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Web Search)","subjectScheme":"FOR"}],"contributors":[],"dates":[{"date":"2016-10-04","dateType":"Created"},{"date":"2016-10-04","dateType":"Updated"},{"date":"2016","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsPreviousVersionOf","relatedIdentifier":"10.6084/m9.figshare.3980463","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["13232 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This dataset contains the data collected for the evaluation of RASH (Research Articles in Simplified HTML), which is presented in the paper 'Research Articles in Simplified HTML: a Web-first format for HTML-based scholarly articles'.\u003cbr\u003eIn particular, it includes:\u003cbr\u003e1) Four CSV files reporting the surveys filled in by authors and reviewers of RASH papers published in the SAVE-SD 2015 and SAVE-SD 2016 workshops:- survey_authors_2015- survey_authors_2016- survey_reviewers_2015- survey_reviewers_2016\u003cbr\u003e2) Four CSV files presenting the more frequent entities and vocabularies included in the RASH papers published in SAVE-SD 2015 and SAVE-SD 2016 workshops:- entities_analysis_2015.csv- entities_analysis_2016.csv- vocabularies_analysis_2015.csv- vocabularies_analysis_2016.csv \u003cbr\u003eFor any question about the data please contact francesco.osborne@open.ac.uk or silvio.peroni@unibo.it\u003cbr\u003e","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://figshare.com/articles/dataset/RASH_evaluation/3980463/1","contentUrl":null,"metadataVersion":4,"schemaVersion":"http://datacite.org/sc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