1.INTRODUCTION Metadata,as a type of data,describes content,provides context,documents transactions,and situates data.Interest in metadata has steadily grown over the last several decades,motivated initially by the in...1.INTRODUCTION Metadata,as a type of data,describes content,provides context,documents transactions,and situates data.Interest in metadata has steadily grown over the last several decades,motivated initially by the increase in digital information,open access,early data sharing policies,and interoperability goals.This foundation has accelerated in more recent times,due to the increase in research data management policies and advances in Al.Specific to research data management,one of the larger factors has been the global adoption of the FAIR(findable,accessible,interoperable,and reusable)data principles[1,2],which are highly metadatadriven.Additionally,researchers across nearly every domain are interested in leveraging metadata for machine learning and other Al applications.展开更多
This paper reports on a demonstration of YAMZ(Yet Another Metadata Zoo)as a mechanism for building community consensus around metadata terms.The demonstration is motivated by the complexity of the metadata standards e...This paper reports on a demonstration of YAMZ(Yet Another Metadata Zoo)as a mechanism for building community consensus around metadata terms.The demonstration is motivated by the complexity of the metadata standards environment and the need for more user-friendly approaches for researchers to achieve vocabulary consensus.The paper reviews a series of metadata standardization challenges,explores crowdsourcing factors that offer possible solutions,and introduces the YAMZ system.A YAMZ demonstration is presented with members of the Toberer materials science laboratory at the Colorado School of Mines,where there is a need to confirm and maintain a shared understanding for the vocabulary supporting research documentation,data management,and their larger metadata infrastructure.The demonstration involves three key steps:1)Sampling terms for the demonstration,2)Engaging graduate student researchers in the demonstration,and 3)Reflecting on the demonstration.The results of these steps,including examples of the dialog provenance among lab members and voting,show the ease with YAMZ can facilitate building metadata vocabulary consensus.The conclusion discusses implications and highlights next steps.展开更多
文摘1.INTRODUCTION Metadata,as a type of data,describes content,provides context,documents transactions,and situates data.Interest in metadata has steadily grown over the last several decades,motivated initially by the increase in digital information,open access,early data sharing policies,and interoperability goals.This foundation has accelerated in more recent times,due to the increase in research data management policies and advances in Al.Specific to research data management,one of the larger factors has been the global adoption of the FAIR(findable,accessible,interoperable,and reusable)data principles[1,2],which are highly metadatadriven.Additionally,researchers across nearly every domain are interested in leveraging metadata for machine learning and other Al applications.
基金supported by National Science Foundation-Office of Advance Cyberinfrastructure(NFS-OAC)2118201,the Ronin Institute/U.S.Research Data Alliance(RDA),and the Institute of Museum and Library Services(IMLS)RE-246450-OLS-20.
文摘This paper reports on a demonstration of YAMZ(Yet Another Metadata Zoo)as a mechanism for building community consensus around metadata terms.The demonstration is motivated by the complexity of the metadata standards environment and the need for more user-friendly approaches for researchers to achieve vocabulary consensus.The paper reviews a series of metadata standardization challenges,explores crowdsourcing factors that offer possible solutions,and introduces the YAMZ system.A YAMZ demonstration is presented with members of the Toberer materials science laboratory at the Colorado School of Mines,where there is a need to confirm and maintain a shared understanding for the vocabulary supporting research documentation,data management,and their larger metadata infrastructure.The demonstration involves three key steps:1)Sampling terms for the demonstration,2)Engaging graduate student researchers in the demonstration,and 3)Reflecting on the demonstration.The results of these steps,including examples of the dialog provenance among lab members and voting,show the ease with YAMZ can facilitate building metadata vocabulary consensus.The conclusion discusses implications and highlights next steps.
