POSITION STATEMENT

As a publicly funded research agency, AIMS is committed to making all of its scientific data available as soon as practicable following creation. Access to and the provision of scientific data are fundamental mechanisms by which AIMS provides value to stakeholders and the community. Data created by AIMS' staff, students and contractors while conducting AIMS' business are assets and records of AIMS.

Whenever meaningful and practical, data custodian(s) should develop collaborative arrangements with data recipients to enhance the value of data access and provision for the custodian(s) and AIMS. In some cases, AIMS may choose to defer the public release of scientific data for the purpose of producing robust scientific products derived from those data. In such cases, the public release of data will not be deferred for more than 12 months except in extraordinary circumstances. In some cases, contractual obligations may require data to be held in confidence as per contract terms and conditions. Any limitations to access to data will be documented in publicly available metadata records.

KEY PRINCIPLES

The following key principles should guide the use and application of this policy:

1. Data are assets and records of AIMS and, as such, shall be managed in a way that preserves and enhances the value of the asset; This includes:
   • Completing a Data Management Plan during the project concept phase
   • Ensuring datasets have a metadata record in the AIMS Data Repository during the project execution phase
   • Curating and lodging datasets into the AIMS Data Repository or other approved repository before project closure.
2. Access to and the provision of data are fundamental mechanisms by which AIMS provides value to stakeholders and the community. In providing access to AIMS' data to external parties, data custodian(s) should, whenever meaningful and practical, develop collaborative arrangements with external parties to enhance the value of data access and provision for the custodian(s) and AIMS
3. All data generated and collected using public monies shall be publicly available as soon as is practicable and take no longer than one (1) year. In special circumstances, public release may be deferred but only with the approval of the Chief Research Officer or CEO
4. The scientific process takes time between the collection of the data and its subsequent publication or use. This is a fundamental part of the way that science works and this needs to be recognised in the process of managing and sharing data
5. Unless agreed otherwise in a legal contract, ownership of the data resides with AIMS and the rights of an individual or group to assert authorship/ownership/custodianship are to be recognised
6. If data were collected under contract, the availability, usage and ownership of data are determined by the terms and conditions set out in the contract. This includes internal usage
7. Data products, previews or summaries may be provided rather than 'raw' data to entice collaboration and reduce the occurrence of misleading interpretation.

MANAGEMENT OF AIMS' SCIENTIFIC DATA

To facilitate access and support knowledge discovery and innovation, AIMS' scientific data requires proper management of data assets and the application of FAIR data principles. The FAIR principles are:

1. Findable: This includes assigning a persistent identifier (like a DOI or Handle), having rich metadata to describe the data and making sure it is findable through disciplinary local or international discovery portals.
2. Accessible: This may include making the data open and available. However, the data does not necessarily have to be open (such as sensitive data). When it is not able to be open, there should be clarity and transparency around the conditions governing access and reuse.
3. Interoperable: This involves using community accepted languages, formats and vocabularies in the data and metadata.
4. Reusable: Reusable data should maintain its initial richness. For example, it should not be diminished for the purpose of explaining the findings in one particular publication. It needs a clear machine-readable license, for example, a Creative Commons License, and provenance information on how the data was formed. It should also have discipline-specific data and metadata standards to give it rich contextual information that will allow reuse.

Data Management Actions

The following fundamental data management actions apply:

1. Projects that collect or generate research data must have a Data Management Plan The project leader(s) is/are responsible for creating the Data Management Plan as part of the Project Concept Process and addressing any concerns raised by ICT or Data Systems Engineering teams including the possibility of having to budget for data storage and the work needed to prepare research data for distribution.

2. Datasets must have at least one metadata record lodged in the AIMS Data Repository. Occasionally, multiple metadata records are used to provide structure to the component parts of a dataset, particularly if usage constraints are different for different parts of the dataset. Metadata allows AIMS to keep a record of its data assets

3. The data custodian(s) is/are responsible for generating the metadata record. Metadata records must be finalized during the execution stage of the project and published with curated archived data prior to the closure stage

4. Datasets must be lodged in an approved repository to ensure data continuity and preservation and comply with;

• The data custodian(s) is/are responsible for lodging the data in the AIMS Data Repository or other approved repository
• Data formats are important to maintain accessibility over the long term. It is preferred that data files submitted to the repository are in non-proprietary, open-source software formats, and well documented.
• It is the responsibility of the data custodian(s) to ensure data integrity and accuracy.

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