{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:06:36Z","timestamp":1760234796422,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,6,24]],"date-time":"2021-06-24T00:00:00Z","timestamp":1624492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Informatics"],"abstract":"<jats:p>In higher education, a wealth of data is available to advisors, recruiters, marketers, and program directors. These large datasets can be accessed using an array of data analysis tools that may lead users to assume that data sources conflict with one another. As users identify new ways of accessing and analyzing these data, they deviate from existing work practices and sometimes create their own databases. This study investigated the needs of end users who are accessing these seemingly fragmented databases. Analysis of a survey completed by eighteen users and ten semi-structured interviews from five colleges and universities highlighted three recurring themes that affect work practices (access, understandability, and use), as well as a series of challenges and opportunities for the design of data gateways for higher education. We discuss a set of broadly applicable design recommendations and five design functionalities that the data gateways should support: training, collaboration, tracking, definitions and roadblocks, and time.<\/jats:p>","DOI":"10.3390\/informatics8030042","type":"journal-article","created":{"date-parts":[[2021,6,24]],"date-time":"2021-06-24T23:22:14Z","timestamp":1624576934000},"page":"42","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2559-8822","authenticated-orcid":false,"given":"Amanda","family":"Briggs","sequence":"first","affiliation":[{"name":"Richard M. Fairbanks School of Public Health, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5744-6386","authenticated-orcid":false,"given":"Francesco","family":"Cafaro","sequence":"additional","affiliation":[{"name":"School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,24]]},"reference":[{"key":"ref_1","unstructured":"Keim, D.A., Mansmann, F., Schneidewind, J., and Ziegler, H. (2006, January 5\u20137). Challenges in visual data analysis. Proceedings of theTenth International Conference on Information Visualisation (IV\u201906), London, UK."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Daniel, B.K. (2017). Big data in higher education: The big picture. Big Data and Learning Analytics in Higher Education, Springer.","DOI":"10.1007\/978-3-319-06520-5_3"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Khan, S.I., and Hoque, A.S.M.L. (2016). Towards development of national health data warehouse for knowledge discovery. Intelligent Systems Technologies and Applications, Springer.","DOI":"10.1007\/978-3-319-23258-4_36"},{"key":"ref_4","unstructured":"Rattenbury, T., Hellerstein, J.M., Heer, J., Kandel, S., and Carreras, C. (2017). Principles of Data Wrangling: Practical Techniques for Data Preparation, O\u2019Reilly Media, Inc."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1145\/2168931.2168943","article-title":"Interactions with big data analytics","volume":"19","author":"Fisher","year":"2012","journal-title":"Interactions"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Voida, A., Harmon, E., and Al-Ani, B. (2011, January 7\u201312). Homebrew databases: Complexities of everyday information management in nonprofit organizations. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Vancouver, BC, Canada.","DOI":"10.1145\/1978942.1979078"},{"key":"ref_7","first-page":"2019","article-title":"The Babel problem with big data in higher ed","volume":"11","author":"Green","year":"2018","journal-title":"Retrieved March"},{"key":"ref_8","unstructured":"Carroll, J.M. (2013). Human computer interaction-brief intro. The Encyclopedia of Human-Computer Interaction, [2nd ed.]. Available online: https:\/\/www.interaction-design.org\/literature\/book\/the-encyclopedia-of-human-computer-interaction-2nd-ed."},{"key":"ref_9","unstructured":"Shneiderman, B., Plaisant, C., Cohen, M.S., Jacobs, S., Elmqvist, N., and Diakopoulos, N. (2016). Designing the User Interface: Strategies for Effective Human-Computer Interaction, Pearson."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1002\/cpe.3635","article-title":"Monitoring and improving performance in human\u2013computer interaction","volume":"28","author":"Carneiro","year":"2016","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zdziebko, T., and Sulikowski, P. (2015). Monitoring human website interactions for online stores. New Contributions in Information Systems and Technologies, Springer.","DOI":"10.1007\/978-3-319-16528-8_35"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-031-02217-3","article-title":"Qualitative HCI research: Going behind the scenes","volume":"9","author":"Blandford","year":"2016","journal-title":"Synth. Lect. Hum. Centered Inform."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.ijhcs.2019.09.004","article-title":"Understanding human-data interaction: Literature review and recommendations for design","volume":"134","author":"Victorelli","year":"2020","journal-title":"Int. J. Hum. Comput. Stud."},{"key":"ref_14","unstructured":"Mortier, R., Haddadi, H., Henderson, T., McAuley, D., and Crowcroft, J. (2021, June 23). Human-Data Interaction: The Human Face of the Data-Driven Society. Available online: https:\/\/arxiv.org\/abs\/1412.6159."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Trajkova, M., Alhakamy, A., Cafaro, F., Mallappa, R., and Kankara, S.R. (2020, January 25\u201330). Move your body: Engaging museum visitors with human-data interaction. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, Honolulu, Hawaii.","DOI":"10.1145\/3313831.3376186"},{"key":"ref_16","unstructured":"Elmqvist, N. (2011, January 7\u201312). Embodied human-data interaction. Proceedings of the ACM CHI 2011 Workshop Embodied Interaction: Theory and Practice in HCI, Vancouver, BC, Canada."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1080\/1369118X.2012.678878","article-title":"Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon","volume":"15","author":"Boyd","year":"2012","journal-title":"Inform. Commun. Soc."},{"key":"ref_18","first-page":"21","article-title":"Big data, analytics and the path from insights to value","volume":"52","author":"LaValle","year":"2011","journal-title":"MIT Sloan Manag. Rev."},{"key":"ref_19","first-page":"17","article-title":"Data Mining and Its Applications in Higher Education","volume":"113","author":"Luan","year":"2002","journal-title":"New Dir. Inst. Res."},{"key":"ref_20","first-page":"9","article-title":"The evolution of big data and learning analytics in American higher education","volume":"16","author":"Picciano","year":"2012","journal-title":"J. Asynchronous Learn. Netw."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhu, C., Zhu, H., Xiong, H., Ding, P., and Xie, F. (2016, January 13\u201317). Recruitment market trend analysis with sequential latent variable models. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939689"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Bergman, O., Beyth-Marom, R., and Nachmias, R. (2006, January 24\u201327). The project fragmentation problem in personal information management. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Montreal, QC, Canada.","DOI":"10.1145\/1124772.1124813"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Bopp, C., Harmon, E., and Voida, A. (2017, January 6\u201311). Disempowered by data: Nonprofits, social enterprises, and the consequences of data-driven work. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA.","DOI":"10.1145\/3025453.3025694"},{"key":"ref_24","unstructured":"Pine, K., and Mazmanian, M. (2015). Emerging Insights on Building Infrastructure for Data-Driven Transparency and Accountability of Organizations. iConf. 2015 Proc., Available online: https:\/\/www.ideals.illinois.edu\/handle\/2142\/73454."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Le Dantec, C.A., and Edwards, W.K. (2010, January 10\u201315). Across boundaries of influence and accountability: The multiple scales of public sector information systems. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Atlanta, GA, USA.","DOI":"10.1145\/1753326.1753345"},{"key":"ref_26","first-page":"185","article-title":"Policy fields, data systems, and the performance of nonprofit human service organizations","volume":"42","author":"Benjamin","year":"2018","journal-title":"Hum. Serv. Organ. Manag. Leadersh. Gov."},{"key":"ref_27","unstructured":"Verma, N., and Voida, A. (March, January 27). On being actionable: Mythologies of business intelligence and disconnects in drill downs. Proceedings of the 19th International Conference on Supporting Group Work, San Francisco, CA, USA."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1080\/02680939.2015.1035758","article-title":"Digital education governance: Data visualization, predictive analytics, and \u2018real-time\u2019policy instruments","volume":"31","author":"Williamson","year":"2016","journal-title":"J. Educ. Policy"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2917","DOI":"10.1109\/TVCG.2012.219","article-title":"Enterprise data analysis and visualization: An interview study","volume":"18","author":"Kandel","year":"2012","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_30","first-page":"39","article-title":"Data visualization and infographics in visual communication design education at the age of information","volume":"3","author":"Dur","year":"2014","journal-title":"J. Arts Humanit."},{"key":"ref_31","unstructured":"Few, S. (2006). Information Dashboard Design: The Effective Visual Communication of Data, O\u2019reilly."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Chul Kwon, B., Fisher, B., and Yi, J.S. (2011, January 23\u201328). Visual analytic roadblocks for novice investigators. Proceedings of the 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), Providence, RI, USA.","DOI":"10.1109\/VAST.2011.6102435"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Sedlmair, M., Isenberg, P., Baur, D., and Butz, A. (2010, January 10\u201311). Evaluating information visualization in large companies: Challenges, experiences and recommendations. Proceedings of the 3rd BELIV\u201910 Workshop: BEyond Time and Errors: Novel Evaluation Methods for Information Visualization, Atlanta, GA, USA.","DOI":"10.1145\/2110192.2110204"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1177\/1473871611415994","article-title":"Research directions in data wrangling: Visualizations and transformations for usable and credible data","volume":"10","author":"Kandel","year":"2011","journal-title":"Inf. Vis."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Roggema, R. (2017). Research by Design: Proposition for a Methodological Approach. Urban Sci., 1.","DOI":"10.3390\/urbansci1010002"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Fiesler, C., Brubaker, J.R., Forte, A., Guha, S., McDonald, N., and Muller, M. (2019, January 3\u201313). Qualitative Methods for CSCW: Challenges and Opportunities. Proceedings of the Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, Austin, TX, USA.","DOI":"10.1145\/3311957.3359428"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"367","DOI":"10.3102\/00028312014004367","article-title":"Frameworks for comprehending discourse","volume":"14","author":"Anderson","year":"1977","journal-title":"Am. Educ. Res. J."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1191\/1478088706qp063oa","article-title":"Using thematic analysis in psychology","volume":"3","author":"Braun","year":"2006","journal-title":"Qual. Res. Psychol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1002\/nur.4770180211","article-title":"Sample size in qualitative research","volume":"18","author":"Sandelowski","year":"1995","journal-title":"Res. Nurs. Health"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/0160-2896(88)90011-6","article-title":"Hick\u2019s law, competing-task performance, and intelligence","volume":"12","author":"Roberts","year":"1988","journal-title":"Intelligence"},{"key":"ref_41","first-page":"37","article-title":"Building portals for higher education","volume":"2002","author":"Pickett","year":"2002","journal-title":"New Dir. Inst. Res."},{"key":"ref_42","unstructured":"Parkinson, C.N., and Osborn, R.C. (1957). Parkinson\u2019s Law, and Other Studies in Administration, Houghton Mifflin."},{"key":"ref_43","unstructured":"Hochschild, A.R. (2016). Invisible Labor: Hidden Work in the Contemporary World, University of California Press."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Beauregard, R., and Corriveau, P. (2007, January 22\u201327). User experience quality: A conceptual framework for goal setting and measurement. Proceedings of the International Conference on Digital Human Modeling, Beijing, China.","DOI":"10.1007\/978-3-540-73321-8_38"}],"container-title":["Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-9709\/8\/3\/42\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:23:10Z","timestamp":1760163790000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-9709\/8\/3\/42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,24]]},"references-count":44,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["informatics8030042"],"URL":"https:\/\/doi.org\/10.3390\/informatics8030042","relation":{},"ISSN":["2227-9709"],"issn-type":[{"type":"electronic","value":"2227-9709"}],"subject":[],"published":{"date-parts":[[2021,6,24]]}}}