The I-ADOPT Interoperability Framework: a proposal for FAIRer observable property descriptions

<p>Global environmental challenges like climate change, pollution, and biodiversity loss are complex. To understand environmental patterns and processes and address these challenges, scientists require the observations of natural phenomena at various temporal and spatial scales and across many domains. The research infrastructures and scientific communities involved in these activities are often following their own data management practices which inevitably leads to a high degree of variability and incompatibility of approaches. Consequently, a variety of metadata standards and vocabularies have been proposed to describe observations and are actively used in different communities. However, this diversity in approaches now causes severe issues regarding the interoperability across datasets and hampers their exploitation as a common data source.</p><p>Projects like ENVRI-FAIR, FAIRsFAIR, FAIRplus are addressing this difficulty by working on the full integration of services across research infrastructures based on FAIR Guiding Principles supporting the EOSC vision towards an open research culture. Beyond these projects, we need collaboration and community consensus across domains to build a common framework for representing observable properties. The Research Data Alliance InteroperAble Descriptions of Observable Property Terminology Working Group (RDA I-ADOPT WG) was formed in October 2019 to address this need. Its membership covers an international representation of terminology users and terminology providers, including terminology developers, scientists, and data centre managers. The group’s overall objective is to deliver a common interoperability framework for observable property variables within its 18-month work plan. Starting with the collection of user stories from research scientists, terminology managers, and data managers or aggregators, we drafted a set of technical and content-related requirements. A survey of terminology resources and annotation practices provided us with information about almost one hundred terminologies, a subset of which was then analysed to identify existing conceptualisation practices, commonalities, gaps, and overlaps. This was then used to derive a conceptual framework to support their alignment. </p><p>In this presentation, we will introduce the I-ADOPT Interoperability Framework highlighting its semantic components. These represent the building blocks for specific ontology design patterns addressing different use cases and varying degrees of complexity in describing observed properties. We will demonstrate the proposed design patterns using a number of essential climate and essential biodiversity variables. We will also show examples of how the I-ADOPT framework will support interoperability between existing representations. This work will provide the semantic foundation for the development of more user-friendly data annotation tools capable of suggesting appropriate FAIR terminologies for observable properties.</p>

Towards an interoperability framework for observable property terminologies

<p>In October 2019, a new working group (InteroperAble Descriptions of Observable Property Terminology or I-ADOPT WG<sup>1</sup>) officially launched its 18-month workplan under the auspices of the Research Data Alliance (RDA) co-led by ENVRI-FAIR<sup>2</sup> project members. The goal of the group is to develop a community-wide, consensus framework for representing observable properties and facilitating semantic mapping between disjoint terminologies used for data annotation. The group has been active for over two years and comprises research communities, data centers, and research infrastructures from environmental sciences. The WG members have been heavily involved in developing or applying terminologies to semantically enrich the descriptions of measured, observed, derived, or computed environmental data. They all recognize the need to enhance interoperability between their efforts through the WG’s activities.</p><p>Ongoing activities of the WG include gathering user stories from research communities (Task 1), reviewing related terminologies and current annotation practices (Task 2) and - based on this - defining and iteratively refining requirements for a community-wide semantic interoperability framework (Task 3). Much like a generic blueprint, this framework will be a basis upon which terminology developers can formulate local design patterns while at the same time remaining globally aligned. This framework will assist interoperability between machine-actionable complex property descriptions observed across the environmental sciences, including Earth, space, and biodiversity science. The WG will seek to synthesize well-adopted but still disparate approaches into global best practice recommendations for improved alignment. Furthermore, the framework will help mediate between generic observation standards (O&M<sup>3</sup>, SSNO<sup>4</sup>, SensorML<sup>5</sup>, OBOE<sup>6</sup>, ..) and current community-led terminologies and annotation practices, fostering harmonized implementations of observable property descriptions. Altogether, the WG’s work will boost the Interoperability component of the FAIR principles (especially principle I3) by encouraging convergence and by enriching the terminologies with qualified references to other resources. We envisage that this will greatly enhance the global effectiveness and scope of tools operating across terminologies. The WG will thus strengthen existing collaborations and build new connections between terminology developers and providers, disciplinary experts, and representatives of scientific data user groups. </p><p>In this presentation, we introduce the working group to the EGU community, and invite them to join our efforts. We report the methodology applied, the results from our first three tasks and the first deliverable, namely a catalog of domain-specific terminologies in use in environmental research, which will enable us to systematically compare existing resources for building the interoperability framework. </p><p><sup>1</sup>https://www.rd-alliance.org/groups/interoperable-descriptions-observable-property-terminology-wg-i-adopt-wg<br><sup>2</sup>https://envri.eu/home-envri-fair/<br><sup>3</sup>https://www.iso.org/standard/32574.html<br><sup>4</sup>https://www.w3.org/TR/vocab-ssn/<br><sup>5</sup>https://www.opengeospatial.org/standards/sensorml<br><sup>6</sup>https://github.com/NCEAS/oboe/</p>

Using Conditional Association to Identify Locally Independent Item Sets

The ordinal, unidimensional monotone latent variable model assumes unidimensionality, local independence, and monotonicity, and implies the observable property of conditional association. We investigated three special cases of conditional association and implemented them in a new procedure that aims at identifying locally dependent items, removing these items from the initial item set, and producing an item subset that is locally independent. A simulation study showed that the new procedure correctly identified 89.5% of the model-consistent items and up to 90% of the model-inconsistent items. We recommend using this procedure for selecting locally independent item sets. The procedure may be used in combination with Mokken scale analysis.

The Distribution of Light in Galaxies

The distribution of light in galaxies is their most obvious and fundamental observable property. Hopefully it gives us some insight into their structure and dynamics. In this talk I will review some recent work on ellipticals and disk galaxies. In summary, the luminosity distributions for both these classes have several complexities, the dynamical significance of which is not yet clear. Both classes turn out to have roughly constant mean surface brightness. This may result from selection. However, if it is real, then it is important dynamically, and I will discuss this question at the end.