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

Last Updated: September 14, 2018

After getting organizedyou have a solid foundation to begin the dialogue with data owners. The reasons below are the most common ones NNIP partners encounter when officials decline their requests for data. 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 our 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 are a mess."
     
  5. "Our agency is making money from selling the data."

 

And Why They Should Say Yes

 

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

One of the most common reasons data providers say no does not relate to a legal or political issue, but to a practical one. Staff members are pressed with work for core agency operations and reluctant to prepare datasets and documentation for external users. Given fixed local government infrastructure, there is likely no way to eliminate the extra work for the staff, but you can articulate benefits to demonstrate the value of data sharing that justify the costs.

  • Offer additional analysis useful to the agency's work. Agency staff might lack the time or expertise for analyzing 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. For  example, in exchange for a file of the locations of homeless prevention payments by the District of Columbia, Greater-Urban DC provided the local homeless coordination agency geocoded files and 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 school districts forecast enrollment, but planning and health departments might feel more comfortable sharing the data with a third party rather than directly, either for legal or political reasons. Even if the data sharing among agencies is possible, the school analysts could prefer to receive aggregate, clean data rather than doing the cleaning and analysis themselves.
  • Save the agency time by answering community inquiries. Local agencies might already 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. The Baltimore Neighborhood Indicators Alliance publishes its aggregate indicators on the city’s open data portal, making the data available for residents and city officials alike.
  • 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 assistance in basic data use perhaps through examples of other data analysis you have done.
  • Offer to share back documentation of the files.  Often local administrative data will not come with documentation of the contents or quality, so you can share back data dictionaries or diagnostics with the agencies. Agencies can use the documentation for sharing the data with other organizations in the future and might be interested in improving their data quality.

 

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

Beyond lacking  time to fulfill a data request, an agency can 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. Examples from other cities can illustrate the advantages of having neighborhood-level data available to inform decisions by commercial firms, non-profit organizations, and other community actors (see Stories for case studies).
  • Provide disclaimers to protect the agency, or provide credit to reward them. Depending on the circumstances, agency staff might want to distance the agency from politically sensitive analysis or protect themselves from liability for any data errors. This can be accomplished by a standard disclaimer on reports using the data or a blanket disclaimer clause in the data-sharing agreement (see discussion in the next section). On the flip side, agency leaders and staff might want credit for supporting community use of information, and acknowledging data providers or cohosting online reports will highlight their progressive actions.
  • Try peer pressure. Examples of other local agencies in your area, or similar agencies from other areas, that have shared their data can help convince reluctant agencies. NNIP partners have found that they can shift the culture so that data sharing is the expectation, not the exception. Outside your community, you can point out that other cities have community information systems that give them a competitive advantage in fundraising and more effective data-driven nonprofit and government programs.
  • Offer them advance notice of upcoming analysis. In some instances, NNIP partners have agreed to let the agency review the analysis before publication. An agency can confirm that the findings make sense or add any cautions about interpretations, but it should not have veto power over releasing the 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 NNIP partners receive are sensitive and confidential, such as individual records about public school enrollment, food stamp receipt, or births and deaths. State or federal law, as HIPPA for health data or FERPA for education data, may regulate the release of the data.

  • Develop and practice secure procedures for handling confidential data.  Organizations should develop a data governance plan that includes security policies and procedures to assure officials you are equipped to handle the data responsibly. These policies 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. Chapter 3 of NNIP’s Resource Guide to Data Governance and Security provides resources on how to create your plan.  You can also view the sample data security plan from Urban–Greater DC.
  • Develop a formal, written agreement to share the data. It is best practice to develop a memorandum of understanding (MOU), a written agreement to govern the transfer, use, and disposition of a data set. An MOU will specify any restrictions on the release of analysis or data files and ensure both parties  understand the conditions. Chapter 4 of NNIP’s Resource Guide to Data Governance and Security provides resources for creating data sharing agreements and you can learn about key elements of a 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 data.

 

 4. The data are a mess.

Because 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 over time.

  • 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 a 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 these: Is there a codebook for the data file? Are individual records archived or overwritten? How complete and accurate is the file's geographic information?
  • Define different 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 had full confidence and a password-protected second area for community development staff with variables that were potentially valuable, but were inconsistently coded or had missing values. 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 feedback. Local government staff might only use individual records or certain fields for operations, and not need to evaluate the data in their entirety. Sharing your diagnostic results with them can, at minimum, ensure open lines of communication, and at best, prompt measures to improve 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 resell the information to commercial customers. This is most common for property data, such as deeds or sales records. Over the long term, organizations should advocate for policy change and for governments to stop selling the data to follow the principles of open data and support evidence-based decisionmaking. In the short term, organizations might settle for having access to the data for themselves, with permission to publish aggregated indicators or analysis of the data.

  • Show savings possible by wider release of the data. Lack of high-quality information for government and nonprofit programs and area initiatives is probably costing governments more than they are making from selling their data. Although hard to quantify, concrete examples can help. 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 code violations. Placing a teen pregnancy center in an area where the problem is not serious deprives the teens who need the services in their neighborhood and wastes government money operating an underused office.
  • Recruit external agency staff or politicians to help. Arguing against selling data is difficult because the city agencies receiving the income might not be the ones that will benefit from the savings data sharing will bring. Mayor’s offices or city council representatives could make the arguments on your behalf. Changing the agency policy might require a mayor supporting open data or new legislation prohibiting the commercial sale of data.

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