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Extensions

Computational Text Extension

Extensions can include time information, location information and Vint Cerf introduced the term ‘Computational Text’ summer of 2020 to cover text in a document which can be integrated with by the author’s choice, rather than by brute force in reader software. This is the type of work Bret Victor (Victor, 2010) is known for and Bruce Horn has developed decades ago. It takes on new relevance with Visual-Meta and Reader since the aspect of Visual-Meta being ‘reverse CSS’, in the words of Jakob Voß. Text or images in the body of the document can be referred to in the Visual-Meta and instructions for interactions presented. This is an early overview of computational text types, which will be elaborated on by the Future Text Initiative advisors over time at computationaltext.info

• Relative time dimensions such as ‘yesterday’, ‘tomorrow’, ‘Friday’ and so on could be stored with reference to the date and time it was typed, if the author chooses, for future reading to either automatically update the text or to allow a reader to manually or by preference specify that any dates should be from the reader’s point in time.
• Any mathematical equations, although tools external to the text can make this work.
• Names of people, places etc. can be encoded with multiple spellings or writing styles (with or without middle initial fx) and external identity servers, such as ORCID.
• Alternative versions for authoring, so that an author can toggle which paragraph or word should be used (like Final Cut Auditions).
• Images to replace text in specific views, such as company logos in a graph view or in a scrolling/search view.
• Glossary definitions which can be dynamically expanded and contracted in the text when reading, at the reader’s presence.
• Transclusions and live links to external text.
• Links which contain the entirety of what they link to, for robustness, in addition to the link.
• Geographical information behind text such as ‘here’.
• Actual computer code, if computer language is somehow and somewhere specified.

The first part shows what text in the document is referred to, followed by the date and finished with a description of what type of data it is:

“In text Reference”  “Data”  “Type of Data/location of description”<json>
[ {“name”:”8:23am, Tuesday, 13th of May 2020″, “2,208,988,800”:”typeNTP”},
{“name”:”14th & Madison, NY”, “Latitude: 40 degrees, 42 minutes, 51 seconds N”:”latlong”},
{“name”:”David Millard”, “0000-0002-7512-2710, “person”:”https://orcid.org”},
] </json>

Please keep in mind that the goal is to be able to copy and paste data across systems while specifying how it is defined and formatted, as shown in brackets above. This is about self-declaring data (to a human or translation code) visible in plain sight, it is about allowing users to copy and paste self-defining JSON data.

These can be data pods, they do not necessarily need to be part of a document. As for the specifics, that is purely a matter of implementation.

Picture the scenario: You read an ordinary PDF and you come across the time an event happened and you can click on that time and a menu of options are presented (depending on what reading software you are using), including showing exactly how long ago it was in the past (or how near in the future) and lets you copy the time and use it when you come across another time event where you can now automatically see how far apart they are in time.

Picture the same with geographical information; you can copy and paste locations and use them semantically with other locations.

Imagine coming across the names of people and having a solid link to their online presence and not having to guess who is really who.

And much, much more–this addressability creates the opportunity for rich, useful interactions.

Rights Extension

There is no reason why the Visual-Meta cannot encode the rights the author confers onto the reader, for use, re-use, transclusion and caching.

Formatting : JSON Extension for Headings

JSON can be used to augment the way headings are recorded for a more robust result, as used in The Future of Text book:

[ {“name”:”Acknowledgements”, “level”:”level1″},
{“name”:”Dear Reader of The Distant Future”, “level”:”level2″},
{“name”:”Dear Reader of Today”, “level”:”level2″},
{“name”:”Adam Cheyer”, “level”:”level2″},
{“name”:”Adam Kampff”, “level”:”level2″}, }]

JSON can also potentially be used to encode the entire document to enable advanced functions like complete reformatting of the document to suit the reader. Since the visual-meta can be very, very small, this does not have to impact the document page number significantly.

‘Stamp’ Of Provenance Extension

When a citation is done through Visual-Meta, the references can Visual-Meta represents a break in how citations are handled, by mandating that they be included in the document at the same level as the content of the document itself, leading to a solid chain from document to citation. Because this is an entirely new level of security and robustness when citing, I suggest that citations made in this way be somehow tagged in the Reference list to show its Visual-Meta origins. Maybe something like this (bold italic is just to draw attention to it for this presentation):

[24] Kitromili, S. & Jordan, J. & Millard, D., in Proceedings of the 30th ACM Conference on Hypertext and Social Media. 2019.
What is Hypertext Authoring? New York, NY, USA.
DOI: 10.1145/3342220.3343653. {Visual-Meta}