Exchange Data with Other Tools

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Data Interoperability with Other Tools

Overview: Pasta-ELN supports data exchange with other tools. Import data from a Nextcloud server, synchronize between Pasta-ELN installations via an elabFTW server, and upload to repositories like Dataverse and Zenodo.

Nextcloud server integration

(to be written)

Synchronize via ElabFTW server

(to be written)

Dataverse Repository

Dataverse integration allows publishing PASTA projects on the Dataverse platform. Projects are packaged as ELN files, datasets are created, metadata is published, and files are uploaded. Metadata configuration is customizable for dataset creation.

Steps to Obtain an API Key:

  1. Log in to your Dataverse instance.

  2. Navigate to "API Token" under user settings.

  3. Generate a new token.

  4. Copy and paste the key into the configuration.

Metadata Requirements:

  • title (string): defaults to the project title

  • author (string): defaults to the list of authors

  • datasetContact (string): defaults to the one in the list of authors

  • dsDescription (string): defaults to the project objective

  • keyword (list): defaults to the tags of this project

  • subject (choice): At least one subject from a controlled vocabulary

  • relatedPublications: is empty

Zenodo

Zenodo integration supports publishing PASTA projects. Metadata is customizable, and files are uploaded to Zenodo's main or testing instance (https://zenodo.org, https://sandbox.zenodo.org).

Steps to Obtain an API Key:

  1. Log in or create an account on Zenodo.

  2. Navigate to "Applications" under user settings.

  3. Generate a Personal Access Token with deposit:write and deposit:actions permissions.

  4. Copy and paste the key into the configuration.

Metadata Requirements:

  • title (string): defaults to the project title

  • creators (list of dicts: name, affiliation, orcid): defaults to the list of authors

  • description (string): defaults to the project objective

  • keywords (list of strings): defaults to the tags of this project

  • additional keys (dict): additional information

  • publication_date (YYYY-MM-DD): is today

  • upload_type (string, e.g. "dataset", "publication", etc.): is "dataset"

  • access_right (e.g. "open", "embargoed", "restricted", "closed"): is "open"

  • license (e.g. "CC-BY-4.0"): is "CC-BY-4.0"

  • related_identifiers (list of dicts: identifier, relation, resource_type): is empty

The research domain can be encoded in:

  • "keywords": ["machine learning", "neuroscience", "data science"]

  • "communities": [{"identifier": "neuroscience"}]

Comparison of Zenodo and Dataverse Terms

Zenodo

Dataverse

author

creators

datasetContact

Not required (optionally in creators or omitted)

dsDescription

description

subject keywords

communities (approx.)

keyword

keywords

publicationDate

publication_date

license (from termsOfUse)

license

language

language

series

No direct match

relatedPublications

related_identifiers

productionDate

No direct match

depositor (internal use)

Not explicitly captured

distributor

No direct match

software (if included)

upload_type = software or related_identifiers

notesText

description (as additional info)

fileDescription

File-level metadata (manually added in Zenodo)

geographicCoverage

No direct match (can go in description or keywords)

temporalCoverage

No direct match

dataSources

description (or none)

methods

description (or none)
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