IQ Papers
From Earth Science Information Partners (ESIP)
Revision as of 17:07, May 4, 2017 by Ramapriyan (talk | contribs)
This section lists selected papers from the literature - published by IQC members as well as others addressing information quality. They are shown in reverse chronological order.
- Labouseur, A G and Matheus, C C 2017 An introduction to dynamic data quality challenges. ACM Journal of Data and Information Quality (JDIQ), 8(2), January 2017. DOI:http://dx.doi.org/10.1145/2998575
- Shankaranarayanan G and Blake R 2017 From content to context: The evolution and growth of data quality research. Journal of Data and Information Quality (JDIQ) 8(2), January 2017. DOI: http://doi.org/10.1145/2996198
- Neumaier S, Umbrich J and Polleres S 2016 Automated quality assessment of metadata across open data portals. ACM Journal of Data and Information Quality (JDIQ), 8(1), October 2016, DOI: http://doi.org/10.1145/2964909.
- Hampapuram Ramapriyan, Ge Peng, David Moroni, Chung-Lin Shie, Ensuring and Improving Information Quality for Earth Science Data and Products – Role of the ESIP Information Quality Cluster, SciDataCon 2016, Denver, CO, September 11-13, 2016. File:SciDataCon 2016 on ESIP Information Quality Cluster.docx
- Peng, G., Ritchey, N. A., Casey, K. S., Kearns, E. J., Privette, J. L., Saunders, D., Jones, P., Maycock, T., & Ansari, S. (2016). Scientific stewardship in the open data and big data era — Roles and responsibilities of stewards and other major product stakeholders. D-Lib Magazine, 22(5/6). doi:10.1045/may2016-peng
- Peng G et al. 2015 A unified framework for measuring stewardship practices applied to digital environmental datasets, Data Science Journal, 13:231, DOI: http://doi.org/10.2481/dsj.14-049.
- Schneider D P et al. 2013, Climate Data Guide Spurs Discovery and Understanding, Eos Trans. AGU, 94(13):121. DOI: http://doi.org/10.1002/2013EO130001
- Bates, J J and Privette, J L 2012 A maturity model for assessing the completeness of climate data records, EOS, Transactions of the AGU, 93 (44):441, DOI:http://doi.org/10.1029/2012EO440006
- Embury, Suzanne M, Paolo Missier, Sandra Sampaio, and R Mark Greenwood. “Incorporating Domain-Specific Information Quality Constraints into Database Queries.” Journal of Data and Information Quality (JDIQ) 1, no. 2 (2009): 1-31. DOI:http://doi.org/10.1145/1577840.1577846.
- Klein, A and Lehner, W 2009 Representing Data Quality in Sensor Data Streaming Environments, ACM Journal of Data and Information Quality (JDIQ), 1(2), September 2009. DOI:http://doi.org/10.1145/1577840.1577845.
- Li X 2009 A Bayesian Approach for Estimating and Replacing Missing Categorical Data, ACM Journal of Data and Information Quality (JDIQ), 1(1), June 2009. DOI: http://dx.doi.org/10.1145/1515693.1515695.
- Madnick S E et al. 2009 Overview and framework for data and information quality research. ACM Journal of Data and Information Quality (JDIQ), 8(1), June 2009. DOI: http://dx.doi.org/10.1145/1515693.1516680.
- Weber K, Otto B and Osterle H et al. 2009. One Size Does Not Fit All---A Contingency Approach to Data Governance, Journal of Data and Information Quality (JDIQ), 1(1), June 2009. DOI: http://doi.org/10.1145/1515693.1515696
- Preece, A., Missier, P., Embury, S., Jin, B., and Greenwood, M. (2008). An ontology-based approach to handling information quality in e-Science. Concurrency and Computation: Practice and Experience 20, 3, 253-264. DOI=10.1002/cpe.v20:3 http://dx.doi.org/10.1002/cpe.v20:3
- Lee, Y W et al. 2002: AIMQ: a methodology for information quality assessment, Information & Management, 40, 133-146.
- Miller, H. 1996, The Multiple Dimensions of Information Quality. Information Systems Management. 13(2):79. doi: http://dx.doi.org/10.1080/10580539608906992
- Wang R Y and Strong D M 1996 Beyond accuracy: What data quality means to consumers. Journal of Management Information Systems 12(4):5. DOI: http://doi.org/10.1080/07421222.1996.11518099
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