{"data":{"id":"10.6084/m9.figshare.c.3658130.v1","type":"dois","attributes":{"doi":"10.6084/m9.figshare.c.3658130.v1","prefix":"10.6084","suffix":"m9.figshare.c.3658130.v1","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Padilla, Stefano","nameType":"Personal","givenName":"Stefano","familyName":"Padilla","affiliation":[],"nameIdentifiers":[{"nameIdentifier":"https://orcid.org/0000-0002-7104-8349","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Understanding Concept Maps: A Closer Look at How People Organise Ideas Open Data Collection."}],"publisher":"Figshare","container":{},"publicationYear":2017,"subjects":[{"subject":"80602 Computer-Human Interaction","subjectScheme":"FOR"},{"subject":"FOS: Psychology","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2017-02-03","dateType":"Created"},{"date":"2017-02-03","dateType":"Updated"},{"date":"2017","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Collection","resourceType":"Collection","resourceTypeGeneral":"Collection"},"relatedIdentifiers":[{"relationType":"IsIdenticalTo","relatedIdentifier":"10.6084/m9.figshare.c.3658130","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"CC BY","rightsUri":"https://creativecommons.org/licenses/by/4.0"}],"descriptions":[{"description":"Open data collection for ACM CHI 2017 paper Understanding Concept Maps: A Closer Look at How People Organise Ideas.\u003cbr\u003ePaper Abstract:Research into creating visualisations that\norganise ideas into concise concept maps often focuses on implicit mathematical\nand statistical theories which are built around algorithmic efficacy or visual\ncomplexity. Although there are multiple techniques which attempt to mathematically\noptimise this multi-dimensional problem, it is still unknown how to create\nconcept maps that are immediately understandable to people. In this paper, we\npresent an in-depth qualitative study observing the behaviour and discussing\nthe strategy used by non-expert participants to create, interact, update and communicate\na concept map that represents a collection of research ideas. Our results show non-expert\nindividuals create concept maps differently to visualisation algorithms. We found\nthat our participants prioritised narrative, landmarks, abstraction, clarity,\nand simplicity. Finally, we derive design recommendations from our results which\nwe hope will inspire future algorithms that automatically create more usable\nand compelling concepts maps better suited to the natural behaviours and needs of\nusers.\u003cbr\u003eCC-BY dataset for Understanding Concept Maps: A\nCloser Look at How People Organise Ideas CHI’17 Paper by Stefano Padilla is\nlicensed under a Creative Commons\nAttribution 4.0 International License.\n\n\u003cbr\u003e\nStefano Padilla,\nThomas S. Methven, David A. Robb, Mike J. Chantler. 2017. Understanding Concept\nMaps: A Closer Look at How People Organise Ideas. In \u003ci\u003eProceedings of the 2017 CHI ACM Conference on Human Factors in\nComputing Systems\u003c/i\u003e (CHI ’17). ACM, Denver, CO, USA. DOI: http://dx.doi.org/10.1145/3025453.3025977 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