Enriching Earth observation datasets through semantics for climate change applications: The EIFFEL ontology
Background Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting...
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| Published in: | Open research Europe Vol. 4; p. 133 |
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| Language: | English |
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2024
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| Abstract | Background Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting and trend analysis. However, researchers and data scientists face challenges in finding appropriate EO datasets due to inconsistent metadata structures and varied keyword descriptions. This misalignment hinders the discoverability and usability of EO data. Methods To address this challenge, the EIFFEL ontology (EIFF-O) is proposed. EIFF-O introduces taxonomies and ontologies to provide (i) global classification of EO data and (ii) linkage between different datasets through common concepts. The taxonomies specified by the European Association of Remote Sensing Companies (EARSC) have been formalized and implemented in EIFF-O. Additionally, EIFF-O incorporates: 1. An Essential Climate Variable (ECV) ontology, defined by the Global Climate Observing System (GCOS), is embedded and tailored for Climate Change (CC) applications. 2. The Sustainable Development Goals (SDG) ontology is included to facilitate linking datasets to specific targets. 3. The ontology extends schema.org vocabularies and promotes the use of JavaScript Object Notation for Linked Data (JSON-LD) formats for semantic web integration. Results EIFF-O provides a unified framework that enhances the discoverability, usability, and application of EO datasets. The implementation of EIFF-O allows data providers and users to bridge the gap between varied metadata descriptions and structured classification, thereby facilitating better linkage and integration of EO datasets. Conclusions The EIFFEL ontology represents a significant advancement in the organization and application of EO datasets. By embedding ECV and SDG ontologies and leveraging semantic web technologies, EIFF-O not only streamlines the data discovery process but also supports diverse applications, particularly in Climate Change monitoring and Sustainable Development Goals achievement. The open-source nature of the ontology and its associated tools promotes rapid adoption among developers |
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| AbstractList | Background Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting and trend analysis. However, researchers and data scientists face challenges in finding appropriate EO datasets due to inconsistent metadata structures and varied keyword descriptions. This misalignment hinders the discoverability and usability of EO data. Methods To address this challenge, the EIFFEL ontology (EIFF-O) is proposed. EIFF-O introduces taxonomies and ontologies to provide (i) global classification of EO data and (ii) linkage between different datasets through common concepts. The taxonomies specified by the European Association of Remote Sensing Companies (EARSC) have been formalized and implemented in EIFF-O. Additionally, EIFF-O incorporates: 1. An Essential Climate Variable (ECV) ontology, defined by the Global Climate Observing System (GCOS), is embedded and tailored for Climate Change (CC) applications. 2. The Sustainable Development Goals (SDG) ontology is included to facilitate linking datasets to specific targets. 3. The ontology extends schema.org vocabularies and promotes the use of JavaScript Object Notation for Linked Data (JSON-LD) formats for semantic web integration. Results EIFF-O provides a unified framework that enhances the discoverability, usability, and application of EO datasets. The implementation of EIFF-O allows data providers and users to bridge the gap between varied metadata descriptions and structured classification, thereby facilitating better linkage and integration of EO datasets. Conclusions The EIFFEL ontology represents a significant advancement in the organization and application of EO datasets. By embedding ECV and SDG ontologies and leveraging semantic web technologies, EIFF-O not only streamlines the data discovery process but also supports diverse applications, particularly in Climate Change monitoring and Sustainable Development Goals achievement. The open-source nature of the ontology and its associated tools promotes rapid adoption among developers Satellites and other tools used to observe Earth provide a lot of data that can help us make decisions, like predicting the weather or understanding climate change. However, these large collections of data are often disorganized and described differently by different people, which makes it hard for scientists and researchers to find and use the information they need. To solve this problem, the paper introduces the EIFFEL Ontology (EIFF-O). This is a new system designed to organize and link Earth observation data in a way that makes it easier to find and use. It does this by creating common categories and connections between different data sets. Three important features of EIFF-O are: It focuses on climate change, helping to categorize important climate data. It connects the data to global goals for sustainable development, which helps in achieving specific environmental targets. It links these data sets to the wider internet in a way that makes them easier to share and understand. The EIFF-O system is freely available for anyone to use and comes with tools that help developers quickly implement it in their projects. This makes it easier for everyone to access and benefit from Earth observation data. Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting and trend analysis. However, researchers and data scientists face challenges in finding appropriate EO datasets due to inconsistent metadata structures and varied keyword descriptions. This misalignment hinders the discoverability and usability of EO data.BackgroundEarth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting and trend analysis. However, researchers and data scientists face challenges in finding appropriate EO datasets due to inconsistent metadata structures and varied keyword descriptions. This misalignment hinders the discoverability and usability of EO data.To address this challenge, the EIFFEL ontology (EIFF-O) is proposed. EIFF-O introduces taxonomies and ontologies to provide (i) global classification of EO data and (ii) linkage between different datasets through common concepts. The taxonomies specified by the European Association of Remote Sensing Companies (EARSC) have been formalized and implemented in EIFF-O. Additionally, EIFF-O incorporates:1.An Essential Climate Variable (ECV) ontology, defined by the Global Climate Observing System (GCOS), is embedded and tailored for Climate Change (CC) applications.2.The Sustainable Development Goals (SDG) ontology is included to facilitate linking datasets to specific targets.3.The ontology extends schema.org vocabularies and promotes the use of JavaScript Object Notation for Linked Data (JSON-LD) formats for semantic web integration.MethodsTo address this challenge, the EIFFEL ontology (EIFF-O) is proposed. EIFF-O introduces taxonomies and ontologies to provide (i) global classification of EO data and (ii) linkage between different datasets through common concepts. The taxonomies specified by the European Association of Remote Sensing Companies (EARSC) have been formalized and implemented in EIFF-O. Additionally, EIFF-O incorporates:1.An Essential Climate Variable (ECV) ontology, defined by the Global Climate Observing System (GCOS), is embedded and tailored for Climate Change (CC) applications.2.The Sustainable Development Goals (SDG) ontology is included to facilitate linking datasets to specific targets.3.The ontology extends schema.org vocabularies and promotes the use of JavaScript Object Notation for Linked Data (JSON-LD) formats for semantic web integration.EIFF-O provides a unified framework that enhances the discoverability, usability, and application of EO datasets. The implementation of EIFF-O allows data providers and users to bridge the gap between varied metadata descriptions and structured classification, thereby facilitating better linkage and integration of EO datasets.ResultsEIFF-O provides a unified framework that enhances the discoverability, usability, and application of EO datasets. The implementation of EIFF-O allows data providers and users to bridge the gap between varied metadata descriptions and structured classification, thereby facilitating better linkage and integration of EO datasets.The EIFFEL ontology represents a significant advancement in the organization and application of EO datasets. By embedding ECV and SDG ontologies and leveraging semantic web technologies, EIFF-O not only streamlines the data discovery process but also supports diverse applications, particularly in Climate Change monitoring and Sustainable Development Goals achievement. The open-source nature of the ontology and its associated tools promotes rapid adoption among developers.ConclusionsThe EIFFEL ontology represents a significant advancement in the organization and application of EO datasets. By embedding ECV and SDG ontologies and leveraging semantic web technologies, EIFF-O not only streamlines the data discovery process but also supports diverse applications, particularly in Climate Change monitoring and Sustainable Development Goals achievement. The open-source nature of the ontology and its associated tools promotes rapid adoption among developers. Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical datasets. These datasets can be integrated with in-situ data to power artificial intelligence mechanisms for accurate forecasting and trend analysis. However, researchers and data scientists face challenges in finding appropriate EO datasets due to inconsistent metadata structures and varied keyword descriptions. This misalignment hinders the discoverability and usability of EO data. To address this challenge, the EIFFEL ontology (EIFF-O) is proposed. EIFF-O introduces taxonomies and ontologies to provide (i) global classification of EO data and (ii) linkage between different datasets through common concepts. The taxonomies specified by the European Association of Remote Sensing Companies (EARSC) have been formalized and implemented in EIFF-O. Additionally, EIFF-O incorporates:1.An Essential Climate Variable (ECV) ontology, defined by the Global Climate Observing System (GCOS), is embedded and tailored for Climate Change (CC) applications.2.The Sustainable Development Goals (SDG) ontology is included to facilitate linking datasets to specific targets.3.The ontology extends schema.org vocabularies and promotes the use of JavaScript Object Notation for Linked Data (JSON-LD) formats for semantic web integration. EIFF-O provides a unified framework that enhances the discoverability, usability, and application of EO datasets. The implementation of EIFF-O allows data providers and users to bridge the gap between varied metadata descriptions and structured classification, thereby facilitating better linkage and integration of EO datasets. The EIFFEL ontology represents a significant advancement in the organization and application of EO datasets. By embedding ECV and SDG ontologies and leveraging semantic web technologies, EIFF-O not only streamlines the data discovery process but also supports diverse applications, particularly in Climate Change monitoring and Sustainable Development Goals achievement. The open-source nature of the ontology and its associated tools promotes rapid adoption among developers. |
| Author | Palau, Carlos E. Molina, Benjamin Calvo-Gallego, Jaime |
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| Keywords | Earth Observation (EO) EO taxonomy Ontology and semantics Essential Climate Variable Sustainable Development Goals Climate change mitigation and adaptation |
| Language | English |
| License | Copyright: © 2024 Molina B et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| References | (ref-11) 2022 A Kavvada (ref-24) 2020; 247 R Shibasaki (ref-4) 2009 ref-6 M Grüninger (ref-18) 1995 (ref-5) 2022 (ref-2) 2022 A Whitcraft (ref-14) 2019; 235 (ref-19) 2022 ref-16 B Molina (ref-25) 2022 (ref-7) 2022 (ref-12) 2022 (ref-1) 2022 B Molina (ref-8) (ref-9) 2022 E Gerasopoulos (ref-15) 2022; 132 N Noy (ref-17) 2001 ref-26 (ref-10) 2021 ref-22 (ref-3) 2022 ref-23 ref-20 P Patel-Schneider (ref-13) 2014 ref-21 |
| References_xml | – ident: ref-8 article-title: D3.2. report on the EIFFEL ontology – ident: ref-22 article-title: EIFF-O online demo – year: 2022 ident: ref-7 article-title: Climate and Forecast metadata conventions. – year: 2001 ident: ref-17 article-title: Ontology development 101: a guide to creating your first ontology. publication-title: Tech rep. – volume: 247 year: 2020 ident: ref-24 article-title: Towards delivering on the sustainable development goals using earth observations. publication-title: Remote Sens Environ. doi: 10.1016/j.rse.2020.111930 – year: 2022 ident: ref-2 article-title: Global Earth Observation System of Systems (GEOSS). – ident: ref-6 article-title: Understanding the common data model – year: 2022 ident: ref-5 article-title: OpenSearch. – ident: ref-21 article-title: EIFF-O DockerHub repository – volume: 235 year: 2019 ident: ref-14 article-title: No pixel left behind: toward integrating Earth Observations for agriculture into the united nations Sustainable Development Goals framework. publication-title: Remote Sens Environ. doi: 10.1016/j.rse.2019.111470 – year: 2022 ident: ref-11 article-title: Essential climate variables, GCOS taxonomy. – year: 2022 ident: ref-9 article-title: D4.3 - Assessment of Copernicus uptake (Update of the user-oriented taxonomy). – year: 2022 ident: ref-19 article-title: Linked open data for SDG statistics. – ident: ref-16 article-title: EIFF-O GitHub repository – year: 1995 ident: ref-18 article-title: Methodology for the design and evaluation of ontologies. – year: 2021 ident: ref-10 article-title: The H2020 EIFFEL project (Revealing the role of GEOSS as the default digital portal for building climate change adaptation mitigation applications). – year: 2009 ident: ref-4 article-title: Interoperability, ontology and taxonomy development for GEOSS. publication-title: Tech rep. – ident: ref-20 article-title: EIFF-O online documentation – year: 2022 ident: ref-3 article-title: Copernicus programme (European’s eyes on earth). – year: 2022 ident: ref-25 article-title: Report on the EIFFEL Ontology. – start-page: 261-276 year: 2014 ident: ref-13 article-title: Analyzing Schema.org. doi: 10.1007/978-3-319-11964-9_17 – volume: 132 start-page: 296-307 year: 2022 ident: ref-15 article-title: Earth observation: an integral part of a smart and sustainable city. publication-title: Environ Sci Policy. doi: 10.1016/j.envsci.2022.02.033 – ident: ref-23 article-title: EIFF-O (EIFFEL ontology) – year: 2022 ident: ref-12 article-title: Sustainable development goals, dag hammarskjöld library. – year: 2022 ident: ref-1 article-title: EUSPA EO and GNSS market report. publication-title: Tech rep. doi: 10.2878/94903 – ident: ref-26 article-title: Group on earth observations, GEO DAB |
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| Snippet | Background Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive... Earth Observation (EO) datasets have become vital for decision support applications, particularly from open satellite portals that provide extensive historical... Satellites and other tools used to observe Earth provide a lot of data that can help us make decisions, like predicting the weather or understanding climate... |
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| SubjectTerms | Climate change mitigation and adaptation Earth Observation (EO) eng EO taxonomy Essential Climate Variable Ontology and semantics Sustainable Development Goals |
| Title | Enriching Earth observation datasets through semantics for climate change applications: The EIFFEL ontology |
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