C+S December 2020 Vol. 6 Issue 12 (web)

cations, site monitoring, etc.) and consistent UAS technology specifi- cations for distinct project activities. This ensures sufficient geospatial data quality and integrity. Project leaders should build and incorporate open data model and exchange standards to maximize interoperability and integration between proprietary systems. Also, adopt or create digital-enabled standard practices for key project activities that require repeatability and predictability. Data-Driven Decision Support Systems The power of effective decision-making is fueled by accurate and reliable data organized and delivered through appropriate mediums. Achieving clarity and meaning from the available data requires a keen focus on geospatial data quality and integrity management. En- gineers use a variety of tools and systems to make design decisions and compile their design intent into CAD models for construction plan development. Limited interoperability between these tools and systems combined with an incremental data flow discourages engagement, col- laboration, and innovation. Incorporating more innovative and iterative processes with early en- gagement of key disciplines brings the right data at the right time to inform the right decisions. This allows engineers to spend less time on data cleansing and manipulation, which will achieve more effec- tive project delivery. Removing the subjectivity of decision making by integrating and exploiting accurate data improves the quality and reliability of important decisions. UAS technology is rapidly transforming how video and imagery data is being used for decision-making. Bridge inspectors are relying heavily on its ability to collect high resolution data of key bridge components at close range instead of renting snooper trucks, using rope access, etc. The improved safety and cost savings combined with rapid deploy- ment and data access, illustrates how integral UAS has become to decision workflows. Cybersecurity risks notwithstanding, the ability to stream actionable video data from UAS platforms to decision makers in other remote locations enables near real-time situational awareness for emergency or crisis situations. To effectively harness this technology and improve decision-making, project leaders need to expose accurate and reliable (as determined by data stewards) data to decision support systems (e.g. CAD, design visu- alization, dashboards, business intelligence, etc.) to enable simplified fit- for-purpose integration of geospatial data. This ensures geospatial data is used properly and propagates benefits throughout project delivery.

Digital Enablers Focused on Data Quality and Integrity Im- prove Project Delivery The engineering and construction industry is on the cusp of a digital transformation with asset owners and project leaders in a unique posi- tion to influence and drive this industry shift by adopting a robust digital ecosystem comprised of the right frameworks, technologies, processes, and workflows. Cultivating this digital ecosystem on projects using specific data quality and integrity enablers can be achieved through incremental (or transformational) changes including more effective geospatial data governance, deliberate data risk management, integra- tion of suitable technologies, application of standards, and enrichment of data-driven decision support systems. Figure 3. Suitability criteria for location-enabled technologies. Source: US Federal Highway Administration

JON GUSTAFSON PS, CFEDS, PMP, GISP, is a Senior Principal and the Geospatial Services Leader for the U.S. East region at Stantec Consulting Services. CLINT JOHNSON is the Sector Leader for Geospatial Services in Canada at Stantec Consulting Services.


december 2020


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