# Meeting outputs



#Vorbereitung


## 1. Socialising and intro

- proving interoperability by having 2 software for same "data class" (.dar): it makes sure the implementation works.
- early feedback: difficult to implement: need to work on researcher's motivation ?(see chapte 3). "what is the point?"
- commenting is a key component, we need to talk and think about that more.

## UI mockups 



## USP

## November meeting

- goal, convince of awesome visual information, easy collaboration:
     - totally in your hands
     - In development, the way you want it

- what do we do 15min demo
    - 2 computers- 1 login, one register
    - one new figure, shared in the SFB
    - commenting on 2nd computer
    - add info 
    
    - get keywords from gin ?
    
- 30 min hands on    

## paper

## others

- social function
- R prototype + interoperability
- scicomm + context integration
-



## 2. Update project Berlin

- shiny app: 
    - working, leightweight, save .zip on dropbox, no xml implementation, based on a .rds file to access data, no installation needed
    - putative server version: no problem
    - Problem of css in iframe: will never look perfect.
    - working on a different idea: instead of the website inside the shiny app, get the shiny app inside the website. 

## 3. Communication research

The problem: the figure alone is not sufficient to make if fast for people to grasp the idea behind the figure. A caption is also not much helping as it is normally only describing the figure. 



- ABT story telling method: and but therefore. What we know (i.e introduction), the problem (scientific hypothesis), the answer (the figure ?)
- usuale intro-method-result- conclusion ?


*How to implement context integration ?*
    - a blog post (image, video and text), figure gallery is then only a thumbnail image of the blog post: miss the point we want to make, but maybe good for outreach...
    - One linked image to describe the research question + method used ):how to link + preview?
    - Use text instead of images to make it easier?


## 4. sourcedata status

- UX
- .dar standard ?


## 5. Paper, collaboration

Ideas and time plan: deadline is June 2021.


## 6. other sfb

would non-neuro sfb make more sense?

1. I do think it would be important to go through the UI mockups together and discuss some aspects that are not yet defined. As outcome of this discussions we should have an agreed priority list of features. I attach here the latest mockups for November. Important pages that need to be discussed:
- Public homepage
- Hall of fame (‘kudo-sprinkler')
- Members of a sharing group

2. Another important aspect is a comparison with related or not so related applications and services and be very clear in what way we distinguish ourselves from these platforms (eg Data Mendeley, osf.io, figshare, resourcespace, even Slideshare and google drive or dropbox). This is related to the ‘early feedback’ and defining clearly the platform. I am not sure what was meant by ‘what is the point’ in you doc. Did you mean we have to clearly articulate the "what is the point" of the platform? Or "what is the point" of getting feedback? I

3. It would also be useful to have a first plan of what kind of questions and discussions we want to elicit from the November meeting. 

4. What social function do we need first and what social networking tools would we like to see integrated? I think this is quite important but difficult and if we could outline some questions we could ask to the community or any strategy that gets us information on users’ need.

With regard to interoperability: while it a is potentially important issue, I think it is not an end in itself and I don’t think it is super urgent yet. In the interest of time, I would suggest to postpone more detailed discussion about this and the .dar format for November - December when we will have the first ’SmartFigure’ editor from Texture with concrete examples to share and discuss. Only then will the format be well defined and then we can more forward.

Maybe we could group under ‘further reaching’ discussions the following items, and go into this if we have time:
- research on scicomm, story telling, Science Matter-like publishing units
- context integration, blog post, auto-summarisation, automated linking
- centralised vs distributed interoperable application


