A Conceptual Enterprise Framework for Managing Scientific Data Stewardship
References
- Arndt, DS and Brewer, M. 2016. Assessing service maturity through end user engagement and climate monitoring. 2016 ESIP summer meeting,
19–22 July 2016 . Durham, NC, USA. - Blunden, J and Arndt, DS. (eds) 2017. State of the Climate in 2016. Bull. Meteor. Soc., 98(8): S1–S277. DOI: 10.1175/2017BAMSStateoftheClimate.2
- Brewer, M, Hollingshead, A and Owen, T. 2017. User engagement and analytics. 97th American Meteorological Society Annual Meeting,
21–26 January 2017 . Seattle, Washington, USA. - CDRP (NOAA’s Climate Data Record Program). 2014. Transitioning CDRs from Research to Operations (R2O). CDRP-PLAN-0017. 48. Version 2 March 13, 2014. [Available online at:
https://www1.ncdc.noaa.gov/pub/data/sds/cdr/Guidelines/Transitioning_CDRs_from_R2O.pdf ]. - Chisholm, M. 2014. Data stewards versus Subject Matter Experts and Data Managers. Information Management. Version: May 28, 2014. [Available online at:
http://www.information-management.com/news/data-stewards-versus-subject-matter-experts-and-data-managers-10025704-1.html .]. - Chung, L. 2013.
Non-Functional Requirements: Soft is harder to deal with than hard – The Ten Commandments . Requirements Management Blog. IBM. Version: September 17, 2013. - Chung, L and do Prado Leite, JCS. 2009.
On Non-Functional Requirements in Software Engineering , 363–379. In: Borgida, AT, Chaudhri, VK, Giorgini, P and Yu, ES (eds.), Conceptual Modeling: Foundations and Applications. Lecture Notes in Computer Science, 5600. Springer, Berlin, Heidelberg. - CMMI. 2014. Data Management Maturity Model. CMMI Institute. Version: 1.0 August 2014, 248.
- Deming, WE. 1986.
Out of the Crisis . MIT Center for Advanced Engineering Study. The 2010 MIT Press edition, 507. Cambridge, MA, USA. - Faundeen, J. 2017. Developing criteria to establish trusted digital repositories. Data Science Journal, 16. DOI: 10.5334/dsj-2017-022
- FGDC (Federal Geographic Data Committee). 2002.
Content standard for digital geospatial metadata – extension for remote sensing data . Version: FGDC-STD-012-2002. Federal Geographic Data Committee. Washington, D.C. [Available online at:https://www.fgdc.gov/standards/projects/csdgm_rs_ex/MetadataRemoteSensingExtens.pdf ]. - Hills, DJ, Downs, RR, Duerr, R, Goldstein, JC, Parsons, MA and Ramapriyan, HK. 2015. The Importance of Data Set Provenance for Science. EOS, 96. DOI: 10.1029/2015EO040557
- Hu, W and Feng, J. 2005. Data and information quality: an information-theoretic perspective. Computing and Information Systems, 9: 32–47.
- Kruk, MC, Parker, B, Marra, JJ, Werner, K, Heim, R, Vose, R and Malsale, P. 2017. Engaging with users of climate information and the co-production of knowledge. Weather, Climate, and Society. DOI: 10.1175/WCAS-D-16-0127.1
- Lee, YW, Strong, DM, Kahn, BK and Wang, RY. 2002. AIMQ: a methodology for information quality assessment, Information & Management, 40: 133–146. DOI: 10.1016/S0378-7206(02)00043-5
- Melillo, JM, Richmond, TC and Yohe, GW. (eds) 2014. Climate Change Impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 841. DOI: 10.7930/J0Z31WJ2
- Mosely, M, Brackett, M, Early, S and Henderson, D. (eds) 2009. The Data Management Body of Knowledge (DAMA-DMBOK Guide). Bradley Beach, NJ, USA: Technics Publications, LLC. 2nd Print Edition, 406.
- Nayab, N and Richter, L. 2013. Exploring the users of Plan-Do-Check-Act cycles. Bright Hub Project Management. Version: 7/21/2013. [Accessed on 4/27/2017 at:
http://www.brighthubpm.com/methods-strategies/75926-exploring-the-uses-of-plan-do-check-act-pdca-cycles/ ]. - NRC. 2007.
Environmental data management at NOAA: Archiving, stewardship, and access , 130. The National Academies Press. Washington, D.C. DOI: 10.17226/12017 [Available online at:https://www.nap.edu/catalog/12017.html ]. - NRC (National Research Council). 2005.
Review of NOAA’s plan for the scientific stewardship program , 38. Washington, DC: The National Academies Press. DOI: 10.17226/11421 [Available online at:https://www.nap.edu/catalog/11421.html ]. - OMB (Office of Management and Budget). 1999. Uniform Administrative Requirements for Grants and Agreements with Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations. OMB Circular A-110.
- Patil, DJ. 2012. Data Jujitsu: The art of turning data into product. Radar. Version: 17 July 2012. [Available online at:
http://radar.oreilly.com/2012/07/data-jujitsu.html ]. - Peng, G. 2018. The state of assessing data stewardship maturity – An overview. Data Science Journal, 17. DOI: 10.5334/dsj-2018-007
- Peng, G, Lawrimore, J, Toner, V, Lief, C, Baldwin, R, Ritchey, NA, Brinegar, D and Delgreco, SA. 2016b. Assessing Stewardship Maturity of the Global Historical Climatology Network-monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned. D.-Lib Magazine, 22. DOI: 10.1045/november2016-peng
- Peng, G, Ramapriyan, H and Moroni, DF. 2016. The State of Building a Consistent Framework for Curation and Presentation of Earth Science Data Quality. Poster. ESIP 2017 winter meeting,
11–13 January 2017 . Bethesda, MD, USA. [Available online at:http://commons.esipfed.org/node/9625 ]. - Peng, G, Ritchey, NA, Casey, KS, Kearns, EJ, Privette, JL, Saunders, D, Jones, P, Maycock, T and Ansari, S. 2016a. Scientific stewardship in the Open Data and Big Data era — Roles and responsibilities of stewards and other major product stakeholders. D.-Lib Magazine, 22. DOI: 10.1045/may2016-gepeng
- Plotkin, D. 2014.
Data stewardship: an actionable guide to effective data management and data governance . Library of Congress Cataloging-in-Publication Data. Morgan Kaufmann Publishers, 223. - Poppendieck, M. 2002. Principles of lean thinking. Poppendieck L.L.C. [Available online at:
https://yourcareeracademy.com/yca/assets/uploads/lib_file/principles%20of%20LeanThinking.pdf ]. - Ramapriyan, HK, Goldstein, J, Hua, H and Wolfe, R. 2016.
Tracking and Establishing Provenance of Earth Science Datasets: A NASA-based example. Chapter in Provenance and Annotation of Data and Process , Volume 9672 of the series Lecture Notes in Computer Science. In: Mattoso, M and Glavic, B (eds.), Springer, 226–229. DOI: 10.1007/978-3-319-40593-3 - Ramapriyan, HK, Kempler, S, Lynnes, C, McConaughy, G, McDonald, K, King, R, Calvo, S, Harberts, R and Roelofs, L. 2002. Conceptual Study of Intelligent Data Archives of the Future. 19th IEEE Symposium on Mass Storage Systems.
April 15–18, 2002 . College Park, MD, USA. [Available online at:http://storageconference.us/2002/papers/b07bp-hkr.pdf ]. - Ramapriyan, HK, Peng, G, Moroni, D and Shie, CL. 2017. Ensuring and Improving Information Quality for Earth Science Data and Products. D.-Lib Magazine, 23. DOI: 10.1045/july2017-ramapriyan
- Shewhart, WA. 1939. Statistical method from the viewpoint of quality control. The Dove edition, 155.
- Stvilia, B, Gasser, L, Twidale, MB and Smith, LC. 2007. A framework for information quality assessment. Journal of the Association for Information Science and Technology, 58: 1720–1733. DOI: 10.1002/asi.20652
- TechTarget. 2007. What is best practice? In: The essential guide to supply chain management best practices. [Available at:
http://searchsoftwarequality.techtarget.com/definition/best-practice ]. - Tilmes, C, Fox, P, Ma, XG, McGuinness, DL, Privette, AP, Smith, A, Waple, A, Zednik, S and Zheng, JG. 2013. Provenance Representation for the National Climate Assessment in the Global Change Information System. IEEE Trans. Geosci. and Remote Sensing, 51. DOI: 10.1109/TGRS.2013.2262179
- Tilmes, C, Privette, AP, Chen, J, Ramachandran, R, Bugbee, KM and Wolfe, RE. 2015b. Linking from observations to data to actionable science in the climate data initiative. Proc. 2015 IEEE Geosci. and Remote Sensing Symposium,
26–31 July 2015 . Milan, Italy. - Tilmes, C, Wolfe, RE, Duggan, B, Aulenbach, S, Goldstein, JC, Ma, X and Zednik, S. 2015a. Supporting trust with provenance of the findings of the national climate assessment. METHOD 2015: The 4th Intl. Workshop on Methods for Establishing Trust of (Open) Data,
11 Oct. 2015 . Bethlehem, PA, USA. [Available at:http://www.few.vu.nl/~dceolin/method2015/papers/METHOD_2015_paper_2.pdf ]. - USGCRP (U.S. Global Change Research Program). 2016.
The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment. Crimmins . In: Balbus, AJ, Gamble, JL, Beard, CB, Bell, JE, Dodgen, D, Eisen, RJ, Fann, N, Hawkins, MD, Herring, SC, Jantarasami, L, Mills, DM, Saha, S, Sarofim, MC, Trtanj, J and Ziska, L (eds.), U.S. Global Change Research Program, 312. Washington, DC. DOI: 10.7930/J0R49NQX - Wang, RY and Strong, DM. 1996. Beyond accuracy: What data quality means to consumers. Journal of Management Information Systems, 12(4): 5. DOI: 10.1080/07421222.1996.11518099
- Wilkinson, MD and 51 others. 2016. The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3. DOI: 10.1038/sdata.2016.18
DOI: https://doi.org/10.5334/dsj-2018-015 | Journal eISSN: 1683-1470
Language: English
Page range: 15 - 15
Submitted on: Sep 15, 2017
Accepted on: Jun 11, 2018
Published on: Jun 28, 2018
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
© 2018 Ge Peng, Jeffrey L. Privette, Curt Tilmes, Sky Bristol, Tom Maycock, John J. Bates, Scott Hausman, Otis Brown, Edward J. Kearns, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.