A Capability Maturity Model for Research Data Management
CMM for RDM » Bibliography


Last modified by Arden Kirkland on 2014/06/03 19:28


Ailamaki, A.,  Ioannidis, Y.E., & Livny, M. (1998). Scientific workflow management by database management. In: Proceedings of the Tenth International Conference on Scientific and Statistical Database Management, Capri, Italy, July 1-3, 1998. Retrieved from http://www.cs.cmu.edu/~natassa/aapubs/conference/scientific-workflow-management.pdf

Australian National Data Service (2011). Research data management framework: Capability maturity guide. Retrieved from http://ands.org.au/guides/dmframework/dmf-capability-maturity-guide.pdf

Black Rock Forest Consortium. (2007). Data submission protocol. Retrieved from http://www.blackrockforest.org/docs/scientist-resources/DataResources/DataSubmission.html

Borer, E. T., Seabloom, E. W., Jones, M. B., & Schildhauer, M. (2009). Some Simple Guidelines for Effective Data Management. Bulletin of the Ecological Society of America, 90(2), 205–214. http://dx.doi.org/10.1890/0012-9623-90.2.205

Brase, J., Socha, Y., Callaghan, S., Borgman, C.L., Uhlir, P.F., Carroll, B. (2014). Data citation: Principles and practice. In J. Ray (Ed.), Research Data Management: Practical Strategies for Information Professionals (Charleston Insights in Library, Information, and Archival Sciences). West Lafayette, Indiana: Purdue University Press.

Brooks Jr, F. P. (2010). The design of design: Essays from a computer scientist. Pearson Education.

Brown, D.A, Brady, P.R., Dietz, A., Cao, J., Johnson, B., & McNabb, J. (2006). A case study on the use of workflow technologies for scientific analysis: Gravitational wave data analysis, in I.J. Taylor, E. Deelman, D. Gannon, and M.S. Shields(Eds.), Workflows for e-Science, chapter 5, pp. 41–61. Berlin: Springer-Verlag.

Carlson, S. (2006). Lost in a sea of science data. The Chronicle of Higher Education, 52(42). Retrieved from http://chronicle.com/weekly/v52/i42/42a03501.htm

CMMI Product Team. (2006). CMMI for Development, Version 1.2 (No. CMU/SEI-2006-TR-008). Pittsburgh, PA, USA: Carnegie Mellon Software Engineering Institute. Retrieved from http://repository.cmu.edu/sei/387

Columbia Center for New Media Teaching and Learning. (n.d.). Responsible conduct of research: Data acquisition and management: Foundation text. Retrieved from http://ccnmtl.columbia.edu/projects/rcr/rcr_data/foundation/index.html#3_B

Cornell University Library. (2007). Cornell University Library personas. Retrieved from http://hdl.handle.net/1813/8302

Corti, L., Van den Eynden, V., Bishop, L., & Woollard, M. (2014). Managing and Sharing Research Data: A Guide to Good Practice. Los Angeles, CA: SAGE. 

DataONE. (2011). Best Practices. Retrieved from https://www.dataone.org/best-practices

DataONE. (2013). Member node description: PISCO. Retrieved from http://www.dataone.org/sites/all/documents/DataONEMNDescription_PISCO.pdf

D’Ignazio, J., & Qin, J. (2008). Faculty data management practices: A campus-wide census of STEM departments. Proceedings of the American Society for Information Science and Technology, 45(1), 1–6. doi:10.1002/meet.2008.14504503139 . Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/meet.2008.14504503139/abstract

Dryad. (2014). Pricing plans and data publishing charges. Retrieved from http://datadryad.org/pages/pricing

Edwards, P. N., Mayernik, M. S., Batcheller, A. L., Bowker, G. C., & Borgman, C. L. (2011). Science friction: Data, metadata, and collaboration. Social Studies of Science, 41(5), 667–690. doi:10.1177/0306312711413314. Retrieved from http://pne.people.si.umich.edu/PDF/EdwardsEtAl2011ScienceFriction.pdf

Faniel, I. M., & Zimmerman, A. (2011). Beyond the Data Deluge: A Research Agenda for Large-Scale Data Sharing and Reuse. International Journal of Digital Curation, 6(1), 58–69. doi:10.2218/ijdc.v6i1.172. Retrieved from http://www.ijdc.net/index.php/ijdc/article/view/163/231

Gray, J. (2007). Jim Gray on eScience: A transformed scientific method. In K. M. Tolle, D. Tansley, & A. J. G. Hey (Eds.), The Fourth Paradigm: Data-Intensive Scientific Discovery (pp. 5–12). Edmond, WA: Microsoft Research. Retrieved from http://languagelog.ldc.upenn.edu/myl/JimGrayOnE-Science.pdf

Hale, S. S., Miglarese, A. H., Bradley, M. P., Belton, T. J., Cooper, L. D., Frame, M. T., et al. (2003). Managing Troubled Data: Coastal Data Partnerships Smooth Data Integration. Environmental Monitoring and Assessment, 81(1-3), 133–148. doi:10.1023/A:1021372923589. Retrieved from http://link.springer.com/article/10.1023%2FA%3A1021372923589

Hook, L. A., Vannan, S. K. S., Beaty, T. W., Cook, R. B., & Wilson, B. E. (2010). Best Practices for Preparing Environmental Data Sets to Share and Archive. Oak Ridge National Laboratory Distributed Active  Archive Center. Retrieved from http://daac.ornl.gov/PI/BestPractices-2010.pdf

Hubbard Brook Ecosystem Study. (2014).  Data use policy. Retrieved from http://www.hubbardbrook.org/data/dataset.php?id=4

Jahnke, L., Asher, A., & Keralis, S. D. (2012). The problem of data. Council on Library and Information Resources (CLIR) Report, pub. #154. ISBN 978-1-932326-42-0 Retrieved from http://digitalcommons.bucknell.edu/fac_pubs/52/

Jones, M. B., Berkley, C., Bojilova, J., & Schildhauer, M. (2001). Managing scientific metadata. IEEE Internet Computing, 5(5), 59–68. doi:10.1109/4236.957896. Retrieved from http://www.computer.org/csdl/mags/ic/2001/05/w5059-abs.html

Karasti, H., & Baker, K. S. (2008). Digital data practices and the long term ecological research program growing global. International Journal of Digital Curation, 3(2), 42–58. doi:10.2218/ijdc.v3i2.57. Retrieved from http://www.ijdc.net/index.php/ijdc/article/view/86

Key Perspectives. (2010). Data dimensions: disciplinary differences in research data sharing, reuse and long term viability. Digital Curation Centre. Retrieved from http://www.dcc.ac.uk/projects/scarp

Lage, K., Losoff, B., & Maness, J. (2011). Receptivity to library involvement in scientific data curation: A case study at the University of Colorado Boulder. Portal: Libraries and the Academy, 11(4): 915-937. doi:10.1353/pla.2011.0049. Retrieved from http://www.press.jhu.edu/journals/portal_libraries_and_the_academy/portal_pre_print/current/articles/11.4lage.pdf

Long, J. S. (2009). The workflow of data analysis using Stata. College Station, Texas: Stata Press Books.

Lyon, L., Ball, A., Duke, M., & Day, M. (2012). Community capability model framework. White Paper. UKOLN, University of Bath & Microsoft Research. Retrieved from http://communitymodel.sharepoint.com/Documents/CCMDIRWhitePaper-24042012.pdf

Mayernik, M. S. (2010). Metadata tensions: A case study of library principles vs. everyday scientific data practices. Proceedings of the American Society for Information Science and Technology, 47(1), 1–2. doi:10.1002/meet.14504701337. Retrieved from http://www.asis.org/asist2010/proceedings/proceedings/ASIST_AM10/submissions/337_Final_Submission.pdf

Mayernik, M. S., Batcheller, A. L., & Borgman, C. L. (2011). How Institutional Factors Influence the Creation of Scientific Metadata. In Proceedings of the 2011 iConference (pp. 417–425). New York, NY, USA: ACM. doi:10.1145/1940761.1940818. Retrieved from http://doi.acm.org/10.1145/1940761.1940818

Michener, W. K. (2006). Meta-information concepts for ecological data management. Ecological Informatics, 1(1), 3–7. doi:10.1016/j.ecoinf.2005.08.004. Retrieved from http://www.sciencedirect.com/science/article/pii/S157495410500004X

Mullins, J. (2007). Enabling international access to scientific data sets: Creation of the Distributed Data Curation Center (D2C2). Purdue University, Purdue E-Pubs. Retrieved from http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1100&context=lib_research

Murray-Rust, P. (2008). Chemistry for everyone. Nature, 451, 648-651. Retrieved from http://www.nature.com/nature/journal/v451/n7179/full/451648a.html

Paulk, M. C., Curtis, B., Chrissis, M. B., & Weber, C. V. (1993a). Capability maturity model, Version 1.1. IEEE Software, 10(4): 18-27. doi:10.1109/52.219617. Retrieved from http://www.computer.org/csdl/mags/so/1993/04/s4018-abs.html

Paulk, M. C., Curtis, B., Chrissis, M. B., & Weber, C. V. (1993b). Capability Maturity Model for Software, Version 1.1 (No. CMU/SEI-93-TR-024). Software Engineering Institute. Retrieved from http://resources.sei.cmu.edu/library/asset-view.cfm?assetID=11955

Pohl, K. & Rupp, C. (2011). Requirements Engineering Fundamentals: Study Guide for the Certified Engineering Exam. Sebastopol, CA: O'Reilly Media.

Protein Data Bank. (2014). Policies and references [of Protein Data Bank]. Retrieved from http://www.rcsb.org/pdb/static.do?p=general_information/about_pdb/policies_references.html

Qin, J., & D’ignazio, J. (2010). The Central Role of Metadata in a Science Data Literacy Course. Journal of Library Metadata, 10(2-3), 188–204. doi:10.1080/19386389.2010.506379. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/19386389.2010.506379

Qin, J., D’Ignazio, J., & Baldwin, S. (2011). A workflow-based knowledge management architecture for geodynamics data. A White paper submitted to NSF GEO/OCI EarchCube Charrette meeting. Retrieved from http://earthcube.ning.com/group/user-requirements/forum/topics/white-paper-a-workflow-based-knowledge-management-architecture

Ray, J. M.  (2014). Introduction to research data management. In J. Ray (Ed.), Research Data Management: Practical Strategies for Information Professionals (Charleston Insights in Library, Information, and Archival Sciences). West Lafayette, Indiana:Purdue University Press.

Riley, Jenn. (2014). Metadata services. In J. Ray (Ed.), Research Data Management: Practical Strategies for Information Professionals (Charleston Insights in Library, Information, and Archival Sciences). West Lafayette, Indiana: Purdue University Press.

Sallans, A. & Lake, S. (2014). Data management assessment and planning tools. In J. Ray (Ed.),Research Data Management: Practical Strategies for Information Professionals (Charleston Insights in Library, Information, and Archival Sciences). West Lafayette, Indiana: Purdue University Press. Retrieved from http://books.google.com/books?id=qZStAQAAQBAJ&pg=PA87&dq=dmvitals&source=gbs_toc_r&cad=3#v=onepage&q=dmvitals&f=false

Sheaffer, P. (2012). Creating a sustainable business model for a digital repository: the Dryad experience. ASIS&T Research Data Access and Preservation Summit 2012, Baltimore, MD. Retrieved from http://www.slideshare.net/asist_org/creating-a-sustainable-business-model-for-a-digital-repository-the-dryad-experience-peggy-schaeffer-rdap12

Steinhart, G., Saylor, J., Albert, P., Alpi, K., Baxter, P., Brown, E., et al. (2008). Digital Research Data Curation: Overview of Issues, Current Activities, and Opportunities for the Cornell University Library (Working Paper). Retrieved from http://hdl.handle.net/1813/10903

Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., Manoff, M., Frame, M. (2011). Data Sharing by Scientists: Practices and Perceptions. PLoS ONE, 6(6), e21101. doi:10.1371/journal.pone.0021101. Retrieved from http://www.plosone.org/article/info:doi/10.1371/journal.pone.0021101

UK Data Archive. (2014). Create and manage data: Documenting your data. Retrieved from http://www.data-archive.ac.uk/create-manage/document

Van den Eynden, V., Corti, L., Woollard, M. & Bishop, L. (2011). Managing and Sharing Data: A Best Practice Guide for Researchers. (3rd ed.) Essex, England: University of Essex. Retrieved from http://www.data-archive.ac.uk/media/2894/managingsharing.pdf

Walters, T. O. (2009). Data curation program development in U.S. universities: The Georgia Institute of Technology example. International Journal of Digital Curation, 4(3), 83–92. doi:10.2218/ijdc.v4i3.116. Retrieved from http://www.ijdc.net/index.php/ijdc/article/view/136

Walters, T. & Skinner, K. (2011). New roles for new times: Digital curation for preservation. Retrieved from http://www.arl.org/focus-areas/workforce/1086

Westra, B. (2014). Developing Data Management Services for Researchers at the University of Oregon. In J. Ray (Ed.), Research Data Management: Practical Strategies for Information Professionals (Charleston Insights in Library, Information, and Archival Sciences). West Lafayette, Indiana: Purdue University Press.

Willis, C., Greenberg, J., & White, H. (2012). Analysis and Synthesis of Metadata Goals for Scientific Data. Journal of American Society for Information Science and Technology, 1505–1520. Retrieved from http://scholarship.law.duke.edu/faculty_scholarship/2713 

Zeng, M. L. & Qin, J. (2014). Metadata. Chicago, IL: ALA Neal Schuman. 

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