Purpose: this paper introduces the Research Articles in Simplified HTML (or RASH ), which is a Web-first format for writing HTML-based scholarly papers; it is accompanied by the RASH Framework , i.e. a set tools for interacting with RASH-based articles. The paper also presents an evaluation that involved authors and reviewers of RASH articles, submitted to the SAVE-SD 2015 and SAVE-SD 2016 workshops.
Design: RASH has been developed in order to: be easy to learn and use; share scholarly documents (and embedded semantic annotations) through the Web; support its adoption within the existing publishing workflow
Findings : the evaluation study confirmed that RASH can already be adopted in workshops, conferences and journals and can be quickly learnt by researchers who are familiar with HTML.
Research limitations: the evaluation study also highlighted some issues in the adoption of RASH, and in general of HTML formats, especially by less technical savvy users. Moreover, additional tools are needed, e.g. for enabling additional conversion from/to existing formats such as OpenXML.
Practical implications: RASH (and its Framework) is another step towards enabling the definition of formal representations of the meaning of the content of an article, facilitate its automatic discovery, enable its linking to semantically related articles, provide access to data within the article in actionable form, and allow integration of data between papers.
Social implications: RASH addresses the intrinsic needs related to the various users of a scholarly article: researchers (focussing on its content), readers (experiencing new ways for browsing it), citizen scientists (reusing available data formally defined within it through semantic annotations), publishers (using the advantages of new technologies as envisioned by the Semantic Publishing movement).
Value: RASH focuses strictly on writing the content of the paper (i.e., organisation of text + semantic annotations) and leaves all the issues about it validation, visualisation, conversion, and semantic data extraction to the various tools developed within its Framework.