As we integrate #OpenAlex data into the #Bonfire#OpenScience flavor, we're displaying familiar metrics: works count, citations, h-index, research topics, institutional affiliations...
These might be exactly what you need, or perhaps just a starting point.
What additional information would help you find collaborators or understand someone's work better?
We're opening this design process to the open science community. Share what works, what doesn't, what's missing.
@open_science
1/2

@bonfire
@open_science

Will there be a possibility to migrate from a Mastodon account to Bonfire, or OSN, as it is possible between Mastodon instances ?

It might be needed to lower the migration barrier and foster Bonfire OSN uptake.

Of course, it comes along with the possibility to migrate between Bonfire, or OSN, instances as smoothly as possible.

Any plans of thoughts on that ?

#OpenAlex#Bonfire #OpenScience

@bonfire @open_science In the German Reproducibility Network @GermanRepro, we developed an academic code of conduct: "Creating a friendly and intellectually stimulating space" (https://reproducibilitynetwork.de/coc/).

This explicitly says: "We discuss views and claims based on the evidence and the quality of arguments, not based on the status of the people making the claim, nor their personal characteristics or their academic rank."

This is the atmosphere I'd like to see at a campfire. Maybe more aspects of that CoC are inspiring for an academic Bonfire.

2/

@bonfire @open_science @GermanRepro What else could be extracted from #OpenAlex?
I would find this helpful:

1. The most recent publication/preprint of a member (as a first author, or also as coauthor?)
2. The most cited publication
3. Affiliation history: Maybe we have a common university in our history?

If your computing resources and the framework allow dyadic information (i.e., how do I relate to every member in the community):

3. What is my coauthor network distance? (I.e., how many hops do you need). If <=3, show the link.
4. What is the publication of that member that is closest to my own works? (e.g., based on embedding dimensions of title and abstract)

That is information that would foster a substantive discourse.

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As we integrate #OpenAlex data into the #Bonfire#OpenScience flavor, we're displaying familiar metrics: works count, citations, h-index, research topics, institutional affiliations...
These might be exactly what you need, or perhaps just a starting point.
What additional information would help you find collaborators or understand someone's work better?
We're opening this design process to the open science community. Share what works, what doesn't, what's missing.
@open_science
1/2

@bonfire @open_science Great that you integrate #OpenAlex! I really appreciate your efforts.

However, I am very skeptical about displaying the h-index and i10 index (and probably also about the overall citation count). With #DORA and #CoARA, we want to get away from these indexes. (They are readily available - but that's their deceptive seduction).

To stay in the analogy: At a campfire gathering, I am looking for deep (and also funny and affiliative) conversations with fellow researchers. If there is a guy shouting out his impressive h-index as a greeting, I would immediately leave.

If we try to build a utopian community place, we should not recreate the dysfunctional incentive structures of default academia.

1/

As we integrate #OpenAlex data into the #Bonfire#OpenScience flavor, we're displaying familiar metrics: works count, citations, h-index, research topics, institutional affiliations...
These might be exactly what you need, or perhaps just a starting point.
What additional information would help you find collaborators or understand someone's work better?
We're opening this design process to the open science community. Share what works, what doesn't, what's missing.
@open_science
1/2