The authors of this guide, as well as the airports and collaborators who engaged in the case studies, have gleaned many best practices over the development of this guide. Lessons are learned and opportunities for improvement are discovered during each project an organization undertakes. As part of a continuous improvement process, documenting best practices helps the organization record problems that occurred in the spirit of avoiding the same problems in the future. This appendix details many of the best practices discussed as a part of the research that went into creating this guide (Table E-1).
Table E-1. Best practices.
| Category | Best Practice |
|---|---|
| Accountability | Ensure the quality control team from your organization has proper time to review contractor or consultant as-built deliverables and that they have the authority to reject and hold the consultant or contractor responsible for updates. |
| Asset Management | Change the focus of the organization to think about the asset versus thinking about the systems that manage the project, improve both data quality and the data governance process. |
| Asset Management | Develop an asset registry that defines what features should be considered an “asset.” The features defined as assets may change per airport because different airports have a different prioritization of some features. |
| Asset Management | Only define those features as an “asset” within the asset registry if you can maintain the data set for that asset and keep them current. |
| Asset Management | Develop a standard for asset naming and identification. Having a naming convention helps streamline hand-off across project phases. It also assists in managing the data across multiple platforms. |
| Change Management | Provide access to a form for geospatial data users to make change requests to standards and policy items that they feel need revision. This ensures user buy-in to the data governance program and facilitates the review change requests. |
| Contract Language | Align contract language to ensure a construction project’s necessary data is delivered in a compliant, as-built format across all organizational documents (i.e., specification documents, standards, etc.). |
| Data Champion(s) | A few key individuals who recognize the value of data and proactively promote this information to executive leadership can make a large difference in the success of a data governance program. |
| Data Exchange | Ensure the needs of all users are accounted for across platforms. Data will often be exchanged between platforms, such as CAD and GIS, but an organization needs to not lose data (e.g., attribution) when moving into CAD. A well-thought-out process on what data resides in which platform and any ETL processes ensures asset metadata, attribution, or other components of information are not lost in a data exchange. |
| Data Owner | Assigning an asset owner to each feature allows that owner to manage the data and break down departmental silos for those that need the data. This ownership can lead to the development of a centralized data resource or “the single source of truth” for that asset. |
| Category | Best Practice |
|---|---|
| Data Sharing | Data needs to be shared among departments to meet individual sector needs and prevent separate and disparate data sets from containing the same features. |
| Digital Twin | Successful operation of a digital twin is impossible without a rigorous data dictionary that includes a defined data maintenance process. |
| Education | Incorporating data governance education into curriculums that teach engineering, construction, and architectural programs could help shift an organization’s mindset regarding data governance. |
| Education | There are many ways to define terms (such as asset management, digital twin, data governance, etc.). These expressions may be defined within the data governance policy and shared to ensure collaborators understand what these terms mean to the organization. |
| Empowerment | Once responsibilities are assigned, ensuring team members feel they can speak up if something is not working (or could be improved) is imperative. For example, lack of push-back when contractors do not provide as-builts may stem from an individual feeling they were not authorized to say the data provided is unacceptable and/or they lacked authority to “kick back” data until the as-built was compliant. |
| Institutional Knowledge | During COVID-19, airports lost a lot of staff and, in turn, a lot of institutional knowledge from some of the senior staff members. Codify as much of this data now from your senior staff into digital information to ensure this data is not lost. |
| Organizational Alignment | Establish executive leadership buy-in for the data governance program. Calculate the estimated ROI for your airport using the tools from this guide. Share examples of how other airports within the case studies have benefited by starting to develop a data governance program on geospatial data. |
| Organizational Alignment | Data governance does not happen by accident—it must be a purposeful action championed by a true data governance advocate or council. These individuals or entities should have well-defined roles and responsibilities and the authority to act when necessary. |
| Organizational Alignment | Utilize your IT department. They touch every department within the organization and can often act as a facilitator for helping data management and governance. IT can also help facilitate any security restrictions necessary on SSI assets. |
| Performance | Establish goals and track the organization’s progress toward achieving these goals. Perform annual roadmap updates to track goal achievement and performance. |
| Pilot Areas | If a contractor or consultant has not previously delivered data to the organization’s standards, ask them to complete a pilot area prior to providing an entire data set. This gradual delivery can help ensure standards will be met long before there is a schedule push to close out a grant and pay the contractor/consultant. These test beds also ensure geospatial data integrity is met through one last round of QC before introduction into live environments. |
| Policy | Develop a geospatial data governance policy that clearly identifies the mission and vision of the organization in relation to data governance. The policy should include data collection, sharing, access, security, and integration processes. |
| Proactive Outreach | Departments that have implemented a data governance program and can attest to the advantages and capabilities of data governance can be an example for the rest of the organization. This outreach elicits a positive response overall on the program and incorporates buy-in from other departments. |
| Proactive Outreach | Do not be afraid to reach out to/visit neighboring airports to see their successes or struggles. The establishment of a data governance committee among airports that meets quarterly to share successes and challenges could be of great benefit. Many organizations spoke of successful BIM technologies meetings that occurred among several airports. |
| Proactive Outreach | Proactively reach out to departments not using the organization’s data to understand the lack of usage and how to get them involved. |
| Procedures | Develop SOP for the business processes to update each asset or group of assets. |
| Regulation | Encourage an industry-wide recognition of data governance and management ROI. |
| Regulation | Incorporate data governance compliance language or, at a minimum, language to follow the organization’s data standards into each project. |
| Category | Best Practice |
|---|---|
| Roadmaps | Develop a data governance roadmap that meets the needs of the organization. Data governance is not a race; many organizations have been working for 5 to 10 years and are still modifying, adapting, and updating their processes. |
| Roadmaps | Roadmaps are not static documents—do not be afraid to update them. The documents should be reviewed periodically by the geospatial data governance council and the executive team to ensure they still align with the organizations vision and mission. |
| Roles and Responsibilities | Define clear roles for each key collaborator in the organization and assign responsibilities to those roles. The use of a RACI chart may help more clearly define the roles and responsibilities and assist with the accountability of those roles. |
| Simplicity | Sometimes, the simplest answer is a perfect starting point. Data governance can become overcomplicated by a flurry of initial efforts. One small, simple step can kick-start geospatial data governance or restart a stalled initiative. Simple concepts are often easier to change and will facilitate further growth. |
| Small Wins | Data governance is a multiyear journey; however, progress can be made with small wins such as hiring or assigning a geospatial data curator, establishing a policy, writing CAD, GIS, and BIM standards. All of these successes will integrate into and enhance the overarching geospatial data governance program. |
| Small Wins | Start with processes that are essential to the daily operations of the airport to illustrate the value of the data to executive leadership. Essential processes may include 911 emergency response, security monitoring, facilities/maintenance, Part 139 inspection and reporting, billing, and space planning systems. |
| Standards | Take advantage of existing data standards. The data schema from FAA AC 150/56300-18B, National CAD Standards, National BIM Standards, Esri’s available geodatabases, and COBie standards can be of significant benefit. |
| Standards | Standards are not static; therefore, department leads or geospatial data owners should meet regularly to discuss standards, the addition/subtraction of features, or updates needed to satisfy requests made by geospatial data users. |
| Standards | Ensure data standards contain required metadata and attributions for each asset. |
| Utilities | Utility data has been a major issue for many airports. Utility strikes can cause significant construction delays and could potentially cause personal harm or loss of life. Consider requiring the location of all utilities before they are covered and/or buried underground. Field verification would provide the highest level of accuracy. Plan information would only provide a generalized vicinity. |
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Abbreviations and acronyms used without definitions in TRB publications:
| A4A | Airlines for America |
| AAAE | American Association of Airport Executives |
| AASHO | American Association of State Highway Officials |
| AASHTO | American Association of State Highway and Transportation Officials |
| ACI–NA | Airports Council International–North America |
| ACRP | Airport Cooperative Research Program |
| ADA | Americans with Disabilities Act |
| APTA | American Public Transportation Association |
| ASCE | American Society of Civil Engineers |
| ASME | American Society of Mechanical Engineers |
| ASTM | American Society for Testing and Materials |
| ATA | American Trucking Associations |
| CTAA | Community Transportation Association of America |
| CTBSSP | Commercial Truck and Bus Safety Synthesis Program |
| DHS | Department of Homeland Security |
| DOE | Department of Energy |
| EPA | Environmental Protection Agency |
| FAA | Federal Aviation Administration |
| FAST | Fixing America’s Surface Transportation Act (2015) |
| FHWA | Federal Highway Administration |
| FMCSA | Federal Motor Carrier Safety Administration |
| FRA | Federal Railroad Administration |
| FTA | Federal Transit Administration |
| GHSA | Governors Highway Safety Association |
| HMCRP | Hazardous Materials Cooperative Research Program |
| IEEE | Institute of Electrical and Electronics Engineers |
| ISTEA | Intermodal Surface Transportation Efficiency Act of 1991 |
| ITE | Institute of Transportation Engineers |
| MAP-21 | Moving Ahead for Progress in the 21st Century Act (2012) |
| NASA | National Aeronautics and Space Administration |
| NASAO | National Association of State Aviation Officials |
| NCFRP | National Cooperative Freight Research Program |
| NCHRP | National Cooperative Highway Research Program |
| NHTSA | National Highway Traffic Safety Administration |
| NTSB | National Transportation Safety Board |
| PHMSA | Pipeline and Hazardous Materials Safety Administration |
| RITA | Research and Innovative Technology Administration |
| SAE | Society of Automotive Engineers |
| SAFETEA-LU | Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) |
| TCRP | Transit Cooperative Research Program |
| TEA-21 | Transportation Equity Act for the 21st Century (1998) |
| TRB | Transportation Research Board |
| TSA | Transportation Security Administration |
| U.S. DOT | United States Department of Transportation |
