Live Papers: explore the data, code and models behind published research

Live papers are public: anyone can read one and work through its resources without registering. This exercise takes you from a published article to the data underneath it.

1. Explore: Open the Live Papers platform and browse the collection. Each entry lists the associated journal article, its authors and the kinds of resource it carries. Pick a study whose topic you know something about.
2. Select and interpret: Live papers are organised into sections that structure the code, models and data behind the article. In the “Resources” sections, you could find a raw recording; a reconstructed morphology; a link to a Model or a Jupyter notebook. Ask of each one: which claim in the paper does this support, and could I check that claim from what is provided here?
3. Compare: Open a second live paper from a different group and compare how the two are put together. Some link out to community repositories such as NeuroMorpho.Org, ModelDB or Open Source Brain; others host their resources in the EBRAINS Knowledge Graph. Note which arrangement makes the study easier to follow.
4. Go further: Follow a live paper's link back to the journal article and read the corresponding figure legend alongside the interactive resource. This is the comparison the format exists to make possible.

Live papers embed viewers and simulation tools, so a resource can be examined where it sits rather than downloaded and wrestled with locally. This exercise puts each of those integrated tools to work.

1. Explore: Find a live paper containing electrophysiology recordings and open one in the built-in viewer, which is powered by the Neo Viewer service. It reads the common electrophysiology formats through Neo, so you can plot traces from a file without knowing how it was written. Step through the segments and channels of a recording and see how it relates to the figure it underpins.
2. Select and interpret: Open a neuronal reconstruction in the 3D morphology viewer. Rotate it, and look at how the dendritic tree is arranged. If the live paper also provides the model built on that morphology, look at the two together: which anatomical features did the model retain, and which did it abstract away?
3. Compare: Where a live paper offers a single-neuron model, run it in the browser through the integrated simulation service, which executes the NEURON model remotely and returns the traces. Change the stimulus and re-run. Compare the response you get against the published figure, and against the raw recording from the first step, if the study provides both.
4. Go further: Launch any Jupyter notebooks the live paper provides in the EBRAINS Collaboratory, or open a linked use case through the BSP Use Case Wizard, which sets up the environment for you. Either way the analysis runs on EBRAINS infrastructure with the data already reachable, so you can re-run the authors’ analysis and then modify it. This step needs a free EBRAINS account.

The Live Paper Builder is a form-based authoring tool: you describe your publication, add your resources section by section, and the platform renders the interactive document. No web development is involved. This exercise walks through building one from a paper you have written.

1. Start: Register for an EBRAINS account if you do not have one, then open the Live Paper Builder. Enter your article’s DOI, or upload the PDF, and the builder will extract the publication metadata (title, authors, abstract, journal, …) for you to check and correct.
2. Add your resources: Build the document section by section, one per figure, method or model as suits your paper. Each section takes a set of resources added through a widget matched to the resource type: recordings that should open in the electrophysiology viewer, morphologies for the 3D viewer, models to be made runnable, notebooks, or plain files of any format. Resources can point at material already deposited in the EBRAINS Knowledge Graph, at community repositories such as NeuroMorpho.Org or ModelDB, or at code on GitHub or another trusted repository. If you have many resources, enter them from a spreadsheet rather than one at a time. Work can be saved and resumed across sessions, either into the Knowledge Graph or as a local file.
3. Share with reviewers: Before your article is accepted, publish the live paper behind a password and give the credentials to the journal. Reviewers get the full interactive document while it stays out of public view, and their anonymity is preserved. If some of your data or models are not yet in a repository, share them through EBRAINS first.
4. Publish: On acceptance, submit the live paper for curation (https://ebrains.eu/data-tools-services/data-knowledge/share-data/models-and-software). EBRAINS checks that every resource is reachable and adequately described, moves anything that needs long-term hosting into EBRAINS archival storage, and issues a DOI so the live paper can be cited from the article itself. The finished document is stored in the Knowledge Graph, where its resources become discoverable alongside the rest of the EBRAINS ecosystem.
5. Go further: Live papers can also be generated programmatically through the Live Papers REST API. This could be useful for generating a live paper from an existing analysis pipeline.