Why Data Providers Say No...And Why They Should Say Yes

Last Updated: January 30, 2012

After getting organized, you have a solid foundation to begin the dialogue with data owners. The reasons below are the most common that NNIP partners encounter, and generally assume that public data owners have genuine concerns about sharing their agency's data files. You can be prepared by understanding the agency staff perspective and foreseeing their objections.

Why Data Providers Say No...

  1. "Preparing the file will burden the already overworked staff."
  2. "I'm afraid of being burned by bad publicity."
  3. "I'm worried about mishandling or improper release of the data."
  4. "The data source is a mess."
  5. "Our agency is making money from selling the data."


And Why They Should Say Yes


1. Preparing the file will burden the already overworked staff.

One of the most common reasons that data providers say no does not relate to a legal or political issue, but a practical one. The staff members are pressed with work for core agency operations and reluctant to add on preparation of datasets and documentation for external users. There is no way to eliminate the extra work for the staff, but there can be benefits to offset the costs.

  • Offer additional analysis useful to the agency's work. Agency staff may lack the time or expertise for analysis of their own data for internal purposes. In return for data sharing, you can offer to fulfill simple agency requests or return enhanced files to the agency. As one example, in exchange for a file of the locations of homeless prevention payments by the District of Columbia, NeighborhoodInfoDC provided the local Homeless Coordination agency with geocoded files and a set of simple maps so they could explore the programs' impact on neighborhoods.
  • Offer access to relevant indicators derived from another office's data. Agencies are often more willing to share data with an outside organization than with other agencies. For example, knowing the number of births or the number of new housing units planned by census tract helps the school district's ability to forecast enrollment.
  • Save the agency time by answering community inquiries. Local agencies may already spend a great deal of their time fulfilling community data requests one-by-one. If you provide publicly-available updated summary statistics in charts and maps, agency staff can refer data seekers to your website and spend less time answering inquiries.
  • Reassure the data owners that you have the skills to use the data. This includes letting them know that your qualified staff will not need extra assistance in basic use of the data, perhaps through examples of other data analysis you have done.


 2. I'm afraid of being burned by bad publicity.

Beyond a simple lack of time to fulfill a data request, an agency can reasonably fear public scrutiny and damaging publicity.

  • Give examples where agencies and communities have benefited (or at least not been harmed). As the NNIP network has grown, we have strong evidence that responsible data sharing is happening in many cities without negative consequences. Real-world examples from other cities can illustrate the potential advantages of having neighborhood-level data available to inform decisions by commercial firms, non-profit organizations, and other community actors (see Stories for specific case studies).
  • Provide disclaimers to protect the agency or credit to reward them. Depending on the circumstances, agency staff may want to distance the agency from politically sensitive analysis or errors due to poor data quality. This can be accomplished by a standard disclaimer on reports using the data or a blanket disclaimer clause in the data sharing agreement. On the flip side, agency leaders and staff should get credit for supporting community use of information, and explicitly acknowledging data providers or co-hosting online reports will highlight their progressive actions.
  • Try peer pressure. Having examples of other local agencies that have shared their data may help convince agencies that are more reluctant. NNIP partners have found that over time, they can shift the culture so that data-sharing is expected, not the exception. Outside your own community, you can point out that many other cities have community information systems that give them a competitive advantage in fundraising efforts and more effective data-driven nonprofit and government programs.
  • Give them advance notice of upcoming analysis. In some instances, NNIP partners have agreed to let the agency review the analysis for a given period of time before publication. An agency can be helpful in confirming that the findings make sense or add any cautions about interpretations, but it should not have veto-power over the release of analysis.


 3. I'm worried about mishandling or improper release of the data.

Some data, such as property records, are public, but more often the data received by NNIP partners is sensitive and confidential, such as individual records about public school enrollment, food stamp recipiency, or births and deaths. Release of the data may be regulated by state or federal law, such as HIPPA for health data or FERPA for student data.

  • Develop and practice secure procedures for handling confidential data. These steps should be outlined in a formal data sharing agreement before receiving the files, and could include confidentiality agreements for staff that will be using the data, encrypted data drives to store the data, and suppression rules to avoid individual identification. To see an example, download security procedures, a data log, and a staff confidentiality pledge from NeighborhoodInfoDC.
  • Develop a formal, written agreement to share the data. A written agreement can specify restrictions on the release of analysis or data files and ensure both parties have a mutual understanding of the conditions. See "Key Elements of Data Sharing Agreements" for more information. For a narrative describing how this negotiation was accomplished by a collaboration of the public school system, local foundation, and researchers in Grand Rapids, see the article Developing a Master Data Sharing Agreement.
  • Give examples of similar data being released in other cities. To assuage concerns that release of the data is not allowed, share the results of the NNIP Data Inventory with the agency staff to give them confidence that there are precedents for releasing the requested type of data.


The U.S. Government Accountability Office released a report in February 2013 titled Sustained and Coordinated Efforts Could Facilitate Data Sharing While Protecting Privacy, which reviews data-sharing practices by several states and localities, the challenges they face in sharing data and protecting privacy, and areas where the federal goverment could help mitigate these challenges.

 4. The data source is a mess.

Since administrative data files are created to support agency operations and reporting, they are rarely organized for outside use and will require staff time to evaluate and process them. Expect the files to arrive with poor or no documentation, duplicate records, inconsistent coding, and contradictory fields. NNIP partners have proven that data quality improves with use, so over time, progress will be made.

  • Learn how and why the agency collects the data. This will give you the basis for deciding how much confidence to have in data elements and how to interpret findings. For example, the zoning field in the tax assessor's file might easily be out of date if zoning is not a factor in calculating a property's value and collecting taxes. Ask basic questions, such as: "Is there a codebook for the data file? Are individual records archived or overwritten? How complete and accurate is the geographic information on the file?"
  • Define different sets of data for different audiences. Every field in the data does not need to be presented to the public. Our Providence partner created two levels of access for their online property database - one screen for the public that included fields in which they has full confidence and a second password-protected area for community development staff with variables that were potentially valuable, but were inconsistently coded or often missing. The advanced users were made aware of the possible problems with the less reliable fields and could then be more cautious about interpreting them.
  • Provide the agency with feedback. Local government staff may only use individual records or certain fields for operations, and not have the need to evaluate their data in its entirety. Sharing your diagnostic results with them can at minimum ensure open lines of communication, and at best, prompt measures to improve the data quality.


 5. Our agency is making money from selling the data.

Many government agencies sell their local data to third-party vendors, who then package and re-sell the information to commercial customers. This is most common for property data, such as deeds or sales records.

  • Show savings possible by wider release of the data. Lack of good information for government and nonprofit programs and initiatives area is probably costing the governments far more money than they are making through the selling their data. While hard to quantify, concrete examples may help. For example, if a city releases tax lien data, neighborhood organizations can monitor a home behind on taxes and report minor problems before the city has to step in to resolve major code violations. Locating a teen pregnancy center in an area where the problem is not the most serious not only deprives the teens who need the services in their neighborhood, but wastes the government's money operating the under-utilized office.
  • Recruit outside agency staff or politicians to help. Arguing against selling data is difficult because the city agencies receiving the income may not be the ones that will directly benefit from the savings data sharing will bring. It may help to involve mayor's offices or city council representatives to make the arguments on your behalf. Changing the agency policy may require a mayor taking a stand on supporting open data or even new legislation prohibiting the commercial selling of the data.


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