Introduction to Panthaion

Get started publishing and discovering climate datasets in less than an hour.

Scientists, researchers, and data enthusiasts use Panthaion (panthaion.org) to publish, share, and discover verified climate and environmental datasets, complete with automated QA scoring and citable DOIs. Whether you're uploading your first field survey or searching for decades of atmospheric records, this guide will walk you through everything you need to get started.

Who is this for: Researchers, climate scientists, data analysts, students, and open-data contributors. What you'll learn: We'll introduce the Panthaion Ecosystem (dataset marketplace), how quality scoring works, and how to publish your first dataset. What you'll build: A published, QA-scored dataset with a citable DOI, ready for the community to discover and use. Prerequisites: None. You only need a free Panthaion account. How long: This guide takes less than one hour to complete.

In this guide you will create a Panthaion account, explore the Ecosystem, prepare your dataset, upload and publish it, read your QA report, then cite and share your dataset.

Step 1: Create Your Account

Go to panthaion.org on a desktop or laptop, as Panthaion is optimised for full-size browsers. Click "Publish a Dataset" in the top-right corner, fill in your name, email, and a password, then confirm your email address. That's it, you now have a Panthaion account.

Tip: Use your institutional email address if you have one. It helps other researchers find and trust your work.

Step 2: Explore the Ecosystem

Before publishing, spend a few minutes browsing the Ecosystem at panthaion.org/marketplace, Panthaion's dataset marketplace. Datasets are organised into six themes: Ocean and Marine, Atmosphere, Land and Forests, Energy Systems, Urban Climate, and Biodiversity. Browsing by theme is the quickest way to find work related to your own.

Every dataset on Panthaion carries a QA Score from 0 to 100, calculated automatically across four dimensions: Completeness (are all expected fields present and populated?), Accuracy (do values fall within expected ranges?), Consistency (are units, formats, and naming conventions uniform?), and Timeliness (is the dataset current and regularly updated?). A score of 90 or above is considered Excellent and publication-ready. 75 to 89 is Good. 60 to 74 is Fair but usable.

Step 3: Prepare Your Dataset

Panthaion accepts datasets in Parquet format, which is recommended for large datasets, as well as CSV and other tabular formats. Before you upload, check that your data is in a supported format, that column headers are descriptive and use consistent naming conventions (for example temperature_celsius rather than temp), that units are documented, and that no personally identifiable information is included.

It also helps to have the following metadata ready before you start the upload form: a clear, descriptive title; the country or region the data covers; the timeframe (start date to end date); the original data source or collection methodology; one of Panthaion's six themes; three to five keyword tags; and whether you want Open Access or restricted access. Open Access maximises discoverability.

Step 4: Upload and Publish

From any page on Panthaion, click "Publish a Dataset". Drag and drop your file or click to browse. Fill in the metadata form, select a theme, add your tags, and choose your access level. Open Access datasets are freely downloadable; restricted datasets require approval from you before others can download. When you're ready, click "Submit for Review".

Panthaion will now run automated quality analysis on your dataset. This typically takes a few seconds to a few minutes depending on file size.

Step 5: Read Your QA Report

Once analysis is complete you'll receive a QA Report covering your overall score, a per-dimension breakdown across Completeness, Accuracy, Consistency, and Timeliness, a list of flagged issues identifying specific columns or rows that triggered warnings, and recommendations for fixes.

If your score is below 75, consider filling in missing values or documenting why they're absent, standardising column names and units, and adding a methodology note that explains any outlier values. You can re-upload a revised file at any time to refresh the QA score before your dataset enters the curation queue.

Step 6: Cite and Share Your Dataset

Once your dataset passes expert curation it will be published to the Ecosystem with a DOI, a permanent citable identifier. Your citation will follow the format: Your Name (year). Dataset Title [Data set]. Panthaion. https://doi.org/10.XXXXX/panthaion.XXXXXX

Copy your DOI and include it in papers, reports, and supplementary materials. You can also share the direct link from your dataset page, or head to Kaleidoscope at panthaion.org/forums to let the community know about your data.

What's next?

Now that you've published your first dataset, you can analyse datasets in-platform using Panthaion's built-in tools to explore data and log each step of your analysis workflow. You can follow themes to stay up to date when new datasets are added in your area of research, join discussions on Kaleidoscope, or explore structured learning paths at panthaion.org/skills.

Troubleshooting

If your upload fails, check that your file is in a supported format and under the maximum file size. If the problem persists contact support@panthaion.org.

If your QA score is lower than expected, open the full QA report to see which dimensions were flagged. The most common issues are inconsistent column naming and missing values in key fields.

If your dataset hasn't been published yet, expert curation takes time. Check your email for updates from the Panthaion team. If it's been more than a week, reach out to support.

If you're on a mobile device and the site isn't loading properly, Panthaion is built for desktop and laptop browsers. Open the site on a full-size browser for the best experience.

Resources

panthaion.org
Ecosystem: panthaion.org/marketplace
Kaleidoscope community forum: panthaion.org/forums
Skills: panthaion.org/skills
Support: support@panthaion.org
LinkedIn: linkedin.com/company/panthaion

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