Sentence examples for metadata standardization from inspiring English sources

Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics.

In the revised version of the manuscript we discuss the problems that the morphological community faces with regard to data and metadata standardization.

Efforts such as metadata standardization [ 5] and bioinformatic tools stressing reproducibility [ 6, 7] represent attempts to make bioinformatic workflows documented and reproducible, thus facilitating collaboration.

We believe that, similar to the problem of data and metadata standardization, the creation of a morphological data repository should not be postponed by trying to achieve the ultimate goal of solving the problems associated with the creation of a standardized ontology.

This specification was developed for the specific purpose of facilitating worldwide metadata standardization by providing guidance on the framework itself, the classification of data, the semantic structure of data, formulation of definitions, naming and identification, and guidance and instruction of the registration of metadata [ 33].

All submissions to the QsarDB repository undergo a special purpose workflow, which performs upload, validation, optimization, metadata-extraction, metadata-description, standardization, and license-selection steps (Figure 7): Figure 7 Item submission workflow.

Projects looking for this kind of support will be easy to find because the problems of metadata collection and standardization that we face today will largely be solved by having them embedded in the systems that collect the data.

NASA is promoting the standardization of metadata.

This course introduces the intellectual foundations of information organization and retrieval: conceptual modeling, semantic representation, vocabulary and metadata design, classification, and standardization, as well as information retrieval practices, technology, and applications, including computational processes for analyzing information in both textual and non-textual formats.

As genomic datasets grow larger and more interconnected, standardization of metadata becomes increasingly vital to allow for exploration and comparison of data between different scientific projects.

Standardization requirements were identified as two different but linked topics: the need to defined standard formats for every data type - which has been partially successfully managed by the several normalization efforts (e.g. MIAME), and the standardization of metadata.