Abstract

Recently, several proposals and discussions have tried to push the use of HTML for preparing and sharing research works within the scholarly domain. Therefore, several native HTML-based templates and formats have been introduced for allowing researchers to write scientific documents, which could be access even with assistive technologies, e.g., screen readers. While HTML can be a good basis for guaranteeing accessibility of such papers, several issues are still in place when we consider the inclusion of non-textual entities in the main text, such as complex formulas and figures. In this paper we experiment on the use of one of such HTML formats, i.e., the Research Articles in Simplified HTML (RASH) format, extended for creating accessible graphs automatically out of CSV data. In particular, we introduce an extension to RASH to let the creation of accessible graphs. Moreover, we analyze the outcomes of some preliminary experiments we have done by using different screen readers on several operating systems and browsers.

Introduction

Accessibility of Web content from users with disabilities is a well-known topic. Since the end of 1980's until now, Standardization entities (i.e. W3C, ISO ), associations, and governments (with the promulgation of laws and acts ) have defined standards and conducted several initiatives with the aim of supporting users with disabilities in accessing digital content and online services.

In this context, accessing scientific content is still a critical issue, in particular for visually impaired people. Major barriers are represented by the Portable Document Format (PDF), which is the standard de-facto format for scientific papers , by the presence of graphs and graphical information, used to vehicle aggregated data as results of investigation and research activities , and by other characteristic elements, according to the topic of the research (e.g. mathematical formulae, chemical diagrams, etc.) . Some studies in this field show that inaccessible PDFs are one of the major causes of frustration when screen readers users browse the Web . Some other works demonstrated that one of the main problems with the PDF format is a lack of knowledge or prioritization of accessibility by document authors . Authors should equip images and graphs in a document with a textual description. Some plugins and browser add-ons have been designed to support authors in equipping their content with adequate textual alternatives for the graphical information . Unfortunately, they are usually based on the idea of presenting a textual description of the graph elements, instead of presenting the elements at the basis of their meaning. As a result, we obtain that screen reader users could miss the real significance of that graph and the data it represents .

Providing a mechanism to facilitate the creation of accessible graphs in research articles is just the tip of an iceberg. Obtaining a more accessible format for conference proceedings and research papers could be a first step in the direction of making accessible learning and didactical materials of STEM (Science, Technology, Engineering and Mathematics) subjects. This would provide great benefits to scholars and students with visual impairments, from primary schools to Ph.D. programmes.

In this paper we presents an experiment that aimed at investigating how existing HTML-based markup languages for scientific documents and conference proceedings can be easily extended so as to enable the automatic generation of graphs from tabular data. In particular, we have extended the Research Article in Simplified HTML (RASH) format with two tools for automatically generating graphs from CSV documents. Such two RASH extensions are based on:

• evoGraphs , a jQuery plugin that allows the creation of dynamic graphs with the capability of being accessed by screen readers; and

• D3 , the well-known Javascript application for dynamic graphs creation.

Thanks to such RASH extensions, two versions of the same document have been created, one written in RASH+evoGraphs, the other one by means of RASH+D3. Such documents contain six different graphs obtained from the same CSV data. Then, these documents have been tested by one of the authors of this paper, who is a screen reader user due to his visual impairments. He compared these two versions by means of the most commonly used combinations of operating systems, browsers and screen readers. The outcomes highlight that only the RASH+evoGraphs extension addressed all the tested accessibility-oriented requirements in a satisfactory manner.

The rest of the paper is structured as follows. presents some related work about the accessibility of PDF documents and the most common barriers that can be faced by visually impaired users in accessing scientific documents and conference proceedings. introduces RASH as the HTML-based format we used in our experiment. The integration of evoGraphs and D3 in RASH is explained in , as well as the experiments we have conducted and the discussion of the related outcomes. Finally, concludes the paper with some final remarks and future works.

Background and Related Work

Several works have proposed investigations on the accessibility of scientific documents, with particular regards to conference proceedings formats and graphical information, when used to represent results of research activities. In general, assistive technologies perform satisfactorily with regard to texts, even if some studies report that the Portable Document Format is not easily manageable in terms of making a research paper accessible to anyone . It is worth noting that if research publications are not accessible to everyone, some readers could be excluded (ethical issue) and the impact of these research results limited (shareability issue).

Even if PDF was created to enable a cross-platform readability of documents, the content of PDF files is not as inherently accessible as other publishing formats, such as HTML. In fact, PDF documents are unreadable by screen readers if they are not correctly annotated, and this prevents readers with disabilities from accessing their content . A first serious attempt in proving accessible PDF documents was done in 2012, when the International Standard Organisation (ISO) has proposed a PDF extension called PDF/Universal Accessibility standard (PDF/UA), described in the ISO 14289 specification . The specification includes the technical requirements for a PDF document to be accessible for a wide variety of processing systems, including assistive technologies. The content creators can referee to PDF/UA to improve the accessibility of their PDF documents by providing accurate tags or textual alternatives . However, this is not enough to guarantee fully accessible PDFs. Automatic checkers can verify if a PDF document meets the technical and syntactical requirements, but they cannot evaluate if a section is correctly tagged or if a figure is accurately described . This means that, similarly to the Web content, both automatic and manual evaluations have to be conducted with the aim of checking if a document meets the PDF/UA standard . The community of researchers involved in the topic of accessibility is currently working on alternative solutions, e.g., by supporting research paper authors in creating accessible PDF documents and in checking their accessibility .

Other textual formats could be exploited with the aim of making conference proceedings and research documents more accessible to a wider audience, including people with visual impairments. Examples are the format used by dokieli dokieli, which is based on HTML syntax, and ScholarlyMarkdown , which is based on the Markdown syntax. In this paper, we use RASH ( ) , which is based on HTML syntax and offers a consistent support to authors, by including several conversion tools from well known word processors (e.g., OpenOffice) to publishing-oriented formats (e.g., LaTeX).

While some positive results have been obtained in making textual content accessible, assistive technologies still have a long way to go as far as graphs are concerned. In scientific papers, graphs can play a very important role, since they can vehicle results and (often tabular) data coming from the research activities in an aggregated and structured way . Several works investigated how to improve the accessibility of graphs and graphical information to users with visual impairments. Some studies focus on specific kind of graphical information, such as maps , floor plans , and chemical diagrams . Some other works investigated how to collect and provide better textual alternatives to graphics and geographical maps, by means of tables too and on how to adapt the information to users’ preferences and needs .

One of the main goals for improving the accessibility of scientific documents is the adequate representation of graphs by screen readers . Some plugins and browser add-ons support authors in equipping their content with textual alternatives for the graphical information. One of the implementations we present in Section IV of this paper is based on one of them: evoGraphs . EvoGraphs is a jQuery plugin that allows the creation of dynamic and stylish graphs with the capability of being screen reader friendly. The plugin is fully customizable to the needs of the user, and it is comprised of HTML, CSS, and jQuery components. The main idea at the basis of evoGraphs is to equip the textual description with the elements of a graph plus additional information for augmenting the comprehension of the visualized data, such as the specification of the graph type and additional statistical measures (i.e. median and standard deviation).

The Research Articles in Simplified HTML Format

The Research Articles in Simplified HTML (RASH) format is a markup language that restricts the use of HTML to only 31 elements for writing academic research articles . In order to improve the user experience in terms of accessibility of such HTML-based papers, RASH reuses some items from the W3C Accessible Rich Internet Applications 1.1 . Moreover, it exploits several roles introduced in the Digital Publishing WAI-ARIA Module 1.0 , which allows digital publisher to apply the structural semantics they need to drive the authoring process while getting accessibility.

Concerning its theoretical foundations, RASH is entirely based on a strong theory on structural patterns for XML documents . The systematic use of these structural patterns is an added value in all stages of the documents’ lifecycle: they can be guidelines for creating well-engineered documents and vocabularies, rules to extract structural components from legacy documents, indicators to study to what extent documents share design principles and community guidelines.

From a development point of view, any RASH document begins as a simple (X)HTML5 document, by specifying the generic HTML DOCTYPE followed by the document html element. On the one hand, the head element of a RASH document must/should include some information about the paper, i.e., the paper title (title element), at least one author and other related information (i.e., affiliations, keywords, categories, by using the meta and link elements). On the other hand, the body element mainly contains textual elements (e.g., paragraphs, emphases, links, and quotations) for describing the content of the paper, and other structural elements (e.g., abstract, sections, references, and footnotes) used to organize the paper in appropriate blocks and to include specific complex structures (e.g., figures, formulas, listings, and tables).

RASH is accompanied by an extended Framework , which includes, in addition to the language, documentation and writing/conversion/extraction tools for facilitating to write and manage academic articles in RASH . Some of these tools are actually included in the RASH Online Conversion Service (ROCS) , which is a Python web application based on web.py that allows one to convert an ODT document (written according to the aforementioned guidelines) into RASH, and from RASH into LaTeX compliant with the most commonly used publisher formats.

Accessibility of Automatically-Generated Graphs

In this section, we present the outcomes of an experiment we prepared for assessing the quality of accessibility of automatically-generated graphs that visualize tabular information stored in CSV documents. To this end, we have created two different extensions of RASH: one based on evoGraphs , and another one based on D3 . introduces such extensions. In , we present the criteria that were used for measuring the accessibility each implementation provided, according to different operating systems, browsers, and screen readers. discusses the outcomes of our analysis.

Conclusions

In this paper, we have presented two extensions of the RASH format that integrates evoGraphs and D3, with the aim of automatically generating graphs from tabular data. We have reported the results of an experiment we have conducted with the aim of evaluating it those graphs are accessible to screen readers users. According to such outcomes, the RASH extension with evoGraphs gave the best results in terms of accessibility.

While the topic discussed in this paper is an important issue to address for making scientific papers more accessible, this is only a smaller part of a bigger picture. This is the case if we consider the even more complex problem of making accessible to screen reader users the scientific content of a document (e.g., including formulas and figures). While some studies and debates have been conducted on this subject, we do not have yet any authoring tool that allows to generate such accessible contents without a deep understanding of the issue and of the different available technologies that could (and should) be used to improve the accessibility of scientific contents. Finding a feasible solution would provide great benefit to a wider audience, which is represented by early scholars, students, and professors with visual impairments. Moreover, an authoring tool to produce such content would support in an effective way even those authors who are not familiar with accessibility technicalities.

We firmly believe that RASH has a great potential in this area and could be leveraged both by students and educators in different education grades ranging from early scholarship to academic courses as an important tool to produce scientific contents in a way that is visually appealing and accessible at the same time. Thus, our future research efforts will focus on making RASH more suitable for this purpose, by including evoGraphs within the RASH Framework and by either developing or extending existing approaches for dealing with mathematical contents in an accessible way.

This paper is also available in RASH at https://w3id.org/people/essepuntato/papers/rash-ads2017.html.

Acknowledgments

The authors want to thank Ather Sharif, who is the main contributor of evoGraphs, and Andrea Zamberletti and Riccardo Pezzolati, for their precious support in integrating evoGraphs and D3 in RASH.

References

1. Caldwell, B., Cooper, M., Guarino Reid, L., Vanderheiden, G. (2008). Web Content Accessibility Guidelines (WCAG) 2.0. W3C Recommendation 11 December 2008. https://www.w3.org/TR/WCAG20/

2. Diggs, J., Craig, J., McCarron, S., Cooper, M. (2015). Accessible Rich Internet Applications (WAI-ARIA) 1.1. W3C Working Draft 19 November 2015. http://www.w3.org/TR/wai-aria-1.1/

3. International Standard Organisation (2012). ISO 14289-1:2014 - Document Management Applications - Electronic Document File Format Enhancement for Accessibility - Part 1: Use of ISO 32000-1, PDF/UA-1. http://www.iso.org/iso/home/store/catalogue_ics/catalogue_detail_ics.htm?csnumber=64599

4. U.S. Rehabilitation Act Amendments (1998). Section 508. Available at: http://www.webaim.org/standards/508/checklist

5. Italian Parliament (2004). Law nr. 4 – 01/09/2004. The Stanca Act. Official Journal nr. 13 – 01/17/2004, January 2004. Available at http://www.camera.it/parlam/leggi/04004l.htm

6. Brady, E., Zhong, Y., Bigham, J.P. (2015) Creating accessible PDFs for conference proceedings. In Proceedings of the 12th Web for All Conference (W4A 2015), ACM, pages 34-37.

7. Mirri, S., Muratori, L.A., Salomoni, P. (2011). Monitoring accessibility: large scale evaluations at a geo-political level. In Proceedings of the 13th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2011): 163-170. New York, New York, USA: ACM. http://dx.doi.org/10.1145/2049536.2049566

8. Armano, T., Capietto, A., Illengo, M., Murru, N., Rossini, R. (2014). An overview on ICT for the accessibility of scientific texts by visually impaired students. In Proceedings of the SIREM–SIE–L Conference 2014: 119-122.

9. Sorge, V., Cervone, D., Krautzberger, P. (2016). Employing Semantic Analysis for Enhanced Accessibility Features in MathJax. In Proceedings of the 13th IEEE International Conference on Consumer Communications and Networking Conference (CCNC 2016). Washington, District Columbia, USA: IEEE.

10. Sorge, V., Lee, M., Wilkinson, S. (2015). End-to-end solution for accessible chemical diagrams. In Proceedings of the 12th Web for All Conference (W4A 2015). New York, New York, USA: ACM. http://dx.doi.org/10.1145/2745555.2746667

11. Lazar, J., Allen, A., Kleinman, J., Malarkey, C. (2007). What frustrates screen reader users on the web: A study of 100 blind users. International Journal of Human-Computer Interaction, 22 (3): 247-269. http://dx.doi.org/10.1080/10447310709336964

12. Di Iorio, A., Nuzzolese, A. G., Osborne, F., Peroni, S., Poggi, F., Smith, M., Vitali, F., Zhao, J. (2015). The RASH Framework: enabling HTML+RDF submissions in scholarly venues. In Proceedings of the poster and demo session of the 14th International Semantic Web Conference (ISWC 2015). http://ceur-ws.org/Vol-1486/paper_72.pdf

13. Sharif, A., Forouraghi, B., Gong, S. (2015). evoGraphs - A jQuery Plugin to Create Web Accessible Graphs. In Proceedings of The Graphical Web Conference 2015.

14. Bostock, M., Ogievetsky, V., Heer, J. (2011). D3 Data-Driven Documents. IEEE Transactions on Visualization and Computer Graphics, 17 (12): 2301-2309. http://dx.doi.org/10.1109/TVCG.2011.185 D³ Data-Driven Documents. IEEE Trans. Vis. Comput. Graph. 17(12): 2301-2309 (2011)

15. Cooper, M., Kirkpatrick, A., O'Connor, J. (2014). PDF Techniques for WCAG 2.0. W3C Working Group Note 8 April 2014. https://www.w3.org/TR/2014/NOTE-WCAG20-TECHS-20140408/pdf.html

16. Drümmer, O., Chang, B. (2014). PDF/UA in a Nutshell: Accessible documents with PDF. Online available at: http://www.pdfa.org/publication/pdfua-in-a-nutshell/

17. Uebelbacher, A., Bianchetti, R., Riesch, M. (2014). PDF Accessibility Checker (PAC 2): The First Tool to Test PDF Documents for PDF/UA Compliance. In Computers Helping People with Special Needs: 197-201. Cham, Switzerland: Springer. http://dx.doi.org/10.1007/978-3-319-08596-8_31

18. Capadisli, S., Guy, A., Auer, S., Berners-Lee, T. (2015). dokieli: decentralised authoring, annotations and social notifications. http://csarven.ca/dokieli (last visited September 30, 2016)

19. Lin, T. T. Y., Beales, G. (2015). ScholarlyMarkdown Syntax Guide. Guide, 31 January 2015. http://scholarlymarkdown.com/Scholarly-Markdown-Guide.html.

20. Mirri, S., Prandi, C., Salomoni, P., (2014). A context-aware system for personalized and accessible pedestrian paths. In Proceedings of the IEEE International Conference on High Performance Computing and Simulation (HPCS 2014): 833-840. Washington, District Columbia, USA: IEEE. http://dx.doi.org/10.1109/NGMAST.2014.59

21. Mirri, S., Prandi, C., Salomoni, P., (2016). Personalizing Pedestrian Accessible Way-finding with mPASS. In Proceedings of the 13th IEEE International Conference on Consumer Communications and Networking Conference (CCNC 2016). Washington, District Columbia, USA: IEEE.

22. Goncu, C., Madugalla, A., Marinai, S., Marriott, K. (2015). Accessible on-line floor plans. In Proceedings of the 24th International Conference on World Wide Web (pp. 388-398). International World Wide Web Conferences Steering Committee.

23. Ferretti, S., Mirri, S., Prandi, C., Salomoni, P., (2015). Automatic web content personalization through reinforcement learning. Journal of Systems and Software (November 2016), volume 121: 157-169.

24. Salomoni, P., Prandi, C., Roccetti, M., Nisi, V., and N. Jardim Nunes (2015). Crowdsourcing Urban Accessibility:: Some Preliminary Experiences with Results. In Proceedings of the 11th Biannual Conference on Italian SIGCHI Chapter (CHItaly 2015), ACM, 2015, pp. 130-133.

25. Ferres, L., Verkhogliad, P., Lindgaard, G., Boucher, L., Chretien, A., Lachance, M. (2007, October). Improving accessibility to statistical graphs: the iGraph-Lite system. In Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility (pp. 67-74). ACM.

26. Garrish, M., Siegman, T., Gylling, M., McCarron, S. (2015). Digital Publishing WAI-ARIA Module 1.0. W3C Working Draft 19 November 2015. https://www.w3.org/TR/dpub-aria-1.0/

27. Di Iorio, A., Peroni, S., Poggi, F., Vitali, F. (2014). Dealing with structural patterns of XML documents. Journal of the American Society for Information Science and Technology, 65(9): 1884–1900. http://dx.doi.org/10.1002/asi.23088

28. Constantin, A., Peroni, S., Pettifer, S., Shotton, D., Vitali, F. (2016). The Document Component Ontology (DoCO). Semantic Web, 7 (2): 167-181. http://dx.doi.org/10.3233/SW-150177

29. Di Iorio, A., Gonzalez-Beltran, A., Osborne, F., Peroni, S., Poggi, F., Vitali, F. (2016). It ROCS! The RASH Online Conversion Service. To appear in the Companion Volume of the Proceedings of the 25th International World Wide Web Conference (WWW 2016). OA version available at https://rawgit.com/essepuntato/rash/master/papers/rash-poster-www2016.html

30. WebAIM Screen Reader Survey #6 results. http://webaim.org/projects/screenreadersurvey6/ (last visited September 30, 2016)

31. NVDA and Windows 10, 2015 http://www.nvaccess.org/win10/

32. Usage of Web Browsers. https://en.wikipedia.org/wiki/Usage_share_of_web_browsers (last visited September 30, 2016)