Improving interoperability by incorporating UnitsML into markup languages

Abstract

Maintaining the integrity of analytical data over time is a challenge. Years ago, data were recorded on paper that was pasted directly into a laboratory notebook. The digital age has made maintaining the integrity of data harder. Nowadays, digitized analytical data are often separated from information about how the sample was collected and prepared for analysis and how the data were acquired. The data are stored on digital media, while the related information about the data may be written in a paper notebook or stored separately in other digital files. Sometimes the connection between this “scientific meta-data” and the analytical data is lost, rendering the spectrum or chromatogram useless. We have been working with ASTM Subcommittee E13.15 on Analytical Data to create the Analytical Information Markup Language or AnIML—a new way to interchange and store spectroscopy and chromatography data based on XML (Extensible Markup Language). XML is a language for describing what data are by enclosing them in computer-useable tags. Recording the units associated with the analytical data and metadata is an essential issue for any data representation scheme that must be addressed by all domain-specific markup languages. As scientific markup languages proliferate, it is very desirable to have a single scheme for handling units to facilitate moving information between different data domains.At NIST, we have been developing a general markup language just for units that we call UnitsML. This presentation will describe how UnitsML is used and how it is being incorporated into AnIML.

Machine-readable data and metadata of international key comparisons in radionuclide metrology

“…One of the most critical points for key comparison data is the implementation of metrological vocabularies. Many representations such as UCUM [15], QUDT [16] and UnitsML [17] are under development for metrological data. These digital measurement representations offer coherent mechanisms describing the relationship between units, quantities, and dimensions, although achieving a complete numerical description of all measurements allowing safe conversions between them, is a delicate challenge [18,19].…”

FAIR digital objects in environmental and life sciences should comprise workflow operation design data and method information for repeatability of study setups and reproducibility of results

“…Any existing conceptual schema, allowing the declaration of relations between object identifiers, is principally suitable to explicitly address design elements in a workflow along with method information and measurement data. And indeed, a considerable proportion of proprietary design elements as defined above may be mappable onto generic or domain-specific schemas, and (de facto) standard schemas like ISA Model, AnIML, UnitsML, MIxS, MOD-CO, Ecological Markup Language (EML) and ABCD ( 64 , 65 , 66 , 67 , 68 , 31 , 69 , 70 , 71 ), as well as others, e.g. listed by GFBio under https://gfbio.biowikifarm.net/wiki/Data_exchange_standards,_protocols_and_formats_relevant_for_the_collection_data_domain_within_the_GFBio_network.…”