Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies (2022) / Chapter Skim
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Pages 98-109
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From page 98... ...
If a user constructs a new dataset based on integrating data produced at several statistical offices, then the new dataset needs its own metadata. For scientific research data, metadata are particularly important in facilitating the machine readability of a dataset (the automatic use of a dataset by software)
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• Datatype (in the case of marital status, nominal datatype) ,4 and • Universe (say, adults in the United States)
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will come up again later in this report, for example in our reviews of the Data Documentation Initia tive (DDI) and the Generic Statistical Information Model (GSIM)
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Metadata elements are enclosed within pointy brackets ("<" and ">") , which makes it possible for a computer to easily retrieve all the information recorded within one.
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The simplicity of JSON is designed to avoid that problem. Finally, as with XML, JSON has a schema language, which allows designers to construct reusable JSON elements and structures.
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Figure 5-2 A simple dataset description in RDF. 103 Figure 5-2 A simple dataset description in RDF.
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• The user interface is the means, possibly in the form of software, for a user to interact with a metadata system. Users can be humans or other systems, and these correspond roughly to whether the metadata are human readable or machine readable, respectively.
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, these projects involve staff from many areas -- management, subject-matter experts, statisticians, information scientists, computer scientists, and IT specialists. These can be complex projects.
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federal statistical agencies, collaborative projects are very likely the right way to proceed. In addition to all of the above, achieving success requires that manage ment and technical staff be supportive.
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RISKS AND BENEFITS Given the costs and time that must be devoted to training and developing tools to adopt and make use of any of the six metadata standards described in detail later in this chapter, there is understandable hesitancy about building the capabilities of statistical metadata management. Some agencies view the making of informed use of metadata standards as "a bridge too far." However, the costs are not excessive, and the benefits will extend long into the future.
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The Federal Data Strategy uses the phrase "Define once; use many times." Metadata are reused when they help describe many resources. For instance, a variable used in every dataset produced by a monthly survey only needs to be described one time.
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. Often, however, metadata management is an afterthought in the planning and design stages of the statistical or survey life cycle, and this leads to the perception that collecting metadata ex post facto is expensive and time consuming.
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