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Open Distributed Scientific Annotations Cloud

Each reader of scientific paper can publish their annotations to a distributed public annotations cloud, others can load as they read, and discuss.
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So, let's say you are reading a paper, have ideas and annotations during the process of reading. You click (or point) to the location, where you want to add an annotation. The system takes the context of the location on the paper (e.g., the reader extracts large enough context of surrounding words or sentences, which uniquely identifies the location, and allows later display the same annotation around the same text in other formats - be it HTML on the web, or other. If that's a picture, then the picture features are extracted via, and the pixel location, allowing to display the same annotation on top of the same image in other formats). Essentially, we would have the context IDs and coordinates with context associated with feature sets, with 1:1 correspondence between context IDs and feature sets, and 1:many correspondence between context ID and annotation.

Then, who-ever reads the paper, in what-ever reader, they could load public annotations, browse their history. This would be nice to have a conversation per annotation. E.g., each annotation creates a possibility for thread of comments. Inside the comments, you could refer to other annotations.

Moreover, each paper would have its paperid generated based on the feature extraction from the paper's text, especially title, summary, and, if there exists, just use the DOI. It seems good to make such system as widely usable as possible, not just for scientific papers, but for any PDFs in general.

Hopefully, this would make reading papers not a lonely activity at all, and cross-pollination of ideas lead to many new developments.

[Cross-posted from the Infinity Project.]

Mindey, Aug 29 2016

The Infinity Project http://infty.xyz/g/68/en
Problem: "Academic research papers are hard to discuss on-line." [Mindey, Aug 29 2016]

Memex https://en.wikipedia.org/wiki/Memex
You're almost describing some aspects of the Memex [hippo, Aug 30 2016]

[link]






       > allowing to display the same annotation on top of the same image in other formats   

       I assume you mean in other formats of your annotation, and not in other formats of the image. If so what formats did you have in mind?   

       And thanks for introducing me to infty.
pashute, Aug 30 2016
  

       [pashute], yes, exactly. I mean, in other formats of the document. However, since the image quality and way of embedding might be different in those formats (e.g., someone might embed an image as an .esp into LaTeX document, while leave it as a JPEG in a HTML document), we would probably have to extract the picture features form what-ever the format image is in, and compare the features rather than raw images.
Mindey, Aug 30 2016
  

       // extract the picture features form what-ever the format image is in, and compare the features rather than raw images. //   

       You want a perceptual hash.
notexactly, Aug 31 2016
  

       One would think that this would also work well on things like Youtube videos, and in fact would be working well given that the mechanism is set up.   

       Take a look sometime at the annotations the public produces and appends to Youtube videos.
bungston, Aug 31 2016
  

       The problems with YouTube's comments are these:   

       1. YouTube ranks videos, it seems, not by difference between likes and dislikes, or percentage of likes vs. dislikes, but by TOTAL of likes and dislikes, based on the idea that controversial videos are popular, or something. Then they decided to apply the same ranking method to comments, leading to terrible comments being ranked at the top.   

       2. YouTube hides all replies to comments except the most recent two replies, until you click to see more, leading to the appearance that the only replies, even to intelligent comments, are things like "you must support Hitler then".
notexactly, Aug 31 2016
  

       So you support Hitler, then?
bungston, Aug 31 2016
  
      
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