peerreview VS ideas4

Hey everyone, I'm an experienced software engineer from an academic family. I've been aware of the problems in academic publishing for most of my life, and for the last several years I've been running headlong into the paywalls as I work on municipal policy advocacy. I've been pondering software solutions to this problem for a long time. This is exactly the sort of problem internet based software is, in theory, best suited to solving: sharing and discussing information. It should be possible to build a web platform that allows academia to share work, collect feedback, organize review that maintains quality, and find relevant papers with out relying on private, for-profit journal publishers. It should be possible to build and run a web platform that handles all of academic publishing for 1% of the current cost of for-profit publishing or less - which would (in theory) allow the universities to keep it funded while allowing it to be free to publish and free to access. Hell, it could probably be run lean enough that individual academics could fund it through small dollar donations. There's really no good reason to allow the private publishers to charge academia $11 billion a year while keeping 80% of the work locked behind paywalls. I've had several ideas for how to approach the problem, and I spent the last year building out a beta of one of them as a side project. Software development is experimental and iterative. It only works when the developers are able to get active feedback from the people most effected by the problems they are trying to solve. So I'm reaching out for feedback on the beta, and on possible paths forward. The web platform that I've built enables crowdsourced peer review of academic papers. It uses a reputation system (similar to StackExchange) and ties reputation to a field/concept tagging system. Submitted papers must be tagged with 1 - n fields, and only peers who have passed a reputation threshold in one of the tagged fields may offer review. Review is also split into two phases: pre-publish and post-publish. Pre-publish review is author driven. It's focused on collaborative, constructive feedback and uses an interface heavily inspired by both Github Pull Requests and Google Docs. Post-publish review is much closer to traditional review, and is focused on maintaining the integrity of the literature by filtering out spam, misinformation, fraud, and poorly done work. Reputation is mostly gained and lost through voting that happens during post-publish review. Reputation can also be gained by offering particularly constructive pre-publish reviews. All reviews are open and published alongside the papers. Post-publish review is on-going. That's iteration one. As much as I believe review could be crowdsourced, it seems pretty clear that going straight from what we have to this platform would be a huge leap. So I have ideas for how to build a journal overlay on top of the crowdsourced review system that would allow editors to manage teams of reviewers and run their journals through the platform. This would allow them to take advantage of the review interface, and would still give authors the benefit of being able to have a conversation with their reviewers. Authors would then be able to choose to submit their papers to one or more journals, crowdsourced review, or both. Building that out is the next project. Right now I'm working on this as a side project and an experiment -- could a web platform like this work? Would people even use it? If the answer turns out be yes, I'd love for it to become a non-profit, multi-stakeholder cooperative. Essentially independent public infrastructure similar to Wikipedia, only more transparent and more clearly democratically governed. I would love feedback on all aspects of this project - both the current crowdsourcing iteration and the thought to build a generic, open platform for diamond open access journals to run their operations through. Could you ever see yourself using something like this to publish? What about to collect pre-print review? Could you see yourself reviewing through it? What about submitting to journals through it? Are there other approaches to building a web platform that might work better? Am I barking up the wrong tree? Should I press forward, abandon, or is there a better tree? You can find the beta platform here: https://peer-review.io The source here: https://github.com/danielbingham/peerreview And more details about exactly how it works (in its current iteration) here: https://peer-review.io/about Maintaining an open roadmap here: https://github.com/users/danielBingham/projects/6/views/1

And the source code here: https://github.com/danielbingham/peerreview

Last summer I finally saved up enough runway to take some time off work and put a significant amount of time into building an MVP beta of it ( https://peer-review.io, https://github.com/danielbingham/peerreview ). I've been trying to find folks interested in trying it out and exploring whether it could work.

Hey HN,

I've been working on Peer Review for the past year. It's still in early beta (pre-0.1) but I'm looking for some early adopters to start putting it through its paces and help highlight areas I should focus on.

Peer Review is an idea I've had for years. You're probably well aware of the problems involved in academic, scientific, and scholarly publishing - HN certainly discusses them enough. Peer Review is my attempt to solve them (or a subset of them).

Peer Review combines features of Github and StackExchange to allow scholarly review to be crowd sourced to a trusted pool of peers. It does this by tying reputation to a hierarchical field tagging system. Reputation gained in children is also gained in the parents. Authors tag their papers with any fields they feel are relevant.

This means authors can tag their papers with fields higher up the hierarchy to cast a wider review net, or go lower down the hierarchy to cast a narrower one. It also enables cross-discipline review and collaboration very easily - authors simply tag their papers with the fields of both disciplines.

The review interface combines aspects of Github PRs and Google docs.

Review is split into two phases: pre-publish "review" focused on giving authors constructive critical feedback to help the improve their work and post-publish "refereeing" which looks more like traditional peer review and is the primary mechanism through which new authors gain reputation.

The whole site is built around the idea that scholars are working to collectively build the body of human knowledge and make it the best they can.

You can see the production site here: https://peer-review.io

You're welcome to explore the staging site and treat it as a sandbox, if you'd like: https://staging.peer-review.io

It's open source: https://github.com/danielbingham/peerreview

I'm doing all the development in the open as much as possible. If it gains traction, the plan is to form a non-profit around it and explore whether a web platform can be governed democratically as a multi-stakeholder cooperative and if we can solve some of the issues around large centralized platforms through that governance approach.

I'm working open source and would welcome contributions! (https://github.com/danielbingham/peerreview)

(Although, the first contribution would probably need to be getting the local working again in a new context... I've been going fast and taking on some techdebt that will need to be paid down soon.)

https://github.com/samsquire/ideas4#334-knowledgegraph-progr...

How would you do control flow and scheduling and parallelism and async efficiently with this code?

`db.save()`, `download()` are IO intensive whereas `document.query("a")` and `parse` is CPU intensive.

I think its work diagram looks like this: https://github.com/samsquire/dream-programming-language/blob...

I've tried to design a multithreaded architecture that is scalable which combines lightweight threads + thread pools for work + control threads for IO epoll or liburing loops:

Here's the high level diagram:

https://github.com/samsquire/ideas5/blob/main/NonblockingRun...

The secret is modelling control flow as a data flow problem and having a simple but efficient scheduler.

I wrote about schedulers here and binpacking work into time:

https://github.com/samsquire/ideas4#196-binpacking-work-into...

I also have a 1:M:N lightweight thread scheduler/multiplexer:

https://github.com/samsquire/preemptible-thread

My blogging/journalling setup is simple.

I just use GitHub. I just rely on the default repository view on GitHub.com

I create a README.md and add markdown headings to the bottom or to the top (bottom if its a journal, top if it's a blog) and then when I get to 100-800 I create a new repository and repeat.

https://github.com/samsquire/ideas (2013)

https://github.com/samsquire/ideas4

https://github.com/samsquire/ideas3

https://github.com/samsquire/ideas2

Thanks for posting this Ask HN question.

I journal ideas and thoughts about computers and software. I am interested in software architecture, parallelism, async, coroutines, database internals, programming language implementation, software design and the web.

https://github.com/samsquire/ideas (2013)

https://github.com/samsquire/ideas2

https://github.com/samsquire/ideas3

https://github.com/samsquire/ideas4 <-- this is recent but needs editing

https://github.com/samsquire/ideas5 <-- this is what I'm working on now

https://github.com/samsquire/startups

https://github.com/samsquire/blog <-- thoughts I want to write about, but incomplete

I use README.md on GitHub and create a heading at the bottom for each entry. I use Typora on Windows or the GitHub web interface to edit.

My deep interest is multithreaded code. For a software engineer working on business software, I'm not sure if they should be spending too much time debugging multithreaded bugs because they are operating at the wrong level of abstraction from my perspective for business operations.

I'm looking for an approach to writing concurrent code with parallelism that is elegant and easy to understand and hard to introduce bugs. This requires alternative programming approaches and in my perspective, alternative notations.

One such design uses monotonic state machines which can only move in one direction. I've designed a syntax and written a parser and very toy runtime for the notation.

https://github.com/samsquire/ideas5#56-stateful-circle-progr...

https://github.com/samsquire/ideas4#558-state-machine-formul...

The idea is inspired by LMAX Disruptor and queuing systems.

This is really good. Thank you!

I've been studying how to create an asynchronous runtime that works across threads. My goal: neither CPU and IO bound work slow down event loops.

I've only written two Rust programs but in Rust you presumably you can use Rayon (CPU scheduling) and Tokio (IO scheduling)

I wrote about using the LMAX Disruptor ringbuffer pattern between threads.

https://github.com/samsquire/ideas4#51-rewrite-synchronous-c...

I am designing a state machine formulation syntax that is thread safe and parallelises effectively. It looks like EBNF syntax or a bash pipeline. Parallel steps go in curly brackets. There is an implied interthread ringbuffer between pipes.

  states = state1 | {state1a state1b state1c} {state2a state2b state2d} | state3

This is very interesting and could lead to some futuristic programming technology.

I kind of want to plot the state space of a program to see all available states.

In my exploration of distributed systems, microservices and multithreaded systems, it is extremely helpful to try and see what potential states the system can be in. Global and local reasoning of these kinds of software is rather difficult.

I've written about value tracing but I've not heard of treating values as types. I would love to be able to see the trajectory of a value through different states.

https://github.com/samsquire/ideas4#571-value-calculus-varia...

I've never written a TLA+ specification and I'm a complete beginner to this space but I've been trying to understand the dining philosophers one. TLA+ Toolbox is aware of discrete states in the state space, which is absolutely awesome. Types can inform us about future possible valid states.

I began writing a visualisation of memory and animated the movement of memory around to try reveal patterns.

https://replit.com/@Chronological/ProgrammingRTS#index.html

If we see types or values as positions, we can create animations of the state space unfolding in front of us. This is the dream.

Great comment!

>I think late architecture is orthogonal to functional, imperative

Absolutely. From a truly architectural view, procedural, functional, and method-oriented (current OO) are really only variations on the call/return architectural style. Good and sometimes important distinctions, but not really that far apart. They are very much about computing, results from inputs. That is an appropriate architecture for fewer and fewer programs.

See Why Architecture Oriented Programming matters

https://blog.metaobject.com/2019/02/why-architecture-oriente...

and

Can Programmers Escape the Gentle Tyranny of call/return?

https://2020.programming-conference.org/details/salon-2020-p...

> its solution is higher level than even functional programming

Yes. Well, functional actually gets most of its utility from being lower level as far as paradigms go (less powerful). But yes.

> and more abstract

No. Well, yes, if expressed with current programming languages. But that's part of the problem set, not part of the solution set. We should be able to express our architectures less abstractly, more concretely, but for that we need linguistic support. Which is why I am working on that:

http://objective.st

> I want software architecture to be cheap and easy to change without breaking any existing behaviours. I don't know much research on this subject.

There was quite a bit of research at CMU, for example on packaging mismatch. Famous paper Architectural Mismatch, Why Reuse is so hard, and the 10 year follow up in 2009: Architectural Mismatch: Why Reuse is Still So Hard

https://repository.upenn.edu/cgi/viewcontent.cgi?article=107...*

Not much has changed since.

> https://github.com/samsquire/ideas4

> https://devops-pipeline.com

Will check those out. Dataflow is definitely a big part of it, with the extension of dataflow constraints (make, spreadsheets, "FRP"/"Rx"). But so is in-process REST with Storage Combinators!

And breaking down barriers between scripting and "real" programming.

Thanks for this.

I have never deployed a server mesh or used one but I am designing something similar at the code layer. It is designed to route between server components. That is, at the architecture between threads in a multithreaded system.

The problem I want to solve is that I want architecture to be trivially easy to change with minimal code changes. This is the promise and allure of enterprise service buses and messaging queues.

I have managed RabbitMQ and I didn't enjoy it.

If I want a system that can scale up and down and that multiples of any system object can be introduced or removed without drastic rewrites.

I would like to decouple bottleneck from code and turn it into runtime configuration.

My understanding of things such as Traefik and istio is that they are frustrating to set up.

Specifically I am working on designing interthread communication patterns for multithreaded software.

How do you design an architecture that is easy to change, scales and is flexible?

I am thinking of a message routing definition format that is extremely flexible and allows any topology to be created.

https://github.com/samsquire/ideas4#526-multiplexing-setting...

I think there is application of the same pattern to the network layer too.

Each communication event has associated with it an environment of keyvalues that look similar to this:

  petsserver1

Thanks for remembering me :-)

I would like things to run locally by default and then deployed to the cloud where they run.

Should be easier to debug problems if I can get the code to my machine and investigate issues with tools that my computer has such as "strace", "perf" and debug logging that I liberally apply to the build script.

In production we would have log aggregation and log search (such as ELK stack) and it is a good habit to get into the perspective of debugging production via tooling.

But CICD feels before that tooling in the pipeline. You could wire up your CICD to log to ELK but I would prefer local deployable software.

I think my focus on automating things means I want to be capable of seeing how the thing works without relying on a deployed black box in the cloud and using assumptions of how it works rather than direct investigation.

One of my journal entries is almost a lamentation of all the things that need to be done to release and use software.

This is that entry:

https://github.com/samsquire/ideas4#5-permanent-softwareplat...

I wonder if software could be deployed more like a URL that has all the information to configure a virtual machine. Docker over URL or something.