Suchergebnisse

This presentation was given during Sustainability Research & Innovation Congress 2021 (SRI2021), 12-15 June 2021, held both online and onsite in Brisbane, Australia. This talk connected the importance of conservation to the datasets used by the communities being effected and researchers to inform approaches to conservation. Frameworks such as FAIR, CARE, and TRUST are important elements in making data usable by the involved communities. Session: Sustainability of biodiversity conservation: too expensive for humans or can we find solutions? Instruments for the conservation of biodiversity are frequently seen as counter productive for human life and prosperity. This session will provide a basis for lively discussion and knowledge-sharing using evidence-based science, the incorporation of indigenous values, and insights from practice to achieve good biodiversity conservation outcomes within our Sustainable Development Goals. Our five speakers offer different perspectives and solutions around the socio-economic factors influencing practical community and government attitudes and actions, the value of indigenous involvement, and the opportunities arising from technological innovation and knowledge-sharing. All speakers have been directly involved with members of their community affected by conservation actions. We have designed the session to stimulate thought and discussion around this important topic, enhanced by information from a prior on-line survey of conference attendees. We ask the following questions to focus our discussion: does the human community 'own' biodiversity conservation enough to make it sustainable in the long-term? What can we learn from each other? Is the cost of conservation (perceived as) too high and how can we change this? Are we able to really measure anything effectively (i.e. are the costs and benefits real or just believed) to know how we are going? How can we better engage the community to invest in conservation action and benefit from it, not just talk about it? what innovative ...

Instruments for the conservation of biodiversity are frequently seen as counter productive for human life and prosperity. This session will provide a basis for lively discussion and knowledge-sharing using evidence-based science, the incorporation of indigenous values, and insights from practice to achieve good biodiversity conservation outcomes within global Sustainable Development Goals. Our five speakers offer different perspectives and solutions around the socio-economic factors influencing practical community and government attitudes and actions, the value of indigenous involvement, and the opportunities arising from technological innovation and knowledge-sharing. All speakers have been directly involved with members of their community affected by conservation actions. We ask the following questions to focus our discussion: • does the human community 'own' biodiversity conservation enough to make it sustainable in the long-term? What can we learn from each other? • Is the cost of conservation (perceived as) too high and how can we change this? • Are we able to really measure anything effectively (i.e. are the costs and benefits real or just believed) to know how we are going? • How can we better engage the community to invest in conservation action and benefit from it, not just talk about it? • what innovative solutions and new tools are most promising? • can open science and open data initiatives help? A selection of key challenges and solutions will be presented by researchers and practitioners. The speakers offer different perspectives, from that of globally-scoping research scientists and nature conservation agency staff, to an expert in citizen science and data management. The session is facilitated by members of PARSEC (Building New Tools for Data Sharing and Reuse through a Transnational Investigation of the Socioeconomic Impacts of Protected Areas), a Belmont Forum- funded international project with partners from Brazil, France, Japan, the United States of America, and collaborators in the UK and ...

This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; Profound changes in our world are exacerbating data availability challenges at the global level, in particular between scientists and other knowledge workers from regions separated by various features including historical, financial, cultural, political aspects, aside from time and space . Very few, if any, of our present problems such as biodiversity decline, climate change, and viral pandemics stop at national, disciplinary and linguistic boundaries, yet our most vital responses to the shared problems, the information generated to analyze and derive solutions, is still siloed in different languages and locations throughout the world. It is clear that in order for us to effectively respond, we need to collaborate globally and communicate information more effectively. Globalization of research requires interoperability of our observations and experimentation systems.The use of common FAIR vocabularies, that are both human and machine readable, is a key criterion in the FAIR principles (Principle I2 of Wilkinson et al 2016 specifies '(meta)data use vocabularies that follow FAIR principles'). Using common FAIR vocabularies will enable data interoperability and the necessary meta-analyses even when data have different origins and are based on multiple vocabularies. The objective of this poster is to offer an overview of the many multi-language challenges for effective Data ...

This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; Profound changes in our world are exacerbating data availability challenges at the global level, in particular between scientists and other knowledge workers from regions separated by various features including historical, financial, cultural, political aspects, aside from time and space . Very few, if any, of our present problems such as biodiversity decline, climate change, and viral pandemics stop at national, disciplinary and linguistic boundaries, yet our most vital responses to the shared problems, the information generated to analyze and derive solutions, is still siloed in different languages and locations throughout the world. It is clear that in order for us to effectively respond, we need to collaborate globally and communicate information more effectively. Globalization of research requires interoperability of our observations and experimentation systems.The use of common FAIR vocabularies, that are both human and machine readable, is a key criterion in the FAIR principles (Principle I2 of Wilkinson et al 2016 specifies '(meta)data use vocabularies that follow FAIR principles'). Using common FAIR vocabularies will enable data interoperability and the necessary meta-analyses even when data have different origins and are based on multiple vocabularies. The objective of this poster is to offer an overview of the many multi-language challenges for effective Data ...

This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; Profound changes in our world are exacerbating data availability challenges at the global level, in particular between scientists and other knowledge workers from regions separated by various features including historical, financial, cultural, political aspects, aside from time and space . Very few, if any, of our present problems such as biodiversity decline, climate change, and viral pandemics stop at national, disciplinary and linguistic boundaries, yet our most vital responses to the shared problems, the information generated to analyze and derive solutions, is still siloed in different languages and locations throughout the world. It is clear that in order for us to effectively respond, we need to collaborate globally and communicate information more effectively. Globalization of research requires interoperability of our observations and experimentation systems.The use of common FAIR vocabularies, that are both human and machine readable, is a key criterion in the FAIR principles (Principle I2 of Wilkinson et al 2016 specifies '(meta)data use vocabularies that follow FAIR principles'). Using common FAIR vocabularies will enable data interoperability and the necessary meta-analyses even when data have different origins and are based on multiple vocabularies. The objective of this poster is to offer an overview of the many multi-language challenges for effective Data ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...

IDW 2022 was hosted in Seoul, the Republic of Korea, by the Korea Institute of Science and Technology Information (KISTI), committed by the Ministry of Science and ICT, Seoul Metropolitan Government, National Library of Korea, and National Assembly Library, with the support of the Korea Research Institute of Standards and Science (KRISS), Sungkyunkwan University (SKKU), Korea Institute of Oriental Medicine and the Korea Institute of Geoscience and Mineral Resources.This landmark event brought together data scientists, researchers, industry leaders, entrepreneurs, policymakers, and data stewards from disciplines across the globe to explore how best to exploit the data revolution to improve science and society through data-driven discovery and innovation. IDW 2022 combined the 19th RDA Plenary Meeting, the biannual meeting of this international member organization working to develop and support global infrastructure facilitating data sharing and reuse, and SciDataCon 2022, the scientific conference addressing the frontiers of data in research organized by CODATA and WDS. ; International audience ; One of the challenges in Machine Learning research is to ensure that the presented and published results are sound and reliable. Reproducibility is an important step to promote open and accessible research, thereby allowing the scientific community to quickly integrate new findings and convert ideas to practice. We already went through the path of darkness: We proposed a set of recommendations ('fixes') to overcome these reproducibility challenges that a researcher may encounter in order to improve Reproducibility and Replicability (R&R) and reduce the likelihood of wasted effort. These strategies can be used as "swiss army knife" to move from DL to more general areas as they are organized as (i) the quality of the dataset (and associated metadata), (ii) the Deep Learning method, (iii) the implementation, and the infrastructure used. We identified the main challenges and constraints from these papers and presented ...