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Month: April 2018

Reply to ‘What should we build’, 23 Apr

Reply to the 22 April 2018 version of https://docs.google.com/document/d/1aj2O9pdCUZ9sc4tR-Kb0jkIzyHrOy3UdmMQa4Vujb1Q/edit#heading=h.6p6fe06beki3  

Comments:#

  • ‘Augmented HTML’ sounds really great but I’m concerned it will be confused with HTML for AR. What do you think? Maybe some other term like expanded HTML? Can we maybe tie in Rich PDF with this? It is simply so that we have a wrapper for this which can be opened by any legacy PDF reader. Or are we committing to work fully with the web, rather than documents? Or is this question off-track?
  • Questions related to Author’s role in the Scenario:#

  • “search for annotations”. Does this mean searching hypothes.is automatically? Is it based on the text in the paragraph?”Going the other way, once a given annotation is linked to from Liquid | Author, the annotation can be updated to contain a back link to the specific paragraph within Liquid | Author as a federated knowledge source.”
  • Does this mean that annotations also include citations in this model?
  • Should the hyperglossary workflow mirror that of annotations?
  • Suggestions, which we can all chip in with:#

  • I think the document should define Live Knowledge Components. I love the term but what is it? “Write a Knowledge converter that can convert the user’s Hypothes.is annotations into a live knowledge object” hints but it would be good to have a description. Sorry if I missed it.
  • The Hyperglossary should also be further defined.
  • I wonder if we should spend some time to discuss the ‘Publish’ Process. I think this is a very important step which we should likely spend an hour on.
  • So what are the explicit benefits in Doug Terms? #

    I suggest: 

  • Structured documents (xFiles)
  • High res address via hypothesis
  • Rich ViewSpecs should listed in there I think
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Liquid Projects Near Future Scenario (with Joe using the Dynamic View)

Re-introducing Joe from Doug Engelbart’s 1962 paper as a character doing knowledge work in this new, near-future environment: 

Our user, Joe, needs to write a report of some kind so therefore needs to do some background research. After searching academic journals, Joe reads and looks up terms and searches based on what he sees, all within half a second using a few keyboard shortcuts.  

[exists in Liquid | Flow] 

He then sits down at his virtual desk and writes themes and ideas for his research in a Dynamic View, along the lines of digital Post-It Notes. He moves them around as ‘nodes’ to see how they fit, grouping some and giving the groups names, connecting some with soft lines, others with strong lines and arrows, some with plain connections and others with labels. 

[Dynamic Views are the primary research component to be built inside Liquid | Author] 

In this view he can choose whether to see any of the research materials he went through, based on his annotations, keywords, who cited them, year of publication and so on, and any other relevant material.  

With a flick of the wrist he turns this dynamic view into a traditional word processing view where the nodes become nested headings of different levels.  

[exists in Liquid | Author] 

He writes out what he has found and adds citations to his assertions, including to video clips. When he writes in jargon he has the option to add terms to his hyperGlossary, allowing anyone who will read his report to access his personal definitions. 

The document grows in size and he needs help to remember where everywhere is, so Joe flips back into the Dynamic View, clicks cmd-f and types a keyword. On hitting ‘enter’ the text gets a coloured background and lines shoot out, into the paragraphs where the keyword is found–thick where many are found, thin where few are found. He decides to do a few of these, all with different colours, to better have a handle on what sections has what keyword text. He then remembers that he has saved sets of these searches and clicks to apply them. Instantly many of these search keywords appear, using colours which has meaning for him. In his case anything blueish has to do with tech, red with people, green with companies and blue with science.  

When he is in the word processing view cmd-f on a keyword instantly reformats the document to only show sentences with the keyword, allowing him quick access to context.  

[exists in Liquid | Author] 

He decides that he needs a thinking space for a sub-section so adds one with a click. He then decides this needs more than one brain so he ‘projects’ it onto the web, via a web intermedia system and invites colleagues to look at and manipulate the projection, and add annotations if they want to, or change the layout. Anything they do is reflected in his local copy but with Joe being able to choose which version to freeze into the document when he is done authoring it.  

[This is a collaborative project referred to as ‘Projected Knowledge Graphs’] 

When done, he Publishes the document as a PDF, with a ‘References’ section appended at the end, with the correct formatting of all citations  

[exists in Liquid | Author] 

Furthermore, this is a new kind of PDF, called a Rich PDF, which contains the full original document, and an HTML version with all the metadata appended, inside the PDF in such a way that anyone who only has a standard PDF reader opens and sees the standard PDF but anyone who uses software which understands Rich PDF will use the richer data versions.  

He also Publishes to his blog, which posts the work with paragraph level addressability so that someone who chooses to cite him can cite any paragraph directly, not just the whole post  

[exists in Liquid | Flow] 

Finally, the Publishing includes posting to Linked Open Research services, with all the correct metadata in place and a final copy is automatically sent to an archival quality site. 

Julia reads Joe’s document but doesn’t have the time to go through all the prose initially. She therefore dons her VR headset and chooses one of her preset views and sees Joe’s document floating in a connected space with all her other research, connected by links, keywords, jargon in the form of hyperglossary terms and more. She extracts interesting sections from the document and slings them over to Twitter where they will enter wider cyberspace, firmly rooted in the original document.

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