Semantic linking of complex properties, monitoring processes and facilities in web-based representations of the environment

Leadbetter, Adam; Vodden, Peter N.

doi:10.1080/17538947.2015.1033483

Cited by 10 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The I-ADOPT ontology, inspired by the atomisation approach of the Complex Property Model [14] and The Scientific Variables Ontology 29 [15,16], conceives the Variable as a compound concept consisting of at least one entity (the ObjectOfInterest) and its Property, but very often includes further entities contextualizing the target object of observation. Splitting the Variable into constituent concepts enables the reuse and the mapping of these components in the context of other variables.…”

Section: Resultsmentioning

confidence: 99%

“…The datasets are enriched with machine-interpretable vocabularies representing variables measured, features, units, methods, instruments, platforms, organization, and people. The vocabularies are available publicly through the TERN Linked Data Services 14 . They are developed either in-house based on community-endorsed specifications (e.g., Australian Soil and Land Survey Field Handbook and AusPlots Rangelands Survey Protocols Manual) or imported from external semantic resources (e.g., QUDT 15 , GCMD 16 , and NERC).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Magagna¹,

Moncoiffé²,

Stoica³

et al. 2021

Preprint

View full text Add to dashboard Cite

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.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&#160;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&#8217;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.&#160;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.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Magagna¹,

Moncoiffé²,

Stoica³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The complex properties model allows system developers to produce interoperable observational data with the necessary fine grained detail to describe the properties of the observation. However, Leadbetter et al [69] argue that the existing INSPIRE complex properties extension is too abstract in terms of real-world implementation. Highlighted is the fact that ocean observations typically require a quantity and a mathematical approach to describe the observed property.…”

Section: B Inspire and Oceansites Netcdf Formatmentioning

confidence: 99%

“…Here the complex properties model is redefined as an archetype TPOT-OM-Details_COMPOUND.complex_properties.v1 (Shown as Archetype D in Fig 6). Redefining the complex properties model as an archetype allows for further managed specialization and helps address the issue (described in [69]) of the complex properties model being overly abstract.…”

Section: Archetype Modeling and Mappingmentioning

confidence: 99%

Interoperable Ocean Observing using Archetypes: A use-case based evaluation

Stacey¹,

Berry²

2018

OCEANS 2018 MTS/IEEE Charleston

View full text Add to dashboard Cite

This paper presents a use-case based evaluation of the impact of two-level modeling on the automatic federation of ocean observational data. The goal of the work is to increase the interoperability and data quality of aggregated ocean observations to support convenient discovery and consumption by applications. An assessment of the interoperability of served data flows from publicly available ocean observing spatial data infrastructures was performed. Barriers to consumption of existing standardscompliant ocean-observing data streams were examined, including the impact of adherence to agreed data standards. Historical data flows were mapped to a set of archetypes and a backward integration experiment was performed to assess the incremental benefit of using two level models to federate data streams. The outcome of the evaluation demonstrates the feasibility of building a two-level model based ocean observing system using a combination of existing open source components, the adaptation of existing standards and the development of new software tools. The automatic integration of data flows becomes possible. This technique also allows real-time applications to automatically discover and federate newly discovered data flows and observations.

show abstract

“…However, they point out that semantic heterogeneity is a hurdle which must be overcome in searching through catalogue services. Leadbetter et al (2014) and Leadbetter & Vodden (2016) demonstrate how interoperable, homogenous semantics can provide improved knowledge-building and cross-disciplinary data integration in environmental data catalogues.…”

Section: Introductionmentioning

confidence: 99%

A modular approach to cataloguing marine science data

et al. 2020

View full text Add to dashboard Cite

The ability to access and search metadata for marine science data is both a key requirement for answering fundamental principles of data management (making data Findable, Accessible, Interoperable and Reusable) and also in meeting domain-specific, community defined standards and legislative requirements placed on data publishers. This paper describes a modular data model to answer the functional requirements developed from these drivers and illustrates how this data model can be operationalised. The ability of this solution to meet the FAIR principles is then assessed.

show abstract

Semantic linking of complex properties, monitoring processes and facilities in web-based representations of the environment

Cited by 10 publications

References 12 publications

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

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

Interoperable Ocean Observing using Archetypes: A use-case based evaluation

A modular approach to cataloguing marine science data

Contact Info

Product

Resources

About