Social scientists' satisfaction with data reuse

Journal of the Association for Information Science and Technology

Volumn 67, Issue 6, 2016, Pages 1404-1416

  Faniel, Ixchel M ^a   Kriesberg, Adam ^b   Yakel, Elizabeth ^b  

^a OCLC Research   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

(attributes of information and data); information use; user satisfaction

Indexed keywords

(ATTRIBUTES OF INFORMATION AND DATA); DIGITAL DATAS; JOURNAL ARTICLES; RECENT RESEARCHES; SOCIAL RESEARCH; SOCIAL SCIENTISTS; SYSTEMS AND INFORMATION; USER SATISFACTION;

INFORMATION USE;

DOCUMENTATION; DRAWING; HUMAN; INFORMATION SCIENCE; INFORMATION SYSTEM; MODEL; SATISFACTION; SCIENTIST; UNIVERSITY;

EID: 84965104556     PISSN: 23301635     EISSN: 23301643     Source Type: Journal    
DOI: 10.1002/asi.23480     Document Type: Article

References (74)

1. Anderson, E.W., &, Sullivan, M.W., (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12 (2), 125-143.
2. Anderson, J.C., &, Gerbing, D.W., (1991). Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities. Journal of Applied Psychology, 76 (5), 732-740.
3. Barry, C.L., (1994). User-defined relevance criteria: An exploratory study. Journal of the American Society for Information Science, 45 (3), 149-159.
4. Bernard, H.R., (2000). Social research methods: Qualitative and quantitative approaches. London: Sage Publications Ltd.
5. Birnholtz, J.P., &, Bietz, M., (2003). Data at work: Supporting sharing in science and engineering. GROUP '03 Proceedings of the 2003 International ACM SIGGROUP Conference on Supporting Group Work (pp. 339-348). New York: ACM.
6. Bourne, P.E., (2005). Will a biological database be different from a biological journal. PLoS Computational Biology, 1 (3), 179-181.
7. Brase, J., (2009). DataCite-A global registration agency for research data. In Fourth International Conference on Cooperation and Promotion of Information Resources in Science and Technology, 2009. COINFO '09 (pp. 257-261). Los Alamitos: IEEE Computer Society.
8. California Digital Library. (2014). Why Use EZID? Retrieved from http://ezid.cdlib.org/home/why
9. Card, J.J., Shapiro, L., Amarillas, A., McKean, E., &, Kuhn, T., (2003). Broadening public access to data through the development of tools for data novices. Social Science Computer Review, 21 (3), 352-359.
10. Carlson, S., &, Anderson, B., (2007). What are data? The many kinds of data and their implications for data re-use. Journal of Computer-Mediated Communication, 12 (2), 635-651.
11. Caro, A., Calero, C., Caballero, I., &, Piattini, M., (2008). A proposal for a set of attributes relevant for Web portal data quality. Software Quality Journal, 16 (4), 513-542.
12. Chin, G., &, Lansing, C.S., (2004). Capturing and supporting contexts for scientific data sharing via the biological sciences collaboratory. In CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work (pp. 409-418). New York: ACM.
13. Churchill, G.A., &, Surprenant, C., (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing Research, 19 (4), 491-504.
14. Consultative Committee for Space Data Systems. (2012). Space Data and Information Transfer Systems-Audit and Certification of Trustworthy Digital Repositories Standard No. ISO 16363:2012 (CCSDS 652-R-1). Washington, DC: Consultative Committee for Space Data Systems. Retrieved from http://www.iso.org/iso/catalogue-detail.htm?csnumber=56510
15. Darby, R., Lambert, S., Matthews, B., Wilson, M., Gitmans, K., Dallmeier-Tiessen, S.,..., Suhonen, J., (2012). Enabling scientific data sharing and re-use. In 2012 IEEE 8th International Conference on E-Science (E-Science) (pp. 1-8). Washington, DC: IEEE Computer Society.
16. Data Archiving and Networked Services (DANS). (2010). Data seal of approval: Quality guidelines for digital research data. The Hague, The Netherlands. Retrieved from http://www.datasealofapproval.org/?q=about
17. Dobratz, S., Schoger, A., &, Strathmann, S., (2007). The nestor Catalogue of Criteria for Trusted Digital Repository Evaluation and Certification. Journal of Digital Information, 8 (2). Retrieved from http://journals.tdl.org/jodi/index.php/jodi/article/view/199/180
18. Faniel, I.M., (2009). Unrealized Potential: The Socio-Technical Challenges of a Large Scale Cyberinfrastructure Initiative. Retrieved from http://hdl.handle.net/2027.42/61845
19. Faniel, I.M., &, Jacobsen, T.E., (2010). Reusing scientific data: How earthquake engineering researchers assess the reusability of colleagues' data. Computer Supported Cooperative Work, 19 (3-4), 355-375.
20. Faniel, I., Kansa, E., Whitcher Kansa, S., Barrera-Gomez, J., &, Yakel, E., (2013). The challenges of digging data: A study of context in archaeological data reuse. In Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries (pp. 295-304). New York: ACM.
21. Faniel, I.M., Kriesberg, A., &, Yakel, E., (2012). Data reuse and sensemaking among novice social scientists. Proceedings of the American Society for Information Science and Technology, 49, 1-10. doi: 10.1002/meet.14504901068
22. Fear, K.M., (2013). Measuring and anticipating the impact of data reuse (Dissertation, University of Michigan). Retrieved from http://deepblue.lib.umich.edu/handle/2027.42/102481
23. Flavián, C., Guinalíu, M., &, Gurrea, R., (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & Management, 43 (1), 1-14.
24. Fogg, B.J., Swani, P., Treinen, M., Marshall, J., Laraki, O., Osipovich, A.,..., Shon, J., (2001). What makes web sites credible? A report on a large quantitative study. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 61-68). New York: ACM.
25. Fogg, B.J., &, Tseng, H., (1999). The elements of computer credibility. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 80-87). New York: ACM.
26. Groves, R.M., Fowler, F.J., Couper, M., Lepkowski, J.M., Singer, E., &, Tourangeau, R., (2009). Survey methodology. Hoboken, NJ: Wiley.
27. Hair, J.F., Anderson, R.E., Tatham, R.L., &, Black, W., (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.
28. Herring, S.D., (2001). Using the World Wide Web for research: Are faculty satisfied? Journal of Academic Librarianship, 27 (3), 213-219.
29. Hey, A.J.G., Tansley, S., &, Tolle, K.M., (2009). The fourth paradigm: Data-intensive scientific discovery. Redmond, WA: Microsoft Research. Retrieved from http://research.microsoft.com/en-us/collaboration/fourthparadigm
30. Huang, H., Stvilia, B., Jörgensen, C., &, Bass, H.W., (2012). Prioritization of data quality dimensions and skills requirements in genome annotation work. Journal of the American Society for Information Science and Technology, 63 (1), 195-207.
31. ICPSR. (2014). ICPSR bibliography of data-related literature. Retrieved from http://www.icpsr.umich.edu/icpsrweb/ICPSR/citations/
32. Ingwersen, P., &, Chavan, V., (2011). Indicators for the Data Usage Index (DUI): An incentive for publishing primary biodiversity data through global information infrastructure. BMC Bioinformatics, 12 (Suppl. 15), S3.
33. Jirotka, M., Procter, R., Hartswood, M., Slack, R., Simpson, A., Coopmans, C.,..., Voss, A., (2005). Collaboration and trust in healthcare innovation: The eDiaMoND CaseStudy. Computer Supported Cooperative Work, 14 (4), 369-398.
34. Kansa, E.C., Kansa, S.W., &, Arbuckle, B., (2014). Publishing and pushing: Mixing models for communicating research data in archaeology. International Journal of Digital Curation, 9 (1), 57-70.
35. Karasti, H., &, Baker, K., (2008). Digital data practices and long term ecological research program growing global. International Journal of Digital Curation, 3 (2), 42-58.
36. King, G., (2011). Ensuring the data-rich future of the social sciences. Science, 331 (6018), 719-721.
37. Kriesberg, A., Frank, R.D., Faniel, I.M., &, Yakel, E., (2013). The role of data reuse in the apprenticeship process. Proceedings of the American Society of Information Science and Technology, 50, 1-10. doi: 10.1002/meet.14505001051.
38. Lee, Y.W., Strong, D.M., Kahn, B.K., &, Wang, R.Y., (2002). AIMQ: A methodology for information quality assessment. Information & Management, 40 (2), 133-146.
39. Lowry, P.B., &, Gaskin, J., (2014). Partial Least Squares (PLS) Structural Equation Modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, Early Access Online, 57 (2), 123-146.
40. Marchand, D., (1990). Managing information quality. In, I. Wormell, (Ed.), Information quality: Definitions and dimensions (pp. 7-17). London: Taylor Graham.
41. Merriam-Webster. (2014). Credibility. Retrieved from http://www.merriam-webster.com/dictionary/credibility
42. Metzger, M.J., Flanagan, A.J., &, Medders, R.B., (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60 (3), 413-439.
43. Michener, W., Vision, T., Cruse, P., Vieglais, D., Kunze, J., &, Janée, G., (2011). DataONE: Data Observation Network for earth-Preserving data and enabling innovation in the biological and environmental sciences. D-Lib Magazine, 17 (1/2).
44. Niu, J., (2009). Perceived documentation quality of social science data. (Dissertation, University of Michigan). Retrieved from http://deepblue.lib.umich.edu/handle/2027.42/63871
45. Norris, M., &, Oppenheim, C., (2007). Comparing alternatives to the Web of science for coverage of the social sciences' literature. Journal of Informetrics, 1 (2), 161-169.
46. Nunnally, J.C., (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
47. Olaisen, J., (1990). Information quality factors and the cognitive authority of electronic information. In, I. Wormell, (Ed.), Information quality: Definitions and dimensions (pp. 91-121). London: Taylor Graham.
48. Oliver, R.L., (2010). Satisfaction: A behavioral perspective on the consumer (2nd ed.). Armonk, NY: M.E. Sharpe.
49. Oliver, R.L., &, DeSarbo, W.S., (1988). Response determinants in satisfaction judgments. Journal of Consumer Research, 14 (4), 495-507.
50. Piwowar, H.A., &, Chapman, W.W., (2010). Public sharing of research data sets: A pilot study of associations. Journal of Informetrics, 4 (2), 148-156.
51. Piwowar, H.A., &, Vision, T.J., (2013). Data reuse and the open data citation advantage. PeerJ, 1: e175, 1-25. doi: 10.7717/peerj.175.
52. Rieh, S.Y., (2002). Judgment of information quality and cognitive authority in the Web. Journal of the American Society for Information Science and Technology, 53 (2), 145-161.
53. Rieh, S.Y., &, Danielson, D.R., (2007). Credibility: A multidisciplinary framework. Annual Review of Information Science and Technology, 41 (1), 307-364.
54. Rolland, B., &, Lee, C.P., (2013). Beyond trust and reliability: Reusing data in collaborative cancer epidemiology research. In CSCW '13 Proceedings of the 2013 Conference on Computer Supported Cooperative Work (pp. 435-444). New York: ACM.
55. Seddon, P., &, Yip, S.-K., (1992). An empirical evaluation of User Information Satisfaction (UIS) measures for use with general ledger accounting software. Journal of Information Systems, 6 (1), 75-92.
56. Seddon, P.B., &, Kiew, M.-Y., (1994). A partial test and development of the DeLone and McLean model of is success. In ICIS 1994 Proceedings (pp. 99-110). Atlanta: Association for Information Systems.
57. Straub, D., Boudreau, M., &, Gefen, D., (2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 13, 380-427. Retrieved from http://aisel.aisnet.org/cais/vol13/iss1/24
58. Stvilia, B., Twidale, M.B., Smith, L.C., &, Gasser, L., (2008). Information quality work organization in Wikipedia. Journal of the American Society for Information Science and Technology, 59 (6), 983-1001.
59. Stvilia, B., Mon, L., &, Yi, Y.J., (2009). A model for online consumer health information quality. Journal of the American Society for Information Science and Technology, 60 (9), 1781-1791.
60. Stvilia, B., Hinnant, C.C., Wu, S., Worrall, A., Lee, D.J., Burnett, K.,..., Marty, P.F., (2014). Research project tasks, data, and perceptions of data quality in a condensed matter physics community. Journal of the Association for Information Science and Technology. doi: 10.1002/asi.23177
61. Taylor, R.S., (1986). Value-added processes in information systems. Norwood, NJ: Ablex Publishing.
62. Teo, T.S.H., &, Wong, P.K., (1998). An empirical study of the performance impact of computerization in the retail industry. Omega, 26 (5), 611-621.
63. Tourangeau, R., Rips, L.J., &, Rasinski, K.A., (2000). The psychology of survey response. Cambridge: Cambridge University Press.
64. Van House, N., (2002). Digital libraries and practices of trust: Networked biodiversity information. Social Epistemology: A Journal of Knowledge, Culture and Policy, 16 (1), 99-114.
65. Van House, N.A., Butler, M.H., &, Schiff, L.R., (1998). Cooperative knowledge work and practices of trust: Sharing environmental planning data sets. In CSCW '98 Proceedings of the 1998 ACM Conference on Computer Supported Cooperative Work (pp. 335-343). New York: ACM.
66. Vardigan, M., Heus, P., &, Thomas, W., (2008). Data documentation initiative: Toward a standard for the social sciences. International Journal of Digital Curation, 3 (1), 107-113.
67. Vardigan, M., Granda, P., Hansen, S.E., Ionescu, S., &, LeClere, F., (2010). Documenting the research life cycle: One data model, many products. IFC Bulletin, 33, 91-104.
68. Wang, P., &, Soergel, D., (1998). A cognitive model of document use during a research project. Study I. Document selection. Journal of the American Society for Information Science, 49 (2), 115-133.
69. Wang, R.Y., &, Strong, D.M., (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12 (4), 5-33.
70. Wang, P.L., &, White, M.D., (1999). A cognitive model of document use during a research project. Study II. Decisions at the reading and citing stages. Journal of the American Society for Information Science, 50 (2), 98-114.
71. Wilkinson, M., (2010). DataCite: The International Data Citation Initiative. Data sets programme (No. 163). Working Paper Series des Rates für Sozial- und Wirtschaftsdaten. Retrieved from http://www.econstor.eu/handle/10419/43618
72. Wilson, P., (1983). Second-hand knowledge: An inquiry into cognitive authority. Westport, CT: Greenwood Press.
73. Zimmerman, A., (2007). Not by metadata alone: The use of diverse forms of knowledge to locate data for reuse. International Journal on Digital Libraries, 7 (1-2), 5-16.
74. Zimmerman, A.S., (2008). New knowledge from old data: The role of standards in the sharing and reuse of ecological data. Science, Technology & Human Values, 33 (5), 631-652.