The global environmental agenda urgently needs a semantic web of knowledge
Abstract Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, infor...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-02-01
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| Series: | Environmental Evidence |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13750-022-00258-y |
| _version_ | 1819277853841162240 |
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| author | Stefano Balbi Kenneth J. Bagstad Ainhoa Magrach Maria Jose Sanz Naikoa Aguilar-Amuchastegui Carlo Giupponi Ferdinando Villa |
| author_facet | Stefano Balbi Kenneth J. Bagstad Ainhoa Magrach Maria Jose Sanz Naikoa Aguilar-Amuchastegui Carlo Giupponi Ferdinando Villa |
| author_sort | Stefano Balbi |
| collection | DOAJ |
| description | Abstract Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, information remains compartmentalized to pre-defined scales and fields, rarely building its way up to collective knowledge. Today's distributed corpus of human intelligence, including the scientific publication system, cannot be exploited with the efficiency needed to meet current evidence synthesis challenges; computer-based intelligence could assist this task. Artificial Intelligence (AI)-based approaches underlain by semantics and machine reasoning offer a constructive way forward, but depend on greater understanding of these technologies by the science and policy communities and coordination of their use. By labelling web-based scientific information to become readable by both humans and computers, machines can search, organize, reuse, combine and synthesize information quickly and in novel ways. Modern open science infrastructure—i.e., public data and model repositories—is a useful starting point, but without shared semantics and common standards for machine actionable data and models, our collective ability to build, grow, and share a collective knowledge base will remain limited. The application of semantic and machine reasoning technologies by a broad community of scientists and decision makers will favour open synthesis to contribute and reuse knowledge and apply it toward decision making. |
| first_indexed | 2024-12-24T00:02:43Z |
| format | Article |
| id | doaj.art-801db7030c9b4a1694062ba3ea895cd0 |
| institution | Directory Open Access Journal |
| issn | 2047-2382 |
| language | English |
| last_indexed | 2024-12-24T00:02:43Z |
| publishDate | 2022-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Environmental Evidence |
| spelling | doaj.art-801db7030c9b4a1694062ba3ea895cd02022-12-21T17:25:05ZengBMCEnvironmental Evidence2047-23822022-02-011111610.1186/s13750-022-00258-yThe global environmental agenda urgently needs a semantic web of knowledgeStefano Balbi0Kenneth J. Bagstad1Ainhoa Magrach2Maria Jose Sanz3Naikoa Aguilar-Amuchastegui4Carlo Giupponi5Ferdinando Villa6Basque Centre for Climate Change (BC3), Scientific Campus of the University of the Basque CountryU.S. Geological Survey, Geosciences and Environmental Change Science CenterBasque Centre for Climate Change (BC3), Scientific Campus of the University of the Basque CountryBasque Centre for Climate Change (BC3), Scientific Campus of the University of the Basque CountryWorld Wildlife FundDepartment of Economics, Ca’ Foscari University of VeniceBasque Centre for Climate Change (BC3), Scientific Campus of the University of the Basque CountryAbstract Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, information remains compartmentalized to pre-defined scales and fields, rarely building its way up to collective knowledge. Today's distributed corpus of human intelligence, including the scientific publication system, cannot be exploited with the efficiency needed to meet current evidence synthesis challenges; computer-based intelligence could assist this task. Artificial Intelligence (AI)-based approaches underlain by semantics and machine reasoning offer a constructive way forward, but depend on greater understanding of these technologies by the science and policy communities and coordination of their use. By labelling web-based scientific information to become readable by both humans and computers, machines can search, organize, reuse, combine and synthesize information quickly and in novel ways. Modern open science infrastructure—i.e., public data and model repositories—is a useful starting point, but without shared semantics and common standards for machine actionable data and models, our collective ability to build, grow, and share a collective knowledge base will remain limited. The application of semantic and machine reasoning technologies by a broad community of scientists and decision makers will favour open synthesis to contribute and reuse knowledge and apply it toward decision making.https://doi.org/10.1186/s13750-022-00258-yGlobal challengesSustainabilityArtificial intelligenceSemanticsKnowledge integration and synthesis |
| spellingShingle | Stefano Balbi Kenneth J. Bagstad Ainhoa Magrach Maria Jose Sanz Naikoa Aguilar-Amuchastegui Carlo Giupponi Ferdinando Villa The global environmental agenda urgently needs a semantic web of knowledge Environmental Evidence Global challenges Sustainability Artificial intelligence Semantics Knowledge integration and synthesis |
| title | The global environmental agenda urgently needs a semantic web of knowledge |
| title_full | The global environmental agenda urgently needs a semantic web of knowledge |
| title_fullStr | The global environmental agenda urgently needs a semantic web of knowledge |
| title_full_unstemmed | The global environmental agenda urgently needs a semantic web of knowledge |
| title_short | The global environmental agenda urgently needs a semantic web of knowledge |
| title_sort | global environmental agenda urgently needs a semantic web of knowledge |
| topic | Global challenges Sustainability Artificial intelligence Semantics Knowledge integration and synthesis |
| url | https://doi.org/10.1186/s13750-022-00258-y |
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