Research data currently face a huge increase of data objects with an increasing variety of types(data types,formats)and variety of workflows by which objects need to be managed across their lifecycle by data infrastru...Research data currently face a huge increase of data objects with an increasing variety of types(data types,formats)and variety of workflows by which objects need to be managed across their lifecycle by data infrastructures.Researchers desire to shorten the workflows from data generation to analysis and publication,and the full workflow needs to become transparent to multiple stakeholders,including research administrators and funders.This poses challenges for research infrastructures and user-oriented data services in terms of not only making data and workflows findable,accessible,interoperable and reusable,but also doing so in a way that leverages machine support for better efficiency.One primary need to be addressed is that of findability,and achieving better findability has benefits for other aspects of data and workflow management.In this article,we describe how machine capabilities can be extended to make workflows more findable,in particular by leveraging the Digital Object Architecture,common object operations and machine learning techniques.展开更多
1 Introduction The primary goal of the Deep-time Digital Earth project is to develop an open collaboration and data sharing platform that enables the transition of deep-time geoscientific research to a Big Data driven...1 Introduction The primary goal of the Deep-time Digital Earth project is to develop an open collaboration and data sharing platform that enables the transition of deep-time geoscientific research to a Big Data driven paradigm.Such an open platform will require the ability to effectively and efficiently access and integrate a wide variety of digital Earth data.展开更多
This study explores the possibility of opening a policy window for the adoption of the FAIR Guidelines—that data be Findable, Accessible, Interoperable, and Reusable(FAIR)—in Uganda’s e Health sector. Although the ...This study explores the possibility of opening a policy window for the adoption of the FAIR Guidelines—that data be Findable, Accessible, Interoperable, and Reusable(FAIR)—in Uganda’s e Health sector. Although the FAIR Guidelines were not mentioned in any of the policy documents relevant to Uganda’s e Health sector, the study found that 83% of the documents mentioned FAIR Equivalent efforts, such as the adoption of the National Identification Number(NIN) as a unique identifier in Uganda’s national Electronic Health Management Information System(e HMIS)(findability), the planned/ongoing integration of various information systems(interoperability), and the alignment of various projects with international best practices/standards(reusability). A FAIR Equivalency Score(FE-Score), devised in this study as an aggregate score of the mention of the equivalent of FAIR facets in the policy documents, showed that the documents at the core of Uganda’s digital health/e Health policy have the highest score of all the documents analysed, indicating that there is a degree of alignment between Uganda’s National e Health Vision and the FAIR Guidelines. Therefore, it can be concluded that favourable conditions exist for the adoption and implementation of the FAIR Guidelines in Uganda’s e Health sector. Hence, it is recommended that the FAIR community adopt a capacity building strategy through organisations with a worldwide mandate, such as the World Health Organization, to promote the adoption of the FAIR Guidelines as part of international best practices.展开更多
The FAIR principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem.Persistent,globally unique identifiers,resolvable on the Web,and associate...The FAIR principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem.Persistent,globally unique identifiers,resolvable on the Web,and associated with a set of additional descriptive metadata,are foundational to FAIR data.Here we describe some basic principles and exemplars for their design,use and orchestration with other system elements to achieve FAIRness for digital research objects.展开更多
The objective of this study was to assess the regulatory framework for health data in Indonesia in order to understand the policy context and explore the possibility of expanding the adoption and implementation of the...The objective of this study was to assess the regulatory framework for health data in Indonesia in order to understand the policy context and explore the possibility of expanding the adoption and implementation of the FAIR Guidelines,which state that data should be Findable,Accessible,Interoperable and Reusable(FAIR),in Indonesia.Although the FAIR Guidelines were not explicitly mentioned in any of the policy documents relevant to the Indonesian digital health sector,six out of the eight documents analysed contained FAIR Equivalent principles.In particular,Indonesia’s Population Identification Number(NIK)has the potential,as a unique identifier,to support the integration and interoperability(findability)of data,which is crucial to all other aspects of the FAIR Guidelines.There is also a plan to build standards and protocols into the implementation of information systems in each ministry and government agency to improve data accessibility(accessibility),the integration of the various information systems is planned/ongoing(interoperability),and the need for a standardised arrangement for health information systems related to health data following the community standard is recognised(reusability).The documents at the core of Indonesia’s digital health/e Health policy have the highest FAIR Equivalency Score(FE-Score),showing some degree of alignment between the Indonesian digital health implementation vision and the FAIR Guidelines.This indicates that Indonesia’s digital health sector is open to using the FAIR Guidelines.展开更多
文摘Research data currently face a huge increase of data objects with an increasing variety of types(data types,formats)and variety of workflows by which objects need to be managed across their lifecycle by data infrastructures.Researchers desire to shorten the workflows from data generation to analysis and publication,and the full workflow needs to become transparent to multiple stakeholders,including research administrators and funders.This poses challenges for research infrastructures and user-oriented data services in terms of not only making data and workflows findable,accessible,interoperable and reusable,but also doing so in a way that leverages machine support for better efficiency.One primary need to be addressed is that of findability,and achieving better findability has benefits for other aspects of data and workflow management.In this article,we describe how machine capabilities can be extended to make workflows more findable,in particular by leveraging the Digital Object Architecture,common object operations and machine learning techniques.
基金the US National Science Foundation for their long-time support of the development of the IGSN(Grant Nos.NSF-0445178,NSF-0514551,NSF-0552123)the Earth Chem system(Grant No.NSF-0522195)+1 种基金operation of both systems as part of the IEDA Data Facility(Grant Nos.NSF-0950477,NSF-1636653)the Alfred P.Sloan Foundation for a grant to Columbia University to support the development of a global,scalable,and sustainable technical and organizational infrastructure for persistent unique identifiers of physical scientific samples.
文摘1 Introduction The primary goal of the Deep-time Digital Earth project is to develop an open collaboration and data sharing platform that enables the transition of deep-time geoscientific research to a Big Data driven paradigm.Such an open platform will require the ability to effectively and efficiently access and integrate a wide variety of digital Earth data.
基金VODAN-Africathe Philips Foundation+2 种基金the Dutch Development Bank FMOCORDAIDthe GO FAIR Foundation for supporting this research
文摘This study explores the possibility of opening a policy window for the adoption of the FAIR Guidelines—that data be Findable, Accessible, Interoperable, and Reusable(FAIR)—in Uganda’s e Health sector. Although the FAIR Guidelines were not mentioned in any of the policy documents relevant to Uganda’s e Health sector, the study found that 83% of the documents mentioned FAIR Equivalent efforts, such as the adoption of the National Identification Number(NIN) as a unique identifier in Uganda’s national Electronic Health Management Information System(e HMIS)(findability), the planned/ongoing integration of various information systems(interoperability), and the alignment of various projects with international best practices/standards(reusability). A FAIR Equivalency Score(FE-Score), devised in this study as an aggregate score of the mention of the equivalent of FAIR facets in the policy documents, showed that the documents at the core of Uganda’s digital health/e Health policy have the highest score of all the documents analysed, indicating that there is a degree of alignment between Uganda’s National e Health Vision and the FAIR Guidelines. Therefore, it can be concluded that favourable conditions exist for the adoption and implementation of the FAIR Guidelines in Uganda’s e Health sector. Hence, it is recommended that the FAIR community adopt a capacity building strategy through organisations with a worldwide mandate, such as the World Health Organization, to promote the adoption of the FAIR Guidelines as part of international best practices.
基金This work was supported in part by the European Union’s Horizon 2020 program under grant agreements 777523,FREYA“Connected Open Identifiers for Discovery,Access and Use of Research Resources”,654248,CORBEL+1 种基金“Coordinated Research Infrastructures Building Enduring Life-science services”,and 823830Bioexcel2,"BioExcel-2 Centre of Excellence for Computational Biomolecular Research".Many thanks to Paul Groth for his helpful comments on the manuscript.
文摘The FAIR principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem.Persistent,globally unique identifiers,resolvable on the Web,and associated with a set of additional descriptive metadata,are foundational to FAIR data.Here we describe some basic principles and exemplars for their design,use and orchestration with other system elements to achieve FAIRness for digital research objects.
基金VODAN-Africathe Philips Foundation+2 种基金the Dutch Development Bank FMOCORDAIDthe GO FAIR Foundation for supporting this research
文摘The objective of this study was to assess the regulatory framework for health data in Indonesia in order to understand the policy context and explore the possibility of expanding the adoption and implementation of the FAIR Guidelines,which state that data should be Findable,Accessible,Interoperable and Reusable(FAIR),in Indonesia.Although the FAIR Guidelines were not explicitly mentioned in any of the policy documents relevant to the Indonesian digital health sector,six out of the eight documents analysed contained FAIR Equivalent principles.In particular,Indonesia’s Population Identification Number(NIK)has the potential,as a unique identifier,to support the integration and interoperability(findability)of data,which is crucial to all other aspects of the FAIR Guidelines.There is also a plan to build standards and protocols into the implementation of information systems in each ministry and government agency to improve data accessibility(accessibility),the integration of the various information systems is planned/ongoing(interoperability),and the need for a standardised arrangement for health information systems related to health data following the community standard is recognised(reusability).The documents at the core of Indonesia’s digital health/e Health policy have the highest FAIR Equivalency Score(FE-Score),showing some degree of alignment between the Indonesian digital health implementation vision and the FAIR Guidelines.This indicates that Indonesia’s digital health sector is open to using the FAIR Guidelines.
