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| - Aligning communities of practice with a wider goal? | | - Aligning communities of practice with a wider goal? |
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| | - Innovation in seeing interdisciplinarity "downstack" (ie not in the front-line science/research, but in the tools that groups use). See that collaboration as also interdisciplinary. |
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| 1.) STRUCTURE & USE | | 1.) STRUCTURE & USE |
| IPCC -> claims obsidian | | IPCC -> claims in obsidian |
| beyond info artecure | | beyond info architecture |
| holy scripture | | holy scripture available for the masses |
| find new connections | | find new connections |
| index | | index |
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| What is it for open science? | | What is it for open science? |
| Mark up our grant proposals, future reuse | | Mark up our grant proposals, future reuse |
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| Semantic bibliography | | Semantic bibliography |
| | This was the first half of that project - https://abstract-poetry.fly.dev/bibliography it related various references to each other so you could see the global narrative. We never built out the ability to annotate each of the papers and how the related to the paper, or to add papers necessarily. (We have a more exploratory /searchy version of this at abstract-poetry.fly.dev/search which can more document a search process. |
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| Tremendous value vision, sustainable overhead? | | Tremendous value vision, sustainable overhead? |
| Finding the right structure | | Finding the right structure |
| Maintaining semantic bibliography for a grant is a great form of legitimate peripheral participation
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| We plan to try this out for preprints in climate. Sensemaking structure to 15,000 refs
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| === DAY 2 ===
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| question how can we use AI processing to discover non-explicit connections?
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| - claim - the simplest job to get here is to create an index.
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| question what are the venues where we can use open/interdisciplinary science?
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| - evidence - women for open climate already exists and would would support this
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| claim - we conceptualize inter-disciplinarity as multiple groups doing their primary research together.
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| - evidence - (counter to truth of claim) Django as an example. This is collaboration btwn website builders making the infrastructure. Or scikitlearn etc. None of these are collaboration on their primary activity.
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| - question - how might we ensure that these groups can collaborate on projects that aren't their direct work?
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| claim - there is a disconnect between the team level incentives and the global level need for collaborative infrastructure
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| - evidence synthesis centers couldn't resolve this algorithmically, and so simply needed to create a space where everyone came in to resolve the connections.
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| Centralized pool for resources - the university used to have machine labs or computing centers meaning that the university cuts it back bc its too costly
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| - Documenting these stories.
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| claim - Teaching mission of the university is missing, I think they should engage in teaching during setting up these resources.
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| - evidence - super computing centers used to do this, but then get's lost.
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| Research Software Engineering groups -
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| - They get attached to grants and become the software engineering groups.
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| - evidence - the escience program in UK moved into software sustainability institute.
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| - - There was an atmosphere that this was super interesting vs a dedicated national service.
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| - evidence - the grid - came out of particle physics. Everyone needs to buy into it. It's been largely overtaken by major software companies.
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| claim - libraries have attempted to make sure that you can manage all the different data but scientists need to know super deeply what the data is in itself, and a library can't actually provide this service. You NEED domain specialists. Similarly, there can't just be a 'random' person who is focused on integrating data -> they won't be able to give you this info.
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| - evidence - how platforms emerge. Coring + tipping. The breadth of view is so large that they aren't going to spot the core of the data.
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| - evidence - cambridge at the institutional level can enforce data sharing. BUT sharing it isn't necessarily what makes it useful.
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| - Claim - we're not making the most of the networks that we have right now, it feels like you need a single person who has the knowledge to share and integrate data to the 'institutional' repository and then the institutional repository can be integrated at the more global level.
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| - is there not enough interest for this to happen?
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| - claim - main motivation for open source is to reduce the maintenance cost of things we build on in the future.
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| - evidence - when you write a grant application, you write a lit review but then when you need to write an updated lit review -> you need to bring a 1.5 year out of date lit review that you haven't explored.
| | Matthew's answers to our draft questions: |
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| OPEN QUESTIONS -
| | - Research Data Alliance (RDA), Materials Research Data Alliance (MaRDA), workshops |
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| - How do we identify the goldilocks level - wide enough infrastructure to allow for everyone to be on the infrastructure, and narrow enough for specific groups to be able to customize to their ideal needs. | | -Taking interdisciplinary in a very narrow sense, an example to bridge gaps between existing materials databases is OPTIMADE. We spent 5 years devising a common API format between 15 or so existing crystal structure databases, primarily of competitors, and with varying uptake. Should now be possible for anyone, to create a database and join the federation, e.g., a new project just tripeld the number of structures available. Each database has different slants even if the quanta of data shared is common. Unclear if this is socially sustainable. Hinged on developing a lightweight federation with "shoddy" infrastructure on top of a relatively API format. |
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| - evidence - data analysis, genome searching, these are places where everyone from many disciplines come together to ensure that you have a shared tech which brings ppl together. | | - Specific example: as this data is machine-actionable, new software projects can now query all known materials, potentially significantly accelerating materials discovery. New databases can trivially join the federation, and previously "dead" data can be brought back to life by adding an API on top of it. Automated labs can exchange information. |
