Difference between revisions of "IQ Papers"

From Federation of Earth Science Information Partners
(add papers published in early 2021)
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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.
 
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.
* Ramapriyan, H K, Peng G, Moroni D, Shie C-L, Ensuring and Improving Information Quality for Earth Science Data and Products. ''D-Lib Magazine'', 23 (7/8), July/August 2017, DOI:https://doi.org/10.1045/july2017-ramapriyan
+
 
* 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
+
*Peng, G., Downs, R.R., Lacagnina, C., Ramapriyan, H., Ivánová, I., Moroni, D., Wei, Y., Larnicol, G., Wyborn, L., Goldberg, M., Schulz, J., Bastrakova, I., Ganske, A., Bastin, L., Khalsa, S.J.S., Wu, M., Shie, C.-L., Ritchey, N., Jones, D., Habermann, T., Lief, C., Maggio, I., Albani, M., Stall, S., Zhou, L., Drévillon, M., Champion, S., Hou, C.S., Doblas-Reyes, F., Lehnert, K., Robinson, E. and Bugbee, K., 2021. Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets. Data Science Journal, 20(1), p.19. DOI: http://doi.org/10.5334/dsj-2021-019
* 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
+
*Downs, R.R., Ramapriyan, H.K., Peng, G., Wei, Y., 2021. Perspectives on Citizen Science Data Quality. Perspective, Frontiers in Climate, Section on Climate Risk Management, Special Issue: Open Citizen Science Data and Methods. 3:615032. https://doi.org/10.3389/fclim.2021.615032
* 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.
+
*Ramapriyan, H K, Peng G, Moroni D, Shie C-L, Ensuring and Improving Information Quality for Earth Science Data and Products. ''D-Lib Magazine'', 23 (7/8), July/August 2017, DOI:https://doi.org/10.1045/july2017-ramapriyan
* 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]]
+
*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
* 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:[http://dlib.org/dlib/may16/peng/05peng.html 10.1045/may2016-peng]
+
*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
* 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.
+
*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.
* 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
+
*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]]
* 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
+
*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:[http://dlib.org/dlib/may16/peng/05peng.html 10.1045/may2016-peng]
* 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.
+
*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.
* 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.
+
*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
* 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.  
+
*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
* 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.
+
*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.
* 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
+
*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.
* 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
+
*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.
* Lee, Y W et al. 2002: AIMQ: a methodology for information quality assessment, ''Information & Management'', 40, 133-146. DOI:http://doi.org/10.1016/S0378-7206(02)00043-5
+
*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.
* Miller, H. 1996, The Multiple Dimensions of Information Quality. ''Information Systems Management''. 13(2):79. doi: http://dx.doi.org/10.1080/10580539608906992
+
*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
* 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
+
*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. DOI:http://doi.org/10.1016/S0378-7206(02)00043-5
 +
*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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Return to [[Information Quality]]
 
Return to [[Information Quality]]

Revision as of 16:45, May 5, 2021

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.

  • Peng, G., Downs, R.R., Lacagnina, C., Ramapriyan, H., Ivánová, I., Moroni, D., Wei, Y., Larnicol, G., Wyborn, L., Goldberg, M., Schulz, J., Bastrakova, I., Ganske, A., Bastin, L., Khalsa, S.J.S., Wu, M., Shie, C.-L., Ritchey, N., Jones, D., Habermann, T., Lief, C., Maggio, I., Albani, M., Stall, S., Zhou, L., Drévillon, M., Champion, S., Hou, C.S., Doblas-Reyes, F., Lehnert, K., Robinson, E. and Bugbee, K., 2021. Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets. Data Science Journal, 20(1), p.19. DOI: http://doi.org/10.5334/dsj-2021-019
  • Downs, R.R., Ramapriyan, H.K., Peng, G., Wei, Y., 2021. Perspectives on Citizen Science Data Quality. Perspective, Frontiers in Climate, Section on Climate Risk Management, Special Issue: Open Citizen Science Data and Methods. 3:615032. https://doi.org/10.3389/fclim.2021.615032
  • Ramapriyan, H K, Peng G, Moroni D, Shie C-L, Ensuring and Improving Information Quality for Earth Science Data and Products. D-Lib Magazine, 23 (7/8), July/August 2017, DOI:https://doi.org/10.1045/july2017-ramapriyan
  • 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. DOI:http://doi.org/10.1016/S0378-7206(02)00043-5
  • 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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