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This paper reports on the Hackathon Sessions organised at the Polar Data Forum IV (PDF IV) (20–24 September 2021), during which 351 participants from 50 different countries discussed collaboratively about the latest developments in polar data management. The 4th edition of the PDF hosted lively discussions on (i) best practices for polar data management, (ii) data policy, (ii) documenting data flows into aggregators, (iv) data interoperability, (v) polar federated search, (vi) semantics and vocabularies, (vii) Virtual Research Environments (VREs), and (viii) new polar technologies. This paper provides an overview of the organisational aspects of PDF IV and summarises the polar data objectives and outcomes by describing the conclusions drawn from the Hackathon Sessions.

This document aims to utilize schema.org for the Polar data management community. The community has agreed on and plans on implementing uniform best practices for documenting data, observing assets, and other entities. Extensive work has been conducted under both the Earth Science Information Partnership Science-on-schema.org group and the Research Data Alliance to develop approaches and guidelines for interoperable metadata practices. While the current Science-on-schema.org guidelines provide a strong technical basis for harmonised use of the schema.org vocabulary, they do not make specific requirements for minimal acceptable metadata nor for specific types of metadata requirements for key polar research use cases. This document assembles data discovery use cases and requirements for polar data discovery that represent a target set of features for the POLDER federated search system. Use cases specifically elucidate and prioritise the functional uses of the federated data discovery platform, which will in turn be used to articulate a specific list of metadata requirements needed to implement a discovery system that provides those features., This document was a collaboration of international organizations working in the POLDER working group (https://polder.info/). The majority of writing sessions to complete this task was completed at the bimonthly Polar to Global Hackathon Sessions, meeting notes and recording can be found at https://p2g-data.org/workshops

This document presents a basis for alignment of polar data policies, notably the policies and statements of the Scientific Committee on Antarctic Research (SCAR), the International Arctic Science Committee (IASC), the Sustaining Arctic Observing Networks (SAON) initiative, the Arctic Spatial Data Infrastructure, and the Southern Ocean Observing System (SOOS). The document examines the state and recent developments of global and important regional data policies, as well as technological and institutional developments that should or might be considered when forming new polar data policies. Based on this examination, we conclude by identifying a number of data management principles that can be regarded as essential to the management of polar research data and can be incorporated in all polar data policies in such a way that they are aligned with each other and with overarching global and regional data policies.

The 1st Southern Ocean Regional Workshop to provide Southern Ocean community inputs to the Science Action Plan of the UN Decade of Ocean Science was held on 16 February 2020 in San Diego, CA, USA. The workshop was held prior to the 2020 Ocean Sciences Meeting to engage diverse participation. The 30 participants, who represented 11 countries, included representatives with expertise in ocean sciences, policy, governance and science communication, from all career stages. The workshop was structured around an opening plenary session, three themed sessions with accompanying breakout groups, and a final plenary session focused on cross-cutting themes (see also Appendix I + II). The opening plenary session provided information about the UN Decade of Ocean Science. This session informed the three theme sessions that focused on a Healthy and Resilient Ocean, a Predicted Ocean, and a Sustainable Productive Ocean. These three of the six UN Ocean Decade themes were chosen as the focus of the workshop because of relevance to the Southern Ocean, and these could be addressed in a one-day workshop. The other UN Ocean Decade themes, a Clean Ocean, a Safe Ocean, and a Transparent and Accessible Ocean, were included implicitly in the discussions of these three themes. The closing plenary session addressed cross-cutting themes. Additional information about the workshop organization is provided in Appendix II. Summaries and recommendations from each of the theme-focused breakout groups and cross-cutting session follow.&nbsp

The summary of the main activities and outcomes from the SOOS Datathon held in Incheon, South Korea on May 15, 2019.

There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of workshops to encourage the creation of Metadata for Machines (M4M), enabling any self-identified stakeholder to define and promote the reuse of standardized, comprehensive machine-actionable metadata. The funders of scientific research recognize that they have an important role to play in ensuring that experimental results are FAIR, and that high quality metadata and careful planning for FAIR data stewardship are central to these goals. We describe the outcome of a recent M4M workshop that has led to a pilot programme involving two national science funders, the Health Research Board of Ireland (HRB) and the Netherlands Organisation for Health Research and Development (ZonMW). These funding organizations will explore new technologies to define at the time that a request for proposals is issued the minimal set of machine-actionable metadata that they would like investigators to use to annotate their datasets, to enable investigators to create such metadata to help make their data FAIR, and to develop data-stewardship plans that ensure that experimental data will be managed appropriately abiding by the FAIR principles. The FAIR Funders design envisions a data-management workflow having seven essential stages, where solution providers are openly invited to participate. The initial pilot programme will launch using existing computer-based tools of those who attended the M4M Workshop.

Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies. publishedVersion