Studies on Agricultural Scientific and Technical Information Core Metadata Register System

To construct the Agricultural Scientific and Technical Information Core Metadata （ASTICM） standard and its expanding principles, and to develop a register system based on ASTICM, the policy and methods of DC （Dublin Core） and SDBCM （Scientific Database Core Metadata） were studied. The construction of ASTICM has started from the proposed elements of the DCMI （Dublin Core Metadata Initiative）, and has expanded the DC and SDBCM with related expanding principles. ASTICM finally includes 75 metadata elements, five expanded principles, and seven application profile creation methods. According to the requirement analysis of a large number of users of agricultural information, a register system based on ASTICM was developed. The ASTICM standard framework and its register system supported the search, sharing, integration exchange and other applications, effectively.

Building Community Consensus for Scientific Metadata with YAMZ

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.

The Semantic Data Dictionary-An Approach for Describing and Annotating Data

It is common practice for data providers to include text descriptions for each column when publishing data sets in the form of data dictionaries.While these documents are useful in helping an end-user properly interpret the meaning of a column in a data set,existing data dictionaries typically are not machine-readable and do not follow a common specification standard.We introduce the Semantic Data Dictionary,a specification that formalizes the assignment of a semantic representation of data,enabling standardization and harmonization across diverse data sets.In this paper,we present our Semantic Data Dictionary work in the context of our work with biomedical data;however,the approach can and has been used in a wide range of domains.The rendition of data in this form helps promote improved discovery,interoperability,reuse,traceability,and reproducibility.We present the associated research and describe how the Semantic Data Dictionary can help address existing limitations in the related literature.We discuss our approach,present an example by annotating portions of the publicly available National Health and Nutrition Examination Survey data set,present modeling challenges,and describe the use of this approach in sponsored research,including our work on a large National Institutes of Health(NIH)-funded exposure and health data portal and in the RPI-IBM collaborative Health Empowerment by Analytics,Learning,and Semantics project.