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We are awash with “Big Data” to this very day because of the technological advancements made during the past decade. The notion of Big Data refers to the datasets which are gigantic in size to be processed by conventional databases and management techniques (volume), are extremely diverse so that no single data model can capture all elements of the data (variety) and are produced or gathered at an unprecedented scale (velocity). Because of this sheer volume, variety, and velocity of big data, enterprises are facing data heterogeneity, diversity andcomplexity challenges. However, this big data era came with big opportunities by resolving the associated challenges, so it could transform our traditional way of decision-making. Enterprises with the technical expertise of managing big data are now replacing their usual guesswork and laborious legacy data modeling based decision making processes with facts derived from bigdata.

Online biomedical repositories contain a wealth of freely available data submitted by the research community, but to reuse this data in further studies requires well-annotated associated metadata. There is a growing set of community-developed standards for creating this metadata, often in the form of templates; still, the difficulties of working with these standards are significant. The Center for Expanded Data Annotation and Retrieval (CEDAR) is building an end-to-end system to ease the authoring of metadata and the templates. This system targets the creation of higher quality metadata to facilitate data discovery, interoperability, and reuse. With our public release in September 2016, we now support many new features which make authoring easier.Template and Metadata Repository: We developed a standardized representation of metadata and the templates that describe them, together with Web-based services to store, search, and share these resources. Templates created using CEDAR technology are stored in our openly accessible community repository, and can now be shared with other people and groups. Researchers can search for templates to annotate their studies, and share their metadata with others. We’ve now added Web-based interfaces and REST APIs to facilitate access to templates, and all the metadata collected using those templates.Template and Metadata Editor: We developed highly interactive Web-based tools to simplify the process of authoring metadata and templates. The Template Editor allows users to create, search, and author templates. An upgraded feature provides interoperation with ontologies: interactive look-up services linked to NCBO’s BioPortal (bioportal.bioontology.org) let template authors find ontology terms to annotate fields in their templates and to define possible values of fields, including creating new terms and value sets. The Metadata Editor, which creates a forms-based acquisition interface from a template, has been redesigned so users can more easily populate metadata based on the template fields.

Next-generation sequencing technologies have led to a rapid production of high-throughput sequence data characterizing adaptive immune-receptor repertoires (AIRRs). As part of the AIRR community (http://airr-community.org) data standards working group, we have developed an initial set of metadata recommendations for publishing AIRR sequencing studies. These recommendations will be implemented in several public repositories, including the NCBI sequence read archive (SRA). Submissions to SRA typically use a flat-file template and include only a minimal amount of term validation. In order to ease the metadata authoring and to implement the ontological terms validation of repertoire sequence data, we are developing an interactive template through CEDAR workbench that will allow for ontological validation, and subsequent deposition in SRA. CEDAR workbench also allows the user to populate the template with metadata for data submission to various data repositories. The incorporation of template-element level ontology mapping not only facilitates validation of data submission, but also enables intelligent queries within and across repositories.

Online biomedical repositories contain a wealth of freely available data submitted by the research community, but to reuse this data in further studies requires well-annotated associated metadata. There is a growing set of community-developed standards for creating this metadata, often in the form of templates; still, the difficulties of working with these standards are significant. The Center for Expanded Data Annotation and Retrieval (CEDAR) is building an end-to-end system to ease the authoring of metadata and the templates. This system targets the creation of higher quality metadata to facilitate data discovery, interoperability, and reuse. With our public release in September 2016, we now support many new features which make authoring easier.Template and Metadata Repository: We developed a standardized representation of metadata and the templates that describe them, together with Web-based services to store, search, and share these resources. Templates created using CEDAR technology are stored in our openly accessible community repository, and can now be shared with other people and groups. Researchers can search for templates to annotate their studies, and share their metadata with others. We’ve now added Web-based interfaces and REST APIs to facilitate access to templates, and all the metadata collected using those templates.Template and Metadata Editor: We developed highly interactive Web-based tools to simplify the process of authoring metadata and templates. The Template Editor allows users to create, search, and author templates. An upgraded feature provides interoperation with ontologies: interactive look-up services linked to NCBO’s BioPortal (bioportal.bioontology.org) let template authors find ontology terms to annotate fields in their templates and to define possible values of fields, including creating new terms and value sets. The Metadata Editor, which creates a forms-based acquisition interface from a template, has been redesigned so users can more easily populate metadata based on the template fields.