{"id":563586,"date":"2019-01-22T12:44:33","date_gmt":"2019-01-22T20:44:33","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=563586"},"modified":"2019-01-22T12:44:33","modified_gmt":"2019-01-22T20:44:33","slug":"communicating-data-to-an-audience","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/communicating-data-to-an-audience\/","title":{"rendered":"Communicating Data to an Audience"},"content":{"rendered":"
Communicating data in an effective and efficient story requires the content author to recognize the needs, goals, and knowledge of the intended audience. To effectively communicate ideas and concepts, content authors need to think carefully about how their work best fits the needs of the audience. Data storytellers have an ethical obligation to ensure that their visualizations do not skew or mislead interpretations unnecessarily and this intersects with the literacy level of the expected audience. An individual in the audience brings their own viewpoints, backgrounds, and experience to each and every data-driven story they consume. Whether driven by their cultural background, social position, education, or other demographic characteristics, readers carry with them their own unique set of knowledge and biases. A consistent design approach can help an audience relate to a producer’s work and entice them to return. Television audiences are also fickle, often switching programs and channels within less than a second.<\/p>\n","protected":false},"excerpt":{"rendered":"
Communicating data in an effective and efficient story requires the content author to recognize the needs, goals, and knowledge of the intended audience. To effectively communicate ideas and concepts, content authors need to think carefully about how their work best fits the needs of the audience. Data storytellers have an ethical obligation to ensure that […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563,13554],"msr-publication-type":[193721],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-563586","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"Taylor & Francis 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