
II Open data policy Most Earth observation satellites |
| Viable Commercial Market (no government funding required) Greater savings from data sales |
III Data sales Possibly emerging remote sensing companies (e.g., Planet Labs, Terra Bella) |
IV Open data policy or tiered data policy Possibly emerging remote sensing companies (e.g., Planet Labs, Terra Bella) |
There has also been significant attention to the rise of commercial remote sensing companies, particularly in the United States, that are using new small satellite technology and traditional Silicon Valley techniques to provide new types of data and lower the cost of data access. Top among these are Planet Labs and Terra Bella. These companies are focusing primarily on temporal resolution—imaging the same area once a day, or even providing persistent video, rather than spatial resolution, as other commercial remote sensing companies have done. They argue that there is a commercial demand for this type of information that is not currently being met. While both companies have launched satellites, neither has achieved full operational status, so the reality of these claims cannot yet be assessed. As of yet, neither company has required or requested significant government assistance in the form of development funding or guaranteed data purchases. It is possible that these will be the first remote sensing companies to be commercially viable in the traditional sense.
Governments should assess the value of the data for noncommercial uses, as well. The NGA has already announced a plan to examine the value of the data for its own national security purposes. If purchased using licensing agreements similar to those used in its contracts with other remote sensing companies, this may provide an opportunity for other US agencies to evaluate the data, as well.
If there is a commercially viable market, and the government assessment shows that there are relatively narrow noncommercial uses, the government can purchase the data at the same prices and under the same conditions as other users—just as it would any other commodity, such as a laptop or an office chair. To the extent that the data has broad noncommercial uses, the government could investigate options for purchasing a license that allows free access to the data for noncommercial uses or making a bulk purchase of archived data, to be made freely available under an open license. The most beneficial arrangement will depend on the specific attributes of the data.
If these systems do need government subsidization to continue operations, the government will need to consider the value of noncommercial uses to determine whether these benefits outweigh the requirement for government support. Government leaders should consider whether this support is needed only in the short term or for a longer period, and whether provision of this “start-up funding” may be a good investment for the government, given the potential benefits of a vibrant commercial remote sensing sector. This echoes the decision that nations have made, and continue to make, with existing, high-resolution imaging companies. Some countries argue that while the “start-up” support for these existing companies has lasted longer than many nations had hoped or projected, it does not necessarily mean these efforts at commercialization have failed. The government should continue to realistically evaluate the likelihood that these activities will become commercially viable in the future.
Overall, what does all of this mean for the future of satellite data sharing? The economic realities of satellite data mean that, as a rule, it is most efficiently treated as a public good and shared freely. Failed efforts at commercialization and dramatic examples of the impact of free data policies have helped to clarify these economic attributes and have helped to drive a trend toward free and open data policies. To maintain this trend, governments and others will need to actively document and demonstrate these benefits, which are not always clearly visible to those outside the Earth observation satellite community, or even everyone within it.
Organizations and nations that hope to increase the availability of satellite data and decrease gaps in climate data collection and sharing should actively work to increase the reputational benefits of data sharing, through organizations such as GEO and WMO. They should consider direct investments of time, technology, and funding to make archived data or data collected by smaller programs that do not or cannot prioritize data sharing more openly available. Governments should promote interactions with the private sector and the growth of commercial remote sensing activities, but this should be done in a way that maximizes long-term, global economic benefits over private returns and short-sighted cost savings. They must carefully consider whether new technological trends—small satellites, big data, and cloud computing—are truly changing the economics of the remote sensing sector, or just providing new ways of operating within the same basic structure. There is great potential to increase the benefits from existing and future Earth observation activities, if the right actions are taken to do so.
Finally, we can ask what all of this means for the open data movement in general. How can the lessons learned from the Earth observation satellite community inform policy-making in other areas? For individuals interested in these questions the greatest takeaway from this book is the validation of the model of data sharing policy development presented in part I. Application to the issue of satellite Earth observation helped to demonstrate the value of using this model, which places the agency as the central actor, and considers the impact of both people—national government, international, and nongovernment actors—and ideas—the economic, normative, security, and technical attributes of the data—in understanding the development of data sharing policies. This model can be used to understand why open data sharing initiatives have been successful in some cases and not others, and it can help to direct the development of future policies.
The model demonstrates that the mission and culture of the agency are key to understanding how and why particular data sharing policies are adopted and implemented the way they are. Free data sharing isn't free from the perspective of the data producer, so the agency needs to have a reason, and an ability, to undertake these activities. Just as seen in the Earth observation satellite community, if an agency doesn't believe data sharing is an important part of its mission, it is unlikely to make its data available. In these cases, national-level policy-makers that direct agencies to share data, through initiatives or laws, are unlikely to see these directives implemented as enthusiastically as they'd like. Similarly, if agencies view open data sharing as an important element of their mission, they are likely to push back against efforts to commercialize or otherwise restrict data sharing.
National-level policy-makers can attempt to affect agencies by better understanding the role data sharing plays in the agency's mission. Sharing can be incentivized by pairing open data initiatives with resources needed to undertake these activities and with efforts to highlight how the data is being used, providing reputational benefits for the agency. Laws that prohibit data sharing are typically effective, but more nuanced directives to share in particular ways or with particular groups require resources and reputational incentives, just as in the case of open data sharing.
Actors that are external to the government—interest groups and international organizations, for example—can play an important role in reinforcing agency culture, providing reputational benefits, and providing information about the effects of relevant data sharing policies in other nations that allow more informed policy-making. These organizations can help bring attention to the distributional effects of data sharing policies, keeping in mind that one of the benefits of open policies is the ability to use data in ways not originally intended or predicted.
Considering these actors and their political interactions without including the ideas and issues that they are debating will paint an incomplete picture. It is important to understand the range of interpretations regarding the security and privacy aspects of the data. Can sharing the data contribute to national security, or does it pose significant security or privacy risks? Are there alternative versions of the data or types of policies that could manage these risks? Normative arguments can also be very strong. Are there ethical reasons that the data must be either shared or restricted? Data that has broad noncommercial uses is likely to result in significant economic benefits if shared widely. If there is a viable commercial market, there may be opportunities to benefit from public-private partnerships. Finally, it is important to understand the technologies that are used to collect, produce, and distribute the data. Changes in technology can affect the other attributes of the data, changing the overall conditions for sharing. The table at the end of part I can act as a guide to consider these issues.
The model and the example of the space sector can also help to provide a general understanding of where open data policies will be more or less likely to be implemented. For example, open data provision is unlikely in cases where such sharing is seen as unrelated or even contrary to the agency mission or culture. This may be the case in agencies that don't typically deal directly with the public, or in agencies—focused on national security or working with personal information—that value secrecy and discretion. National-level policy-makers who decline to provide resources needed to support data sharing systems or who fail to recognize the benefits of agency data sharing will inhibit the adoption of open data policies. Legislatures can also prohibit data sharing by making distribution of the data illegal. In cases where there are significant national security or privacy risks of sharing data, this may be appropriate, although opportunities to aggregate or otherwise transform data into a form that could be shared can also be explored. Further, if the data has not been shared in the past, there is unlikely to be a large group of users advocating for data sharing or looking for these types of opportunities.
When the technologies for collecting and/or providing the data are relatively expensive, and when the primary users of data outside the government are private actors, data sales will be attractive, and potentially more economically efficient, than open data policies. If the agency does not have a strong preference for data sharing based on its mission or culture, it may favor cost recovery efforts or commercial partnerships to decrease pressure on its budget, and national-level policy-makers concerned with budget issues are likely to share these views. Organizations that can afford these data purchases may advocate for status quo pricing if it gives existing commercial actors an advantage over new entrants. Data collection technology that is sufficiently well understood can also lead to commercial involvement and even commoditization of the data.
Agencies that have a culture of openness and see data sharing as part of their mission—perhaps because of an affiliation with the science community or a broad public information or service-oriented responsibility—will be more amenable to data sharing. In these cases, there may be existing users who understand the value of the data and are interested in using it. These groups can advocate for sharing and make the value of the data clear to others, including national-level decision-makers. This makes national-level support for sharing more likely, and can lead to provision of resources and reputational benefits that further promote sharing by the agency. This will be made even easier if the technologies for data collection and/or provision are relatively inexpensive and the uses are primarily noncommercial. Strong normative arguments for data sharing, related to uses of the data and/or to issues of government transparency, can reinforce these trends.
As a whole, the spread of Internet and computing technology is making data more easily accessible and resulting in a more information-savvy citizenry. Users are more likely to recognize the benefits of open data sharing and have the skills needed to use the data—as scientific researchers, as journalists, as entrepreneurs, or as members of the informed public. Interest groups, agencies, and legislatures, and all other elements of the model of data sharing policy development are affected by these developments. The trend toward open sharing of government data will not be smooth and it may never extend to all government data, but it is a trend that will continue moving forward.
1. National Research Council, “Resolving Conflicts Arising from the Privatization of Environmental Data,” ed. Freeman Gilbert and William L Chameides (2001).