From the author, there are not less than a dozen of rather significant recent publications in scientific editions anticipating some aspects of importance to innovation such as “bigger data”, AI, IP, and frontier tec...From the author, there are not less than a dozen of rather significant recent publications in scientific editions anticipating some aspects of importance to innovation such as “bigger data”, AI, IP, and frontier technology with a central massive contribution in 2020 on AI, IP, and EI. Nonetheless, the IP associated with AI remains still barely covered in scientific publications. Especially patent discussion tends to be rather a legal matter. Another trilogy, 2013, “Business Strategy-IP Strategy-R&D Strategy: An All-in-One Business Model” proposed by the author, marked the advent, and customized implementation of a new strategy level. After the two trilogies’ volumes, the AI-IP “accessibility” chapter was a logical step brought to the attention of a larger public by the author. The time now to bring to light another chapter, namely the IP eligibility of AI innovation steps in ad hoc inventions. The main objectives of this short, principally illustrated communication, are to: 1) Revise the best mode requirement status, i.e. the best way to enable the reproducibility of claimed matter, reviewing its need for improvement when AI is involved. And proposing a unique sequence of evolution inspired by IP’s current and evolving practices. 2) Give a new dimension to visual aids to help the Best Mode description, demystify AI complexity, and underline frontier traits that may hinder a confident adoption or well-argued rejection. 3) Further illustrations take into account the fact that IoT, AI, and 3D can be simpler than perceived. 4) Finally ATA©, Adjacent Technology Analysis, is timely refreshed in a unique challenging, indeed tumultuous, environment. 5) Bias, such as semantic ones is consistently monitored. 6) Overall leaving space for innovative pleasurable interpretation. The emphasis is on educational, illustrative and demonstrative value.展开更多
The last letter of the FAIR acronym stands for Reusability.Data and metadata should be made available with a clear and accessible usage license.But,what are the choices?How can researchers share data and allow reusabi...The last letter of the FAIR acronym stands for Reusability.Data and metadata should be made available with a clear and accessible usage license.But,what are the choices?How can researchers share data and allow reusability?Are all the licenses available for sharing content suitable for data?Data can be covered by different layers of copyright protection making the relationship between data and copyright particularly complex.Some research data can be considered as a work and therefore covered by full copyright while other data can be in the public domain due to their lack of originality.Moreover,a collection of data can be protected by special rights in Europe to acknowledge the investment in time and money in obtaining,presenting,arranging or verifying the data.The need of using a license when sharing data comes from the fact that,under current copyright laws,when rights exist,the absence of any legal notice must be understood as the default“all rights reserved”regime.Unless an exception applies,the authorisation of right holders is necessary for reuse.Right holders could use any text to state the reusability of data but it is advisable to use some of the existing licenses,and especially the ones that are suitable for data and databases.We hope that with this paper we can bring some clarity in relation to the rights involved when sharing research data.展开更多
文摘From the author, there are not less than a dozen of rather significant recent publications in scientific editions anticipating some aspects of importance to innovation such as “bigger data”, AI, IP, and frontier technology with a central massive contribution in 2020 on AI, IP, and EI. Nonetheless, the IP associated with AI remains still barely covered in scientific publications. Especially patent discussion tends to be rather a legal matter. Another trilogy, 2013, “Business Strategy-IP Strategy-R&D Strategy: An All-in-One Business Model” proposed by the author, marked the advent, and customized implementation of a new strategy level. After the two trilogies’ volumes, the AI-IP “accessibility” chapter was a logical step brought to the attention of a larger public by the author. The time now to bring to light another chapter, namely the IP eligibility of AI innovation steps in ad hoc inventions. The main objectives of this short, principally illustrated communication, are to: 1) Revise the best mode requirement status, i.e. the best way to enable the reproducibility of claimed matter, reviewing its need for improvement when AI is involved. And proposing a unique sequence of evolution inspired by IP’s current and evolving practices. 2) Give a new dimension to visual aids to help the Best Mode description, demystify AI complexity, and underline frontier traits that may hinder a confident adoption or well-argued rejection. 3) Further illustrations take into account the fact that IoT, AI, and 3D can be simpler than perceived. 4) Finally ATA©, Adjacent Technology Analysis, is timely refreshed in a unique challenging, indeed tumultuous, environment. 5) Bias, such as semantic ones is consistently monitored. 6) Overall leaving space for innovative pleasurable interpretation. The emphasis is on educational, illustrative and demonstrative value.
基金Thomas Margoni co-coordinates the legal task force of OpenAIRE Advance,a project funded under the H2020 programme of the European Commission,project n°:777541.We would like to thank the support of the project.
文摘The last letter of the FAIR acronym stands for Reusability.Data and metadata should be made available with a clear and accessible usage license.But,what are the choices?How can researchers share data and allow reusability?Are all the licenses available for sharing content suitable for data?Data can be covered by different layers of copyright protection making the relationship between data and copyright particularly complex.Some research data can be considered as a work and therefore covered by full copyright while other data can be in the public domain due to their lack of originality.Moreover,a collection of data can be protected by special rights in Europe to acknowledge the investment in time and money in obtaining,presenting,arranging or verifying the data.The need of using a license when sharing data comes from the fact that,under current copyright laws,when rights exist,the absence of any legal notice must be understood as the default“all rights reserved”regime.Unless an exception applies,the authorisation of right holders is necessary for reuse.Right holders could use any text to state the reusability of data but it is advisable to use some of the existing licenses,and especially the ones that are suitable for data and databases.We hope that with this paper we can bring some clarity in relation to the rights involved when sharing research data.
