Characterizing Perceived Data Sharing Barriers and Promotion Strategies in Civil Engineering
Publication: Computing in Civil Engineering 2021
ABSTRACT
Despite the proven benefits of data sharing between different stakeholders participating in civil engineering projects, a systematic classification of data sharing barriers and strategies for promoting data sharing in the civil engineering domain is missing. The Data Sensing and Analysis Committee of the American Society of Civil Engineers (ASCE DSA Committee) initiated an investigation to explore the current practices, barriers, and future vision in civil engineering data sharing. The approach is to conduct a literature review and interviews with domain experts to identify and classify data sharing barriers and strategies for promoting data sharing in the civil engineering domain. An online survey then follows, asking the participants having different job functions in various organizations (e.g., for-profit corporations, academic institutions) to prioritize five categories of barriers and three categories of promotion strategies summarized by the authors. The survey results show that: (1) most responders regard data sharing policy and data standard regulation as urgent needs; (2) different stakeholders prefer different promotion strategies due to they face different aspects of the data-sharing problem encountered; and (3) non-academic stakeholders hardly perceive the value of incentives for data-sharing research. The synthesis of these findings can guide the systematic design of three road maps that help advance healthy data-sharing systems in civil engineering: (1) policy road map, (2) technology road map, and (3) business road map.
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REFERENCES
Agarwal, R., and Dhar, V. (2014). Big data, data science, and analytics: The opportunity and challenge for IS research. INFORMS.
Anderson, C. (2015). Creating a data-driven organization: Practical advice from the trenches, O’Reilly Media, Inc.
Attard, J., Orlandi, F., Scerri, S., and Auer, S. (2015). “A systematic review of open government data initiatives.” Government Information Quarterly, 32(4), 399–418.
Balaji, B. (2018). “Zodiac Dataset.” <https://www.synergylabs.org/bharath/datasets.html>. (2018).
Beaulieu-Jones, B. K., Wu, Z. S., Williams, C., Lee, R., Bhavnani, S. P., Byrd, J. B., and Greene, C. S. (2019). “Privacy-preserving generative deep neural networks support clinical data sharing.” Circulation: Cardiovascular Quality and Outcomes, 12(7), e005122.
Becker, T., Curry, E., Jentzsch, A., and Palmetshofer, W. (2016). “New Horizons for a Data-Driven Economy: Roadmaps and Action Plans for Technology, Businesses, Policy, and Society.”
Bradley, A., Li, H., Lark, R., and Dunn, S. (2016). “BIM for infrastructure: An overall review and constructor perspective.” Automation in Construction, 71, 139–152.
Dikeocha, L. U., Nwaiwu, B. N., Nwagu, C. C., and Amaechi, L. (2018). “Promoting small scale business: Road map for a rapid national development.” Nigerian Journal of Business Education (NIGJBED), 5(2), 132–140.
DOE, U. S. D. o. E. (2014). “Public Access Plan.” <https://www.energy.gov/sites/prod/files/2014/08/f18/DOE_Public_Access%20Plan_FINAL.pdf>. (2018).
DOE, U. S. D. o. E. (2018). “Privacy.” <https://www.energy.gov/about-us/web-policies/privacy>. (2018).
Dyke, S. O., and Hubbard, T. J. (2011). “Developing and implementing an institute-wide data sharing policy.” Genome medicine, 3(9), 1–8.
Economist-Intelligence-Unit. (2012). The Deciding Factor: Big Data & Decision Making.
EUROPA. (2016). “EU Regulation for Data Protection.” <https://eur-lex.europa.eu/eli/reg/2016/679/2016-05-04>. (2019).
Google. (2020). “Google Search Trends.” <https://trends.google.com/trends/>. (2020).
Guo, F., Jahren, C. T., Turkan, Y., and David Jeong, H. (2017). “Civil integrated management: An emerging paradigm for civil infrastructure project delivery and management.” Journal of Management in Engineering, 33(2), 04016044.
Halfawy, M. R. (2008). “Integration of municipal infrastructure asset management processes: challenges and solutions.” Journal of Computing in Civil Engineering, 22(3), 216–229.
Halfawy, M. R. (2010). “Municipal information models and federated software architecture for implementing integrated infrastructure management environments.” Automation in Construction, 19(4), 433–446.
Janssen, M., van der Voort, H., and Wahyudi, A. (2017). “Factors influencing big data decision-making quality.” Journal of Business Research, 70, 338–345.
Le, T., and David Jeong, H. (2017). “NLP-based approach to semantic classification of heterogeneous transportation asset data terminology.” Journal of Computing in Civil Engineering, 31(6), 04017057.
Lee, H.-K., Liu, C.-M., and Lee, M.-H. (2006). “Aligning the Business Roadmap to Technology Roadmap for Managing the New Product Development Project.” Journal of the Chinese Institute of Industrial Engineers, 23(6), 449–457.
Müller, O., Fay, M., and Vom Brocke, J. (2018). “The effect of big data and analytics on firm performance: An econometric analysis considering industry characteristics.” Journal of Management Information Systems, 35(2), 488–509.
Ng, S. T., Xu, F. J., Yang, Y., and Lu, M. (2017). “A master data management solution to unlock the value of big infrastructure data for smart, sustainable and resilient city planning.” Procedia engineering, 196, 939–947.
Nguyen, V. M., Brooks, J. L., Young, N., Lennox, R. J., Haddaway, N., Whoriskey, F. G., Harcourt, R., and Cooke, S. J. (2017). “To share or not to share in the emerging era of big data: perspectives from fish telemetry researchers on data sharing.” Canadian Journal of Fisheries and Aquatic Sciences, 74(8), 1260–1274.
Olszak, C. M. (2016). “Toward better understanding and use of Business Intelligence in organizations.” Information Systems Management, 33(2), 105–123.
Pryor, G. (2009). “Multi-scale data sharing in the life sciences: some lessons for policy makers.” International Journal of Digital Curation, 4(3), 71–82.
Rathje, E. M., Dawson, C., Padgett, J. E., Pinelli, J.-P., Stanzione, D., Adair, A., Arduino, P., Brandenberg, S. J., Cockerill, T., and Dey, C. (2017). “DesignSafe: new cyberinfrastructure for natural hazards engineering.” Natural Hazards Review, 18(3), 06017001.
Sangogboye, F. C., Jia, R., Hong, T., Spanos, C., and Kjærgaard, M. B. (2018). “A framework for privacy-preserving data publishing with enhanced utility for cyber-physical systems.” ACM Transactions on Sensor Networks (TOSN), 14(3-4), 1–22.
Sivarajah, U., Kamal, M. M., Irani, Z., and Weerakkody, V. (2017). “Critical analysis of Big Data challenges and analytical methods.” Journal of Business Research, 70, 263–286.
Wall, B., Jagdev, H., and Browne, J. (2005). “An approach to developing an eBusiness roadmap.” Production planning & control, 16(7), 701–715.
Wang, H., Xu, Z., Fujita, H., and Liu, S. (2016). “Towards felicitous decision making: An overview on challenges and trends of Big Data.” Information Sciences, 367, 747–765.
Zakaib, G. (2019). “Alberta Nonprofit Data Strategy Roadmap.” <https://static1.squarespace.com/static/5aef5b46cef3728571e6c46c/t/5c745650eb393140a620215e/1551128147129/ANDS+Roadmap+-+February+2019.pdf>. (2019).
Zuiden, B. V. (2019). “Universal Data Sharing Agreement.” <https://github.com/Clever/policies/blob/master/universal-data-sharing-agreement.md#universal-data-sharing-agreement>. (2019).
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Computing in Civil Engineering 2021
Pages: 42 - 49
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Published online: May 24, 2022
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