International Semantic Web Conference, Nov 1, 2004
... utwente.nl Gerd Wagner Eindhoven University of Technology, Eindhoven, The Netherlands G.Wagne... more ... utwente.nl Gerd Wagner Eindhoven University of Technology, Eindhoven, The Netherlands G.Wagner@tm.tue.nl José Gonçalves Pereira Filho ... Although they are from different medical specialties, thus from different initial CoPs, they are married (social characteristic) and share ...
Scientific advances, especially in the healthcare domain, can be accelerated by making data avail... more Scientific advances, especially in the healthcare domain, can be accelerated by making data available for analysis. However, in traditional data analysis systems, data need to be moved to a central processing unit that performs analyses, which may be undesirable, e.g. due to privacy regulations in case these data contain personal information. This paper discusses the Personal Health Train (PHT) approach in which data processing is brought to the (personal health) data rather than the other way around, allowing (private) data accessed to be controlled, and to observe ethical and legal concerns. This paper introduces the PHT architecture and discusses the data staging solution that allows processing to be delegated to components spawned in a private cloud environment in case the (health) organisation hosting the data has limited resources to execute the required processing. This paper shows the feasibility and suitability of the solution with a relatively simple, yet representative, c...
Pesquisa Brasileira em Ciência da Informação e Biblioteconomia, 2019
Os princípios FAIR, um acrônimo para Findable, Accessible, Interoperable e Reusable, estão presen... more Os princípios FAIR, um acrônimo para Findable, Accessible, Interoperable e Reusable, estão presentes nas discussões e práticas contemporâneas da ciência de dados, desde o início de 2014, e tiveram sua aplicação consolidada em 2017, quando a Comissão Europeia passou a exigir a adoção de plano de gestão de dados, com base nesses princípios, por projetos financiados por seus recursos. Desde então, tais princípios passaram a ser norteadores da descoberta, do acesso, da interoperabilidade, do compartilhamento e da reutilização dos dados de pesquisa. No entanto, quando colocados em prática levantam dúvidas e imprecisões, gerando diferentes interpretações, o que dificulta sua aplicação. Por essa razão buscou-se elucidar seu entendimento, utilizando-se de conceitos esclarecedores, apresentando métricas específicas que medem o nível de FAIRnessdos objetos digitais; disseminando a proposta do ecossistema dos dados FAIR e as tecnologias Data FAIRPort e FAIR Data Point. Apresentamos, ainda, est...
Genetics research is focusing more and more on mining fully sequenced genomes and their annotatio... more Genetics research is focusing more and more on mining fully sequenced genomes and their annotations to identify the causal genes associated with specific traits (phenotypes) of interest. However, a complex trait is typically associated with multiple quantitative trait loci (QTLs), each with hundreds of genes positively/negatively affecting the desired trait(s). Our aim is to develop a Big data analytics & semantic interoperability infrastructure for candidate gene prioritization that will aid breeders in the design of an optimal genotype with a desired trait(s) for a given environment.
Figshare's annual report, The State of Open Data 2018, looks at global attitudes towards open... more Figshare's annual report, The State of Open Data 2018, looks at global attitudes towards open data. It includes survey results of researchers and a collection of articles from industry experts, as well as a foreword from Ross Wilkinson, Director, Global Strategy at Australian Research Data Commons.The report is the third in the series and the survey results continue to show encouraging progress that open data is becoming more embedded in the research community.The key finding is that open data has become more embedded in the research community – 64% of survey respondents reveal they made their data openly available in 2018. However, a surprising number of respondents (60%) had never heard of the FAIR principles, a guideline to enhance the reusability of academic data.
1 Leiden University Medical Centre, The Netherlands {m.roos,m.thompson,r.kaliyaperumal,a.jacobsen... more 1 Leiden University Medical Centre, The Netherlands {m.roos,m.thompson,r.kaliyaperumal,a.jacobsen}@lumc.nl 2 Universidad Politcnica de Madrid, Spain markw@illuminae.com 3 Istituto Superiore di Sanitá, Italy claudio.carta@iss.it 4 University Medical Center Groningen, The Netherlands david.van.enckevort@umcg.nl 5 Wageningen Plant Research, The Netherlands richard.finkers@wur.nl 6 Dutch Techcentre for Life Sciences, The Netherlands {luiz.bonino,erik.schultes,mascha.jansen}@dtls.nl
Functionally interlinking datasets is essential for knowledge discovery. The ‘Bring Your Own Data... more Functionally interlinking datasets is essential for knowledge discovery. The ‘Bring Your Own Data’ workshop (BYOD) has proven an excellent tool for the adoption of techniques to achieve this. It provides a mechanism for data owners who would like to add value to their data by preparing them for data integration and computational analysis, but are unfamiliar with basic techniques to make data Findable, Accessible, Interoperable, and Reusable for humans and computers (FAIR). Using linked data and associated technologies, data owners, domain experts, and linked data experts collaborate to make owner’s data linkable and explore possibilities to answer questions across multiple data sources. Momentarily, BYODs play a critical role in establishing a robust and sustainable infrastructure of linkable data sources where the responsibility for FAIR data stewardship starts at the source. We present the organisational roadmap of the three-day workshop and the latest insights into making BYODs m...
Page 1. v 2009 13th Enterprise Distributed Object Computing Conference Workshops, EDOCW Proceedin... more Page 1. v 2009 13th Enterprise Distributed Object Computing Conference Workshops, EDOCW Proceedings of the IEEE EDOC 2009 Workshops and Short Papers Edited by Vladimir Tosic Table of Contents Proceedings of the IEEE EDOC 2009 Workshops and Short Papers: Editor's Message Vladimir Tosic iii Dynamic and Declarative Business Processes (DDBP) 2009 organized by Dragan Ga��evi��, Georg Grossmann, Sylvain Hall�� Dynamic and Declarative Business Processes: Editorial Dragan Ga��evi��, Georg Grossmann, Sylvain Hall�� 1 ...
The specialist field of rare diseases must connect its vast array of globally distributed disease... more The specialist field of rare diseases must connect its vast array of globally distributed disease and patient registries to maximise their value. Unfortunately, many registries are “boutique”, with few or no staff with formal informatics training. At a series of Bring Your Own Data workshops, we helped registry owners transform their data into formally structured triple stores following the Linked Data principles and demonstrated the potential of data linkage. We documented several useful approaches that we believe could be followed independently by other registry owners worldwide, including: that the transformation to Linked Data could be considered as passing through layers of increasing semantic complexity; that only a subset of ontologies are relevant at each layer; and that certain data transformation processes could be modelled as an “archetype”, and presented to registry staff to fill-in with their data. We propose that formally capturing these ontological layers and archetyp...
In recent years, implementations enabling Distributed Analytics (DA) have gained considerable att... more In recent years, implementations enabling Distributed Analytics (DA) have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data. These concepts propose privacy-enhancing alternatives to data centralisation approaches, which have restricted applicability in case of sensitive data due to ethical, legal or social aspects. Nevertheless, the immanent problem of DA-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions, particularly the absence of basic metadata for data sets or analysis tasks. To approach the mentioned problems, we propose a metadata schema for DA infrastructures, which provides a vocabulary to enrich the involved entities with descriptive semantics. We initially perform a requirement analysis with domain experts to reveal necessary metadata items, which represents the foundation of...
Navigating Healthcare Through Challenging Times, 2021
Background: Integration of heterogenous resources is key for Rare Disease research. Within the EJ... more Background: Integration of heterogenous resources is key for Rare Disease research. Within the EJP RD, common Application Programming Interface specifications are proposed for discovery of resources and data records. This is not sufficient for automated processing between RD resources and meeting the FAIR principles. Objective: To design a solution to improve FAIR for machines for the EJP RD API specification. Methods: A FAIR Data Point is used to expose machine-actionable metadata of digital resources and it is configured to store its content to a semantic database to be FAIR at the source. Results: A solution was designed based on grlc server as middleware to implement the EJP RD API specification on top of the FDP. Conclusion: grlc reduces potential API implementation overhead faced by maintainers who use FAIR at the source.
Este artigo tem o objetivo de apresentar os princípios FAIR e a iniciativa Global Open FAIR que b... more Este artigo tem o objetivo de apresentar os princípios FAIR e a iniciativa Global Open FAIR que busca disseminar esses princípios em todos os países interessados na aplicação dos dados FAIR (Findable, Accessible, Interoperable, Reusable) em seus serviços de informação. Propõe ainda a divulgação e capacitação de instituições de ensino e pesquisa nesses princípios, com o intuito de promover a normalização no tratamento da gestão dos dados garantindo a interoperabilidade entre eles. Como procedimento metodológico, utiliza a revisão bibliográfica e documental para o embasamento teórico sobre ciência aberta, acesso aberto à informação científica e aos dados de pesquisa, visando fundamentar os princípios FAIR em aplicações e serviços de gestão de dados de pesquisa. Ressalta a importância desse tipo de iniciativa para a expansão mundial de abertura dos dados de pesquisa no âmbito da ciência aberta. Ao final, aponta para a necessidade de uma mudança nos processos de pesquisa em ciência e te...
The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders... more The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 FAIR guiding principles do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability and Reusability of digital resources. This has likely contributed to the broad adoption of the FAIR principles, because individual stakeholder communities can implement their own FAIR solutions. However, it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations. Thus, while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways, for true interoperability we need to support convergence in implementation choices that are widely accessible and (re)-usable. We introduce the concept of FAIR implementation considerations to assist accelerated global participation and converg...
In order to provide responsible access to health data by reconciling benefits of data sharing wit... more In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements, Findable, Accessible, Interoperable and Reusable (FAIR) metadata should be developed. According to the H2020 Program Guidelines on FAIR Data, data should be “as open as possible and as closed as necessary”, “open” in order to foster the reusability and to accelerate research, but at the same time they should be “closed” to safeguard the privacy of the subjects. Additional provisions on the protection of natural persons with regard to the processing of personal data have been endorsed by the European General Data Protection Regulation (GDPR), Reg (EU) 2016/679, that came into force in May 2018. This work aims to solve accessibility problems related to the protection of personal data in the digital era and to achieve a responsible access to and responsible use of health data. We strongly suggest associating each data set with FAIR m...
In recent years, as newer technologies have evolved around the healthcare ecosystem, more and mor... more In recent years, as newer technologies have evolved around the healthcare ecosystem, more and more data have been generated. Advanced analytics could power the data collected from numerous sources, both from healthcare institutions, or generated by individuals themselves via apps and devices, and lead to innovations in treatment and diagnosis of diseases; improve the care given to the patient; and empower citizens to participate in the decision-making process regarding their own health and well-being. However, the sensitive nature of the health data prohibits healthcare organizations from sharing the data. The Personal Health Train (PHT) is a novel approach, aiming to establish a distributed data analytics infrastructure enabling the (re)use of distributed healthcare data, while data owners stay in control of their own data. The main principle of the PHT is that data remain in their original location, and analytical tasks visit data sources and execute the tasks. The PHT provides a ...
International Semantic Web Conference, Nov 1, 2004
... utwente.nl Gerd Wagner Eindhoven University of Technology, Eindhoven, The Netherlands G.Wagne... more ... utwente.nl Gerd Wagner Eindhoven University of Technology, Eindhoven, The Netherlands G.Wagner@tm.tue.nl José Gonçalves Pereira Filho ... Although they are from different medical specialties, thus from different initial CoPs, they are married (social characteristic) and share ...
Scientific advances, especially in the healthcare domain, can be accelerated by making data avail... more Scientific advances, especially in the healthcare domain, can be accelerated by making data available for analysis. However, in traditional data analysis systems, data need to be moved to a central processing unit that performs analyses, which may be undesirable, e.g. due to privacy regulations in case these data contain personal information. This paper discusses the Personal Health Train (PHT) approach in which data processing is brought to the (personal health) data rather than the other way around, allowing (private) data accessed to be controlled, and to observe ethical and legal concerns. This paper introduces the PHT architecture and discusses the data staging solution that allows processing to be delegated to components spawned in a private cloud environment in case the (health) organisation hosting the data has limited resources to execute the required processing. This paper shows the feasibility and suitability of the solution with a relatively simple, yet representative, c...
Pesquisa Brasileira em Ciência da Informação e Biblioteconomia, 2019
Os princípios FAIR, um acrônimo para Findable, Accessible, Interoperable e Reusable, estão presen... more Os princípios FAIR, um acrônimo para Findable, Accessible, Interoperable e Reusable, estão presentes nas discussões e práticas contemporâneas da ciência de dados, desde o início de 2014, e tiveram sua aplicação consolidada em 2017, quando a Comissão Europeia passou a exigir a adoção de plano de gestão de dados, com base nesses princípios, por projetos financiados por seus recursos. Desde então, tais princípios passaram a ser norteadores da descoberta, do acesso, da interoperabilidade, do compartilhamento e da reutilização dos dados de pesquisa. No entanto, quando colocados em prática levantam dúvidas e imprecisões, gerando diferentes interpretações, o que dificulta sua aplicação. Por essa razão buscou-se elucidar seu entendimento, utilizando-se de conceitos esclarecedores, apresentando métricas específicas que medem o nível de FAIRnessdos objetos digitais; disseminando a proposta do ecossistema dos dados FAIR e as tecnologias Data FAIRPort e FAIR Data Point. Apresentamos, ainda, est...
Genetics research is focusing more and more on mining fully sequenced genomes and their annotatio... more Genetics research is focusing more and more on mining fully sequenced genomes and their annotations to identify the causal genes associated with specific traits (phenotypes) of interest. However, a complex trait is typically associated with multiple quantitative trait loci (QTLs), each with hundreds of genes positively/negatively affecting the desired trait(s). Our aim is to develop a Big data analytics & semantic interoperability infrastructure for candidate gene prioritization that will aid breeders in the design of an optimal genotype with a desired trait(s) for a given environment.
Figshare's annual report, The State of Open Data 2018, looks at global attitudes towards open... more Figshare's annual report, The State of Open Data 2018, looks at global attitudes towards open data. It includes survey results of researchers and a collection of articles from industry experts, as well as a foreword from Ross Wilkinson, Director, Global Strategy at Australian Research Data Commons.The report is the third in the series and the survey results continue to show encouraging progress that open data is becoming more embedded in the research community.The key finding is that open data has become more embedded in the research community – 64% of survey respondents reveal they made their data openly available in 2018. However, a surprising number of respondents (60%) had never heard of the FAIR principles, a guideline to enhance the reusability of academic data.
1 Leiden University Medical Centre, The Netherlands {m.roos,m.thompson,r.kaliyaperumal,a.jacobsen... more 1 Leiden University Medical Centre, The Netherlands {m.roos,m.thompson,r.kaliyaperumal,a.jacobsen}@lumc.nl 2 Universidad Politcnica de Madrid, Spain markw@illuminae.com 3 Istituto Superiore di Sanitá, Italy claudio.carta@iss.it 4 University Medical Center Groningen, The Netherlands david.van.enckevort@umcg.nl 5 Wageningen Plant Research, The Netherlands richard.finkers@wur.nl 6 Dutch Techcentre for Life Sciences, The Netherlands {luiz.bonino,erik.schultes,mascha.jansen}@dtls.nl
Functionally interlinking datasets is essential for knowledge discovery. The ‘Bring Your Own Data... more Functionally interlinking datasets is essential for knowledge discovery. The ‘Bring Your Own Data’ workshop (BYOD) has proven an excellent tool for the adoption of techniques to achieve this. It provides a mechanism for data owners who would like to add value to their data by preparing them for data integration and computational analysis, but are unfamiliar with basic techniques to make data Findable, Accessible, Interoperable, and Reusable for humans and computers (FAIR). Using linked data and associated technologies, data owners, domain experts, and linked data experts collaborate to make owner’s data linkable and explore possibilities to answer questions across multiple data sources. Momentarily, BYODs play a critical role in establishing a robust and sustainable infrastructure of linkable data sources where the responsibility for FAIR data stewardship starts at the source. We present the organisational roadmap of the three-day workshop and the latest insights into making BYODs m...
Page 1. v 2009 13th Enterprise Distributed Object Computing Conference Workshops, EDOCW Proceedin... more Page 1. v 2009 13th Enterprise Distributed Object Computing Conference Workshops, EDOCW Proceedings of the IEEE EDOC 2009 Workshops and Short Papers Edited by Vladimir Tosic Table of Contents Proceedings of the IEEE EDOC 2009 Workshops and Short Papers: Editor's Message Vladimir Tosic iii Dynamic and Declarative Business Processes (DDBP) 2009 organized by Dragan Ga��evi��, Georg Grossmann, Sylvain Hall�� Dynamic and Declarative Business Processes: Editorial Dragan Ga��evi��, Georg Grossmann, Sylvain Hall�� 1 ...
The specialist field of rare diseases must connect its vast array of globally distributed disease... more The specialist field of rare diseases must connect its vast array of globally distributed disease and patient registries to maximise their value. Unfortunately, many registries are “boutique”, with few or no staff with formal informatics training. At a series of Bring Your Own Data workshops, we helped registry owners transform their data into formally structured triple stores following the Linked Data principles and demonstrated the potential of data linkage. We documented several useful approaches that we believe could be followed independently by other registry owners worldwide, including: that the transformation to Linked Data could be considered as passing through layers of increasing semantic complexity; that only a subset of ontologies are relevant at each layer; and that certain data transformation processes could be modelled as an “archetype”, and presented to registry staff to fill-in with their data. We propose that formally capturing these ontological layers and archetyp...
In recent years, implementations enabling Distributed Analytics (DA) have gained considerable att... more In recent years, implementations enabling Distributed Analytics (DA) have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data. These concepts propose privacy-enhancing alternatives to data centralisation approaches, which have restricted applicability in case of sensitive data due to ethical, legal or social aspects. Nevertheless, the immanent problem of DA-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions, particularly the absence of basic metadata for data sets or analysis tasks. To approach the mentioned problems, we propose a metadata schema for DA infrastructures, which provides a vocabulary to enrich the involved entities with descriptive semantics. We initially perform a requirement analysis with domain experts to reveal necessary metadata items, which represents the foundation of...
Navigating Healthcare Through Challenging Times, 2021
Background: Integration of heterogenous resources is key for Rare Disease research. Within the EJ... more Background: Integration of heterogenous resources is key for Rare Disease research. Within the EJP RD, common Application Programming Interface specifications are proposed for discovery of resources and data records. This is not sufficient for automated processing between RD resources and meeting the FAIR principles. Objective: To design a solution to improve FAIR for machines for the EJP RD API specification. Methods: A FAIR Data Point is used to expose machine-actionable metadata of digital resources and it is configured to store its content to a semantic database to be FAIR at the source. Results: A solution was designed based on grlc server as middleware to implement the EJP RD API specification on top of the FDP. Conclusion: grlc reduces potential API implementation overhead faced by maintainers who use FAIR at the source.
Este artigo tem o objetivo de apresentar os princípios FAIR e a iniciativa Global Open FAIR que b... more Este artigo tem o objetivo de apresentar os princípios FAIR e a iniciativa Global Open FAIR que busca disseminar esses princípios em todos os países interessados na aplicação dos dados FAIR (Findable, Accessible, Interoperable, Reusable) em seus serviços de informação. Propõe ainda a divulgação e capacitação de instituições de ensino e pesquisa nesses princípios, com o intuito de promover a normalização no tratamento da gestão dos dados garantindo a interoperabilidade entre eles. Como procedimento metodológico, utiliza a revisão bibliográfica e documental para o embasamento teórico sobre ciência aberta, acesso aberto à informação científica e aos dados de pesquisa, visando fundamentar os princípios FAIR em aplicações e serviços de gestão de dados de pesquisa. Ressalta a importância desse tipo de iniciativa para a expansão mundial de abertura dos dados de pesquisa no âmbito da ciência aberta. Ao final, aponta para a necessidade de uma mudança nos processos de pesquisa em ciência e te...
The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders... more The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 FAIR guiding principles do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability and Reusability of digital resources. This has likely contributed to the broad adoption of the FAIR principles, because individual stakeholder communities can implement their own FAIR solutions. However, it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations. Thus, while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways, for true interoperability we need to support convergence in implementation choices that are widely accessible and (re)-usable. We introduce the concept of FAIR implementation considerations to assist accelerated global participation and converg...
In order to provide responsible access to health data by reconciling benefits of data sharing wit... more In order to provide responsible access to health data by reconciling benefits of data sharing with privacy rights and ethical and regulatory requirements, Findable, Accessible, Interoperable and Reusable (FAIR) metadata should be developed. According to the H2020 Program Guidelines on FAIR Data, data should be “as open as possible and as closed as necessary”, “open” in order to foster the reusability and to accelerate research, but at the same time they should be “closed” to safeguard the privacy of the subjects. Additional provisions on the protection of natural persons with regard to the processing of personal data have been endorsed by the European General Data Protection Regulation (GDPR), Reg (EU) 2016/679, that came into force in May 2018. This work aims to solve accessibility problems related to the protection of personal data in the digital era and to achieve a responsible access to and responsible use of health data. We strongly suggest associating each data set with FAIR m...
In recent years, as newer technologies have evolved around the healthcare ecosystem, more and mor... more In recent years, as newer technologies have evolved around the healthcare ecosystem, more and more data have been generated. Advanced analytics could power the data collected from numerous sources, both from healthcare institutions, or generated by individuals themselves via apps and devices, and lead to innovations in treatment and diagnosis of diseases; improve the care given to the patient; and empower citizens to participate in the decision-making process regarding their own health and well-being. However, the sensitive nature of the health data prohibits healthcare organizations from sharing the data. The Personal Health Train (PHT) is a novel approach, aiming to establish a distributed data analytics infrastructure enabling the (re)use of distributed healthcare data, while data owners stay in control of their own data. The main principle of the PHT is that data remain in their original location, and analytical tasks visit data sources and execute the tasks. The PHT provides a ...
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Papers by Luiz Olavo Bonino da Silva Santos