A posteriori metadata from automated provenance tracking: Integration of AiiDA and TCOD

TL;DR

This paper presents an automated protocol that uses AiiDA and TCOD to extract and deposit comprehensive provenance metadata for computational materials science data, enhancing data findability, reproducibility, and reusability.

Contribution

It introduces a novel automated method to tag and deposit computational data with provenance metadata without manual curation, integrating AiiDA and TCOD.

Findings

Automated deposition of 170 structures with full provenance.

Extraction of metadata from over 4600 AiiDA nodes.

Enhanced reproducibility and data management in materials science.

Abstract

In order to make results of computational scientific research findable, accessible, interoperable and re-usable, it is necessary to decorate them with standardised metadata. However, there are a number of technical and practical challenges that make this process difficult to achieve in practice. Here the implementation of a protocol is presented to tag crystal structures with their computed properties, without the need of human intervention to curate the data. This protocol leverages the capabilities of AiiDA, an open-source platform to manage and automate scientific computational workflows, and TCOD, an open-access database storing computed materials properties using a well-defined and exhaustive ontology. Based on these, the complete procedure to deposit computed data in the TCOD database is automated. All relevant metadata are extracted from the full provenance information that AiiDA tracks and stores automatically while managing the calculations. Such a protocol also enables reproducibility of scientific data in the field of computational materials science. As a proof of concept, the AiiDA-TCOD interface is used to deposit 170 theoretical structures together with their computed properties and their full provenance graphs, consisting in over 4600 AiiDA nodes.