400
Lant, C., et al. (2019). The U.S. food–energy–water system: A blueprint to fill the meso-scale gap
for science and decision-making. Ambio, 48, 251–263.
Maupin, M. A., Kenny, J. F., Hutson, S. S., Lovelace, J. K., Barber, N. L., & Linsey, K. S. 2014.
Estimated use of water in the United States in 2010 (56p.). U.S. Geological Survey Circular
1405. https://doi.org/10.3133/cir1405
Miller, R. E., & Blair, P. D. (2009). Input-output analysis: Foundations and extensions. Cambridge:
Cambridge University Press.
NASS. (2015). Agricultural statistics 2015. Washington DC: U.S. Department of Agriculture
National Agricultural Statistics Service (NASS), U.S. Government Printing Office.
OMB. (2017). North American industry classification system United States 2017 (NAICS).
Executive Office of the President Office of Management and Budget (OMB). Retrieved April
28, 2017, from https://www.census.gov/eos/www/naics/2017NAICS/2017_NAICS_Manual.
pdf.
Privacy International. (n.d.). A guide for policy engagement on data protection. Part 3: Data protection principles. Retrieved December 4, 2018, from https://privacyinternational.org/sites/
default/files/2018-09/Part%203%20-%20Data%20Protection%20Principles.pdf.
Ruddell, B. L. (2006). Scientific metadata: Back to basics. In ICHE Conference 2006. Philadelphia,
PA: Drexel University.
Ruddell, B. L., & Kumar, P. (2006). Hydrologic data models, Chapter 5. In P. Kumar (Ed.),
Hydroinformatics: Data integrative approaches in computation, analysis, and modeling. Boca
Raton, FL: CRC Press.
Ruddell, B. L., & Kumar, P. (2009). Ecohydrologic process networks: 1. Identification. Water
Resources Research, 45, W03419. https://doi.org/10.1029/2008WR007279.
Ruddell, B. L., Zaslavsky, I., Valentine, D., Beran, B., Piasecki, M., Fu, Q., & Kumar, P. (2014).
Sustainable long term scientific data publication: Lessons learned from a prototype Observatory
Information System for the Illinois River basin. Environmental Modelling & Software, 54,
73–87. https://doi.org/10.1016/j.envsoft.2013.12.015.
Wilkinson, M. D., et al. (2016). The FAIR guiding principles for scientific data management and
stewardship. Scientific Data, 3, 160018. https://www.go-fair.org/fair-principles/.
Further Reading
Best Practices for Data Management. (n.d.). DataOne. Retrieved December 4, 2018, from https://
www.dataone.org/best-practices.
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural,
technological, and scholarly phenomenon. Information, Communication & Society, 15(5),
662–679.
COPDESS. (n.d.). Enabling FAIR data FAQs. Retrieved December 4, 2018, from http://www.
copdess.org/enabling-fair-data-project/enabling-fair-data-faqs/.
Data Best Practices. (n.d.). Stanford libraries. Retrieved December 4, 2018, from https://library.
stanford.edu/research/data-management-services/data-best-practices.
Data Life Cycle. (n.d.). DataOne. Retrieved December 4, 2018, from https://www.dataone.org/
data-life-cycle.
DHS. (n.d.). Protected Critical Infrastructure Information (PCII) Program. Retrieved December
4, 2018, from https://www.dhs.gov/pcii-program.
Dwork, C. (2008). Differential privacy: A survey of results. In International Conference on Theory
and Applications of Models of Computation. Berlin: Springer.
Floridi, L., & Taddeo, M. (2016). What is data ethics? Philosophical Transactions of the Royal
Society A, 374, 20160360.
B. L. Ruddell
Lant, C., et al. (2019). The U.S. food–energy–water system: A blueprint to fill the meso-scale gap
for science and decision-making. Ambio, 48, 251–263.
Maupin, M. A., Kenny, J. F., Hutson, S. S., Lovelace, J. K., Barber, N. L., & Linsey, K. S. 2014.
Estimated use of water in the United States in 2010 (56p.). U.S. Geological Survey Circular
1405. https://doi.org/10.3133/cir1405
Miller, R. E., & Blair, P. D. (2009). Input-output analysis: Foundations and extensions. Cambridge:
Cambridge University Press.
NASS. (2015). Agricultural statistics 2015. Washington DC: U.S. Department of Agriculture
National Agricultural Statistics Service (NASS), U.S. Government Printing Office.
OMB. (2017). North American industry classification system United States 2017 (NAICS).
Executive Office of the President Office of Management and Budget (OMB). Retrieved April
28, 2017, from https://www.census.gov/eos/www/naics/2017NAICS/2017_NAICS_Manual.
pdf.
Privacy International. (n.d.). A guide for policy engagement on data protection. Part 3: Data protection principles. Retrieved December 4, 2018, from https://privacyinternational.org/sites/
default/files/2018-09/Part%203%20-%20Data%20Protection%20Principles.pdf.
Ruddell, B. L. (2006). Scientific metadata: Back to basics. In ICHE Conference 2006. Philadelphia,
PA: Drexel University.
Ruddell, B. L., & Kumar, P. (2006). Hydrologic data models, Chapter 5. In P. Kumar (Ed.),
Hydroinformatics: Data integrative approaches in computation, analysis, and modeling. Boca
Raton, FL: CRC Press.
Ruddell, B. L., & Kumar, P. (2009). Ecohydrologic process networks: 1. Identification. Water
Resources Research, 45, W03419. https://doi.org/10.1029/2008WR007279.
Ruddell, B. L., Zaslavsky, I., Valentine, D., Beran, B., Piasecki, M., Fu, Q., & Kumar, P. (2014).
Sustainable long term scientific data publication: Lessons learned from a prototype Observatory
Information System for the Illinois River basin. Environmental Modelling & Software, 54,
73–87. https://doi.org/10.1016/j.envsoft.2013.12.015.
Wilkinson, M. D., et al. (2016). The FAIR guiding principles for scientific data management and
stewardship. Scientific Data, 3, 160018. https://www.go-fair.org/fair-principles/.
Further Reading
Best Practices for Data Management. (n.d.). DataOne. Retrieved December 4, 2018, from https://
www.dataone.org/best-practices.
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural,
technological, and scholarly phenomenon. Information, Communication & Society, 15(5),
662–679.
COPDESS. (n.d.). Enabling FAIR data FAQs. Retrieved December 4, 2018, from http://www.
copdess.org/enabling-fair-data-project/enabling-fair-data-faqs/.
Data Best Practices. (n.d.). Stanford libraries. Retrieved December 4, 2018, from https://library.
stanford.edu/research/data-management-services/data-best-practices.
Data Life Cycle. (n.d.). DataOne. Retrieved December 4, 2018, from https://www.dataone.org/
data-life-cycle.
DHS. (n.d.). Protected Critical Infrastructure Information (PCII) Program. Retrieved December
4, 2018, from https://www.dhs.gov/pcii-program.
Dwork, C. (2008). Differential privacy: A survey of results. In International Conference on Theory
and Applications of Models of Computation. Berlin: Springer.
Floridi, L., & Taddeo, M. (2016). What is data ethics? Philosophical Transactions of the Royal
Society A, 374, 20160360.
B. L. Ruddell