Metadata Authoring Research Articles

Machine actionable metadata models

Community-developed minimum information checklists are designed to drive the rich and consistent reporting of metadata, underpinning the reproducibility and reuse of the data. These reporting guidelines, however, are usually in the form of narratives intended for human consumption. Modular and reusable machine-readable versions are also needed. Firstly, to provide the necessary quantitative and verifiable measures of the degree to which the metadata descriptors meet these community requirements, a requirement of the FAIR Principles. Secondly, to encourage the creation of standards-driven templates for metadata authoring, especially when describing complex experiments that require multiple reporting guidelines to be used in combination or extended. We present new functionalities to support the creation and improvements of machine-readable models. We apply the approach to an exemplar set of reporting guidelines in Life Science and discuss the challenges. Our work, targeted to developers of standards and those familiar with standards, promotes the concept of compositional metadata elements and encourages the creation of community-standards which are modular and interoperable from the onset.

Streamlined Conversion of Omics Metadata into Manuscript Facilitates Publishing and Reuse of Omics Data

Data papers have started to gain popularity as a publishing format that allows easy and quick publishing of research data (Chavan and Penev 2011, Penev et al. 2017). They describe single or multiple datasets and the methodologies required for their generation. Similar to traditional research articles, data papers and the underlying datasets are peer-reviewed. In this poster, we demonstrate how data papers can be used to incentivise researchers producing omics datasets to increase the quality of the metadata descriptors and the data itself through the journal authoring, peer review and publication process, thus improving data visibility, discoverability, sharing and reuse. We illustrate a highly automated workflow for the creation of omics data paper manuscripts, which started with the development of a template for this specific article type in the Biodiversity Data Journal (BDJ), published by Pensoft (Dimitrova et al. 2020). The workflow streamlines automatic conversion and import of metadata from the European Nucleotide Archive (ENA) into an omics data paper manuscript created in the ARPHA Writing Tool (AWT), following a three step procedure: mapping of the European Nucleotide Archive (ENA) metadata to the manuscript sections, extraction of the relevant metadata through the ENA project or study ID, and transforming the metadata into HTML or XML files. The XML file follows the Journal Article Tag Suite (JATS) standard and can be used by anyone as a draft to further develop a data paper manuscript and submit it to any journal. mapping of the European Nucleotide Archive (ENA) metadata to the manuscript sections, extraction of the relevant metadata through the ENA project or study ID, and transforming the metadata into HTML or XML files. The XML file follows the Journal Article Tag Suite (JATS) standard and can be used by anyone as a draft to further develop a data paper manuscript and submit it to any journal. Records in ENA sometimes have linked data in the ArrayExpress and BioSamples databases, which describe sequencing experiments and samples following the community-accepted metadata standards MINSEQE and MIxS. The workflow also retrieves such records and inserts them both into the omics data paper narrative and as supplementary data files. The workflow has been integrated with Pensoft's ARPHA platform but the conversion code is openly accessible on GitHub under the Apache 2.0 license and can be run as a R Shiny app. By openly providing access to the code and its implementation in a web application, we enable the full reproducibility of the streamlined import of ENA metadata into an omics data paper manuscript. The plan is to further develop the workflow to include the import of various other types of omics data and omics data repositories in addition to the currently supported ENA genomic data. The workflow reaffirms the important role of high-quality metadata for creating extended dataset descriptions, recognised by Chavan and Penev 2011. Conversion of metadata into a manuscript helped us discover many datasets with insufficient or inaccurate metadata. Hence, we hope that our workflow promotes not only omics data paper publishing but also better metadata authoring and curation.

Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases.

Metadata—the machine-readable descriptions of the data—are increasingly seen as crucial for describing the vast array of biomedical datasets that are currently being deposited in public repositories. While most public repositories have firm requirements that metadata must accompany submitted datasets, the quality of those metadata is generally very poor. A key problem is that the typical metadata acquisition process is onerous and time consuming, with little interactive guidance or assistance provided to users. Secondary problems include the lack of validation and sparse use of standardized terms or ontologies when authoring metadata. There is a pressing need for improvements to the metadata acquisition process that will help users to enter metadata quickly and accurately. In this paper, we outline a recommendation system for metadata that aims to address this challenge. Our approach uses association rule mining to uncover hidden associations among metadata values and to represent them in the form of association rules. These rules are then used to present users with real-time recommendations when authoring metadata. The novelties of our method are that it is able to combine analyses of metadata from multiple repositories when generating recommendations and can enhance those recommendations by aligning them with ontology terms. We implemented our approach as a service integrated into the CEDAR Workbench metadata authoring platform, and evaluated it using metadata from two public biomedical repositories: US-based National Center for Biotechnology Information BioSample and European Bioinformatics Institute BioSamples. The results show that our approach is able to use analyses of previously entered metadata coupled with ontology-based mappings to present users with accurate recommendations when authoring metadata.

Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

As any resources, ontologies, thesaurus, vocabularies and terminologies need to be described with relevant metadata to facilitate their identification, selection and reuse. For ontologies to be FAIR, there is a need for metadata authoring guidelines and for harmonization of existing metadata vocabularies—taken independently none of them can completely describe an ontology. Ontology libraries and repositories also have to play an important role. Indeed, some metadata properties are intrinsic to the ontology (name, license, description); other information, such as community feedbacks or relations to other ontologies are typically information that an ontology library shall capture, populate and consolidate to facilitate the processes of identifying and selecting the right ontology(ies) to use. We have studied ontology metadata practices by: (1) analyzing metadata annotations of 805 ontologies; (2) reviewing the most standard and relevant vocabularies (23 totals) currently available to describe metadata for ontologies (such as Dublin Core, Ontology Metadata Vocabulary, VoID, etc.); (3) comparing different metadata implementation in multiple ontology libraries or repositories. We have then built a new metadata model for our AgroPortal vocabulary and ontology repository, a platform dedicated to agronomy based on the NCBO BioPortal technology. AgroPortal now recognizes 346 properties from existing metadata vocabularies that could be used to describe different aspects of ontologies: intrinsic descriptions, people, date, relations, content, metrics, community, administration, and access. We use them to populate an internal model of 127 properties implemented in the portal and harmonized for all the ontologies. We—and AgroPortal’s users—have spent a significant amount of time to edit and curate the metadata of the ontologies to offer a better synthetized and harmonized information and enable new ontology identification features. Our goal was also to facilitate the comprehension of the agronomical ontology landscape by displaying diagrams and charts about all the ontologies on the portal. We have evaluated our work with a user appreciation survey which confirms the new features are indeed relevant and helpful to ease the processes of identification and selection of ontologies. This paper presents how to harness the potential of a complete and unified metadata model with dedicated features in an ontology repository; however, the new AgroPortal’s model is not a new vocabulary as it relies on preexisting ones. A generalization of this work is studied in a community-driven standardization effort in the context of the RDA Vocabulary and Semantic Services Interest Group.

The center for expanded data annotation and retrieval.

The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments.

Social Accessibility Action to Improve Quality of OER User-generated Video-classes and Associated Resources

Abstract Social Accessibility is an approach to shorten the time for making web content more accessible by allowing ICT volunteers to improve its quality through collaborative work. In this context new forms of volunteerism have emerged through the creative and innovative use of ICTs. The first action in social ICT volunteering at UNED, the largest public distance university in Spain, took place in 2013 by enrolling 13 student volunteers. In 2014, the second action started with promising outcomes and more than 60 volunteers. The overall project aimed to improve the accessibility of original user-generated video learning resources contained in a multimedia repository of the university commonly used by the vast community of a quarter of a million students. The video classes were textually transcribed, subtitled and converted into mp3 audio. Its semantic labelling in the repository was also improved through collaborative volunteer metadata authoring. Main contribution of this paper is to show the ICT-based volunteering experience and the corresponding discussion on main findings. The experience has demonstrated the capacity of ICTs to promote social innovation at the universities and bring about citizen empowerment, in this case developing conscious awareness of the difficulties that must be faced daily by people with functional diversity and the benefits of implementing universal web accessibility.

Exploratory Analysis of Collaborative Web Accessibility Improvement

The Web is becoming a platform for daily activities and is expanding the opportunities for collaboration among people all over the world. The effects of these innovations are seen not only in major Web services such as wikis and social networking services but also in accessibility services. Collaborative accessibility improvement has great potential to make the Web more adaptive. Screen reader users, developers, site owners, and any Web volunteers who want to help the users are invited into the activities to improve accessibility in a timely manner. The Social Accessibility Project is an experimental service for a new needs-driven improvement model based on collaborative metadata authoring technologies. In 20 months, about 19,000 pieces of metadata were created for more than 3,000 Web pages through collaboration based on 355 requests submitted from users. We encountered many challenges as we sought to create a new mainstream approach and created distinctive features in new user interfaces to address some of these challenges. Although the new features increased user participation, serious issues remain. The productivity of the volunteers exceeded our expectations, but we found large and important problems in the users’ lack of awareness of their own accessibility problems. This is a critical problem for sustaining the active use of the service, because about 70% of the improvement starts with a request from a user. Helping users with visual impairments understand the actual issues is a crucial and challenging topic, and will lead to improved accessibility. We first introduce examples of collaboration, analyze several kinds of statistics on the activities of the users and volunteers of the pilot service, and then discuss our findings and challenges. Five future foci are considered: site-wide metadata authoring, encouraging active participation by users, quality management for the created metadata, metadata for dynamic HTML applications, and collaborations with site owners.

Search engines tackle the desktop

As PC hard drives get bigger and new information sources become available, users will have much more data of different types, including multimedia, on their computers. This makes it increasingly difficult to find documents, e-mail messages, spreadsheets, audio clips, and other files. Current desktop-based search capabilities, such as those in Windows, are inadequate to meet this challenge. Desktop search features built into current operating systems, e-mail programs, and other applications have far fewer capabilities than Web search engines. They generally offer only simple keyword searches of a set of files, usually of a single file type. However, desktop search engines face the additional challenge of recognizing which of the many file types it is dealing with. The engines also must derive whatever metadata authors have chosen to include in e-mail notes, database files, and other document types. Desktop engines must be efficient and avoid imposing a substantial processing or memory load on the computer. Integrating desktop and Web search capabilities into the same application presents security and privacy challenges.

Metadata Broadcasting for Personalized Service: a Practical Solution

As the number of broadcasting channels and programs increases rapidly, the importance of personalized service has been emphasized. In this paper, we propose a practical framework of metadata broadcasting to provide personalized service according to user preferences and various terminal/network conditions. First, we present an overall system architecture of a metadata broadcasting system and then propose several core technologies (particularly in the parts of metadata authoring, metadata encoding, and metadata-based personalized content consumption). For interoperability, the proposed solution is designed to be compliant with the relevant standards of the TV-Anytime Forum, MPEG-7 Systems, and MPEG-2 Systems. Considering a home network environment, we also propose a metadata-based content adaptation scheme. Each component technology has been implemented individually, integrated into an end-to-end prototype broadcasting system, and successfully tested with a set of personalized service scenarios that are also developed in this study.

A visual approach to authoring XPath expressions

Web metadata is crucial for providing machine-understandable descriptions of Web resources, and has a number of applications such as discovery, qualification, and adaptation of Web contents. While metadata is often embedded into a target document, metadata can also be associated externally by means of an addressing scheme such as the XPath language. However, creation and modification of external metadata solely with a conventional editor is not easy because metadata authoring involves the maintenance and elaboration of addressing expressions as well as editing individual documents. The objective of this study is to advance extensibility in the design of annotation editors with particular emphasis on a visual approach to authoring XPath expressions. The key idea behind the XPath authoring process is to facilitate flexibility in the creation of XPath expressions as a result of the seamless integration of three authoring methods: instantaneous creation, context-constrained creation, and manual creation. In this paper, we briefly introduce a framework for external annotation first, and give a high-level overview of our annotation editor. The three XPath creation methods are then explained, showing examples of XPath expressions and the graphical user interface for visual authoring process. Finally, we present our annotation editor developed with the visual XPath authoring capability, and show how the annotation editor is customized for an annotation vocabulary at hand.

Managing Digital Educational Resources with the ARIADNE Metadata System

SUMMARY The primary goal of the ARIADNE project, supported by the European Commission, is to foster share and reuse of digital pedagogical material. For this purpose, a Europe-wide repository of reusable pedagogical documents, called the Knowledge Pool System (KPS), has been set up. One of the key features of the KPS is the underlying metadata specification, which has been used in extensive experiments. The ARIADNE metadata scheme includes both mandatory and optional elements, and is at the basis of the emerging Learning Objects Metadata standard, developed by the IEEE Learning Technology Standards Committee. This article presents the ARIADNE metadata scheme and discusses ARIADNE tools developed to support metadata authoring and indexing, database querying, and course development activities. A discussion of the ARIADNE community's experience is also presented.

Metadata Issues for ATSC Audio

The audio decoder in a consumer digital television (DTV) receiver conforming to the Advanced Television Systems Committee (ATSC) specification needs two types of data in order to work properly. The data stream it receives must contain coded audio as well as audio metadata. Audio metadata is a group of parameters that describes the audio program data being transmitted and controls some aspects of how the audio program is presented in the consumer's receiver. This paper will provide an overview of the audio metadata parameters. It will discuss the purpose of the parameters and how they are chosen. The paper will also discuss the effect that each of these parameters has on domestic receiver operation. The operational implications of authoring the different parameters at different points in the production or distribution chain will be examined. Some different methods for authoring the metadata will also be proposed. These methods will include those necessary during the transition period when proper metadata authoring and monitoring equipment may not exist.