Data curation policy

Trustworthiness of the INFRA-ART Spectral Library

The INFRA-ART Spectral Library aims to be a trusted resource for researchers, fostering confidence in the quality and integrity of the data provided. The database is carefully assembled, curated, and maintained by application experts to ensure the highest standards of data quality.

Data curation within the INFRA-ART Spectral Library involves a range of activities aimed at enhancing, preserving, and managing spectral data throughout its lifecycle. Curation involves not only the initial efforts of data acquisition but also actions performed by authorized data curators to ensure data quality, accessibility, and long-term usability. These activities may include:

  • • Enhancing and standardizing metadata for improved discovery.
  • • Performing quality assurance checks and validating datasets.
  • • Reviewing, selecting, and organizing datasets into meaningful collections.
  • • Reformatting datasets to ensure interoperability and preservation.
  • • Creating new access points to facilitate data reuse.
  • • Ensuring ongoing maintenance and updates to maintain data relevance.

We are committed to ensuring the trustworthiness of the INFRA-ART Spectral Library by maintaining rigorous standards for data accuracy, transparency, and ethical practices. Our approach to fostering trust includes:

  • • Data Quality Assurance: All datasets undergo a thorough validation process to ensure accuracy, consistency, and reliability before being made available.
  • • Transparency: We provide detailed metadata and documentation, enabling users to understand the origin, context, and methodology behind each dataset.
  • • Compliance with FAIR Principles: We adhere to the FAIR Guiding Principles, ensuring that our data is findable, accessible, interoperable, and reusable.
  • • Ethical Data Use: We ensure that all data collection and sharing comply with ethical standards and legal requirements, protecting the integrity and confidentiality of the information.
  • • User Feedback and Continuous Improvement: We actively seek feedback from users to improve data quality, access processes, and user support services.

Level of Curation (aligned with CoreTrustSeal)

The INFRA-ART Spectral Library aspires to meet the CoreTrustSeal standards for trustworthy data repositories. Our repository is curated and maintained by domain experts, ensuring rigorous data quality and integrity. The curation level reflects our commitment to:

  • • Systematic quality checks and dataset validation.
  • • Long-term preservation and accessibility.
  • • Comprehensive metadata documentation for all datasets.

Curated Spectra

All spectra within the INFRA-ART Spectral Library are measured under optimal experimental conditions to minimize noise and maximize data accuracy. Full details on the research equipment used and experimental conditions employed for data acquisition can be found under Experimental Setup. Our spectral data curation process includes:

  • • Quality Control: Each spectrum undergoes meticulous quality checks to ensure accuracy, consistency, and adherence to scientific standards.
  • • Validation: Datasets are reviewed and verified by experts before being made available.
  • • Traceability: Each dataset is accompanied by detailed metadata to ensure reproducibility and contextual understanding.

This rigorous approach ensures researchers can rely on high-quality spectral data for their scientific inquiries and analyses.

File formats

We prioritize the use of open, widely supported file formats to ensure long-term accessibility and interoperability. The spectral file formats used include CSV, ASCII, JCAMP-DX. To support data longevity, we regularly review and migrate datasets to current, sustainable formats and maintain backups to ensure data preservation.

Metadata

A metadata record is a structured collection of metadata elements that provide essential information about a dataset or collection, facilitating its identification, discovery, interpretation, use, and management. We provide machine-readable metadata to enhance transparency, facilitate discovery, and ensure long-term data usability. Currently, our machine-readable metadata include basic descriptive information aligned with the RDA Data Repository Attributes Working Group recommendations. At the object level (for datasets), machine-readable metadata is currently under active implementation. This involves mapping dataset descriptors to relevant semantic artifacts and identifying appropriate domain-specific ontologies.

Transparency and Metadata Practices

The INFRA-ART Spectral Library supports transparency through the adoption of FAIR-enabling practices and open standards. By aligning with international best practices and guidelines for repositories and registries on exposing repository trustworthiness status and FAIR data assessments outcomes, we ensure that our data remains discoverable, transparent, and reusable over time.

  • • Metadata Exposure: We use the DCAT (Data Catalog Vocabulary) metadata schema to expose relevant metadata at the organizational and object level, following a prototype developed by FAIR-IMPACT.

Collaborative Curation and Continuous Improvement

While the importance of data curation is widely recognized, the scope and practices of curation are evolving, requiring ongoing assessment and refinement. We welcome collaboration with researchers, institutions, and other data repositories to enhance (metat)data curation and promote open science. We are committed to evolving our curation practices in response to community needs, technological advancements, and emerging standards. For inquiries, comments, or suggestions, please contact us via email at infraart@inoe.ro.