Descriptive Metadata Research Articles

Institutional Metadata and the Problem of Context

Abstract The traditional archive catalogue constitutes a form of structural and descriptive metadata that long precedes the internet; and the cataloguing of photographs is just one part of a process of archival administration. The application of keywords to images contrasts with archival prose description, which is based on the visual content of the image and is predominantly context-free; a remediation of the image itself. At the heart of this lies the notion that the single photograph is itself devoid of context; it is a discrete embodiment of shutter time and there is nothing certain either side of that. Thus, one can only speculate at its context, and institutional description techniques actively avoid such speculation. Yet context in the archive is ever-present and key to the function of images as objects of information and evidence. It is built through static relationships, through the situating of photographs in accordance with the concept of original order, and it is replicated through storage systems and hierarchical catalogue entries. Such orders, hierarchies and relationships are absent within sets of images that are brought together by keyword search, including through the websites of archival institutions that struggle to reconcile archival principles and identity with network culture. Images are transported to places where contextual information is at best difficult to access, especially for those unfamiliar with archival interfaces. In contrast to the controlled stasis of archival storage and interconnected recordkeeping systems, network storage is messy, unstable and poorly described. However, we must accept that context is not a prerequisite for many users, and for them the networking of archival images denotes a freedom; a democratisation of the archive. But in a media-driven society that is becoming more and more indifferent to the evidential value of documents of any kind, the context-free image is left predisposed to exploitation.

Metadata description of the ORCA database (ORganic and Conventional Agriculture's impact on aquatic biodiversity)

The database of the ORCA project (A comparative analysis of ORganic and Conventional Agriculture's impact on aquatic biodiversity) comprises species occurrence data of different organism groups (zooplankton, macro-invertebrates, macrophytes, amphibians (eDNA) and fish (eDNA)) and data on physical, chemical and morphometric variables of 48 small farmland ponds distributed over Flanders, Belgium.

Challenges for FAIR-compliant description and comparison of crop phenotype data with standardized controlled vocabularies.

Crop phenotypic data underpin many pre-breeding efforts to characterize variation within germplasm collections. Although there has been an increase in the global capacity for accumulating and comparing such data, a lack of consistency in the systematic description of metadata often limits integration and sharing. We therefore aimed to understand some of the challenges facing findable, accesible, interoperable and reusable (FAIR) curation and annotation of phenotypic data from minor and underutilized crops. We used bambara groundnut (Vigna subterranea) as an exemplar underutilized crop to assess the ability of the Crop Ontology system to facilitate curation of trait datasets, so that they are accessible for comparative analysis. This involved generating a controlled vocabulary Trait Dictionary of 134 terms. Systematic quantification of syntactic and semantic cohesiveness of the full set of 28 crop-specific COs identified inconsistencies between trait descriptor names, a relative lack of cross-referencing to other ontologies and a flat ontological structure for classifying traits. We also evaluated the Minimal Information About a Phenotyping Experiment and FAIR compliance of bambara trait datasets curated within the CropStoreDB schema. We discuss specifications for a more systematic and generic approach to trait controlled vocabularies, which would benefit from representation of terms that adhere to Open Biological and Biomedical Ontologies principles. In particular, we focus on the benefits of reuse of existing definitions within pre- and post-composed axioms from other domains in order to facilitate the curation and comparison of datasets from a wider range of crops. Database URL: https://www.cropstoredb.org/cs_bambara.html

A streamlined workflow for conversion, peer review, and publication of genomics metadata as omics data papers.

BackgroundData papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability.ObjectiveWe aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript.MethodsAn omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases.FindingsThe template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing.ConclusionThe omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility.

Citing and referencing habits in medicine and social sciences journals in 2019

PurposeThis article explores citing and referencing systems in social sciences and medicine articles from different theoretical and practical perspectives, considering bibliographic references as a facet of descriptive representation.Design/methodology/approachThe analysis of citing and referencing elements (i.e. bibliographic references, mentions, quotations and respective in-text reference pointers) identified citing and referencing habits within disciplines under consideration and errors occurring over the long term as stated by previous studies now expanded. Future expected trends of information retrieval from bibliographic metadata was gathered by approaching these referencing elements from the Functional Requirements for Bibliographic Records (FRBR) entities concepts.FindingsReference styles do not fully accomplish with their role of guiding authors and publishers on providing concise and well-structured bibliographic metadata within bibliographic references. Trends on representative description revision suggest a predicted distancing on the ways information is approached by bibliographic references and bibliographic catalogs adopting FRBR concepts, including the description levels adopted by each of them under the perspective of the FRBR entities concept.Research limitations/implicationsThis study was based on a subset of medicine and social sciences articles published in 2019 and, therefore, it may not be taken as a final and broad coverage. Future studies expanding these approaches to other disciplines and chronological periods are encouraged.Originality/valueBy approaching citing and referencing issues as descriptive representation's facets, findings on this study may encourage further studies that will support information science and computer science on providing tools to become bibliographic metadata description simpler, better structured and more efficient facing the revision of descriptive representation actually in progress.

Improving Discovery and Use of NASA’s Earth Observation Data Through Metadata Quality Assessments

High quality descriptive metadata is essential to enabling the effective discovery of Earth observation data to a growing number of diverse users. In this paper, we define a framework to assess the quality of NASA’s Earth observation metadata with the overarching goal of improving the discoverability, accessibility and usability of the data it describes. The framework, developed by the Analysis and Review of the Common Metadata Repository (ARC) team, focuses on the metadata quality dimensions of correctness, completeness, and consistency. The methodology used by the ARC team to implement the framework is described, as well as best practices, lessons learned and recommendations for implementing similar metadata quality assessment processes. Initial results from the project indicate that this methodology, in combination with community and stakeholder collaboration, is effective in improving metadata quality.

Implementing a Registry Federation for Materials Science Data Discovery.

As a result of a number of national initiatives, we are seeing rapid growth in the data important to materials science that are available over the web. Consequently, it is becoming increasingly difficult for researchers to learn what data are available and how to access them. To address this problem, the Research Data Alliance (RDA) Working Group for International Materials Science Registries (IMRR) was established to bring together materials science and information technology experts to develop an international federation of registries that can be used for global discovery of data resources for materials science. A resource registry collects high-level metadata descriptions of resources such as data repositories, archives, websites, and services that are useful for data-driven research. By making the collection searchable, it aids scientists in industry, universities, and government laboratories to discover data relevant to their research and work interests.We present the results of our successful piloting of a registry federation for materials science data discovery. In particular, we out a blueprint for creating such a federation that is capable of amassing a global view of all available materials science data, and we enumerate the requirements for the standards that make the registries interoperable within the federation. These standards include a protocol for exchanging resource descriptions and a standard metadata schema for encoding those descriptions. We summarize how we leveraged an existing standard (OAI-PMH) for metadata exchange. Finally, we review the registry software developed to realize the federation and describe the user experience.

Challenges with organization, discoverability and access in Canadian open health data repositories.

IntroductionOpen health data provides healthcare professionals, biomedical researchers and the general public with access to health data which has the potential to improve healthcare delivery and policy. The challenge is to create and implement appropriate metadata, or structured data about the data, to ensure that data are easy to discover, access and re-use. The goal of this study is to identify, evaluate and compare Canadian open health data repositories for their searching, browsing and navigation functionalities, the richness of their metadata description practices, and their metadata-based filtering mechanisms.MethodsMetadata-based search and browsing was evaluated in addition to the number and nature of metadata elements. Six Canadian open health data repositories across national, provincial and institutional levels were evaluated. Data collected using verbatim text recording was evaluated using an analytical framework based on the 2019 Dataverse North Metadata Best Practices guide and 2019 Data Citation Implementation Project roadmap.ResultsAll repositories required filtering to access “open health data.” All repositories included ‘subject’ facets for filtering, and ‘title’ and ‘description’ on the Results List. Use case evaluations suggest improvements including advanced search, health-specific search terms, records for all repositories, and links to related publications.DiscussionConsistent use of ‘title’ and ‘description’ suggests that an interoperable interface is possible. Inconsistencies in records indicate the need for explicit, easy to find mechanisms to access metadata in repositories. The analytical framework represents first draft guidelines for metadata creation and implementation to improve organization, discoverability, and access to Canadian open health data.

How to Increase the Value of Digital Badges for Assessment and Recognition in Higher Education. A University Case

The main goal of this research is to enhance the understanding of quality criteria for DB metadata for assessment and recognition as factors increasing their value in higher education (HE). To attain this goal, a case study approach centered in one HE institution was used, aiming (a) at an analysis of the status quo description of metadata of DBs issued by the HE institution to identify the value of DBs in terms of assessment and recognition procedures, and (b) a list of quality criteria for DB description metadata was proposed on the basis of academic research and on expert interview results. The results of the research demonstrate that in the institution under research, these criteria are not present in most cases of DB descriptions as teachers do not provide them. Distinct assessment and recognition criteria make an important quality factor for the DBs to become valid and valued digital credentials in HE.

What an Image Is

This article investigates how images are understood inside and outside heritage institutions. It focuses on information specialists in libraries, archives, and museums and on a very specific yet substantial end-user group for visual heritage material: university scholars in the humanities. Based on a survey on the production and use of descriptive metadata, this study discloses that there is an ontological divide between these two groups, and that the extensive production of descriptive metadata does not match the needs and interest of researchers in the humanities, but rather other end users. An increased dialogue is needed between these two groups concerning what metadata should be attached to images. This potentially could lead to a broader and more extended scholarly use of visual heritage material.

Plasmonic Anticounterfeit Tags with High Encoding Capacity Rapidly Authenticated with Deep Machine Learning.

Counterfeit goods create significant economic losses and product failures in many industries. Here, we report a covert anticounterfeit platform where plasmonic nanoparticles (NPs) create physically unclonable functions (PUFs) with high encoding capacity. By allowing anisotropic Au NPs of different sizes to deposit randomly, a diversity of surfaces can be facilely tagged with NP deposits that serve as PUFs and are analyzed using optical microscopy. High encoding capacity is engineered into the tags by the sizes of the Au NPs, which provide a range of color responses, while their anisotropy provides sensitivity to light polarization. An estimated encoding capacity of 270n is achieved, which is one of the highest reported to date. Authentication of the tags with deep machine learning allows for high accuracy and rapid matching of a tag to a specific product. Moreover, the tags contain descriptive metadata that is leveraged to match a tag to a specific lot number (i.e., a collection of tags created in the same manner from the same formulation of anisotropic Au NPs). Overall, integration of designer plasmonic NPs with deep machine learning methods can create a rapidly authenticated anticounterfeit platform with high encoding capacity.

Decentralized geospatial metadata management

Metadata descriptions are typically monolithic data structures and their denormalized, text-based nature yields shortcomings such as inconsistencies and heterogeneities. Moreover, fluidity of research environments, coupled with single-tenancy of metadata descriptions, impedes enforcing authority on the related datasets effectively. We propose a novel paradigm for metadata articulation, delegation, that helps solve the aforementioned issues. After elaborating on the requirements to this practice, we present two worked-out implementation examples in the domain of geospatial metadata and discuss its advantages with respect to key issues in this domain; namely, metadata consistency, interoperability, and mitigating semantic heterogeneity. The technique and the supporting software we present are equally applicable to any XML-based metadata schema and application domain.

An indexing system for the relevance of academic production and research from digital repositories and metadata

PurposeThis paper aims to propose a set of quantitative statistical indicators for measuring the scientific relevance of research groups and researchers, based on high-impact open-access digital production repositories.Design/methodology/approachAn action research (AR) methodology is proposed in which research is associated with the practice; research informs practice and practice is responsible for informing research in a cooperative way. AR is divided into five phases, beginning with the definition of the problematic scenario and an analysis of the state of the art and ending with conducting tests and publishing the results.FindingsThe proposed indicators were used to characterise group and individual output in a major public university in south-eastern Mexico. University campuses hosting a large number of high-impact research groups. These indicators were very useful in generating information that confirmed specific assumptions about the scientific production of the university.Research limitations/implicationsThe data used here were retrieved from Scopus and open access national repository of Mexico. It would be possible to use other data sources to calculate these indicators.Practical implicationsThe system used to implement the proposed indicators is independent of any particular technological tool and is based on standards for metadata description and exchange, thus facilitating the easy integration of new elements for evaluation.Social implicationsMany organisations evaluate researchers according to specific criteria, one of which is the prestige of journals. Although the guidelines differ between evaluation bodies, relevance is measured based on elements that can be adapted and where some have greater weight than others, including the prestige of the journal, the degree of collaboration with other researchers and individual production, etc. The proposed indicators can be used by various entities to evaluate researchers and research groups. Each country has its own organisations that are responsible for evaluation, using various criteria based on the impact of the publications.Originality/valueThe proposed indicators assess based on the importance of the types of publications and the degree of collaborations. However, they can be adapted to other similar scenarios.

UniBioDicts: Unified access to Biological Dictionaries.

SummaryWe present a set of software packages that provide uniform access to diverse biological vocabulary resources that are instrumental for current biocuration efforts and tools. The Unified Biological Dictionaries (UniBioDicts or UBDs) provide a single query-interface for accessing the online API services of leading biological data providers. Given a search string, UBDs return a list of matching term, identifier and metadata units from databases (e.g. UniProt), controlled vocabularies (e.g. PSI-MI) and ontologies (e.g. GO, via BioPortal). This functionality can be connected to input fields (user-interface components) that offer autocomplete lookup for these dictionaries. UBDs create a unified gateway for accessing life science concepts, helping curators find annotation terms across resources (based on descriptive metadata and unambiguous identifiers), and helping data users search and retrieve the right query terms.Availability and implementationThe UBDs are available through npm and the code is available in the GitHub organisation UniBioDicts (https://github.com/UniBioDicts) under the Affero GPL license.Supplementary information Supplementary data are available at Bioinformatics online.

ATLAS in-file metadata and multi-threaded processing

Processing and scientific analysis of the data taken by the ATLAS experiment requires reliable information describing the event data recorded by the detector or generated in software. ATLAS event processing applications store such descriptive metadata information in the output data files along with the event information. To better leverage the available computing resources during LHC Run3 the ATLAS experiment has migrated its data processing and analysis software to a multi-threaded framework: AthenaMT. Therefore in-file metadata must support concurrent event processing, especially around input file boundaries. The in-file metadata handling software was originally designed for serial event processing. It grew into a rather complex system over the many years of ATLAS operation. To migrate this system to the multi-threaded environment it was necessary to adopt several pragmatic solutions, mainly because of the shortage of available person-power to work on this project in early phases of the AthenaMT development. In order to simplify the migration, first the redundant parts of the code were cleaned up wherever possible. Next the infrastructure was improved by removing reliance on constructs that are problematic during multi-threaded processing. Finally, the remaining software infrastructure was redesigned for thread safety.

LifeWatch observatory data: phytoplankton observations in the Belgian Part of the North Sea.

BackgroundThis paper describes a phytoplankton data series generated through systematic observations in the Belgian Part of the North Sea (BPNS). Phytoplankton samples were collected during multidisciplinary sampling campaigns, visiting nine nearshore stations with monthly frequency and an additional eight offshore stations on a seasonal basis.New informationThe data series contain taxon-specific phytoplankton densities determined by analysis with the Flow Cytometer And Microscope (FlowCAM®) and associated image-based classification. The classification is performed by two separate semi-automated classification systems, followed by manual validation by taxonomic experts. To date, 637,819 biological particles have been collected and identified, yielding a large dataset of validated phytoplankton images. The collection and processing of the 2017–2018 dataset are described, along with its data curation, quality control and data storage. In addition, the classification of images using image classification algorithms, based on convolutional neural networks (CNN) from 2019 onwards, is also described. Data are published in a standardised format together with environmental parameters, accompanied by extensive metadata descriptions and finally labelled with digital identifiers for traceability. The data are published under a CC‐BY 4.0 licence, allowing the use of the data under the condition of providing the reference to the source.

FAIR‐compliant clinical, radiomics and DICOM metadata of RIDER, interobserver, Lung1 and head‐Neck1 TCIA collections

Purpose One of the most frequently cited radiomics investigations showed that features automatically extracted from routine clinical images could be used in prognostic modeling. These images have been made publicly accessible via The Cancer Imaging Archive (TCIA). There have been numerous requests for additional explanatory metadata on the following datasets — RIDER, Interobserver, Lung1, and Head–Neck1. To support repeatability, reproducibility, generalizability, and transparency in radiomics research, we publish the subjects’ clinical data, extracted radiomics features, and digital imaging and communications in medicine (DICOM) headers of these four datasets with descriptive metadata, in order to be more compliant with findable, accessible, interoperable, and reusable (FAIR) data management principles. Acquisition and validation methods Overall survival time intervals were updated using a national citizens registry after internal ethics board approval. Spatial offsets of the primary gross tumor volume (GTV) regions of interest (ROIs) associated with the Lung1 CT series were improved on the TCIA. GTV radiomics features were extracted using the open-source Ontology-Guided Radiomics Analysis Workflow (O-RAW). We reshaped the output of O-RAW to map features and extraction settings to the latest version of Radiomics Ontology, so as to be consistent with the Image Biomarker Standardization Initiative (IBSI). Digital imaging and communications in medicine metadata was extracted using a research version of Semantic DICOM (SOHARD, GmbH, Fuerth; Germany). Subjects’ clinical data were described with metadata using the Radiation Oncology Ontology. All of the above were published in Resource Descriptor Format (RDF), that is, triples. Example SPARQL queries are shared with the reader to use on the online triples archive, which are intended to illustrate how to exploit this data submission. Data format The accumulated RDF data are publicly accessible through a SPARQL endpoint where the triples are archived. The endpoint is remotely queried through a graph database web application at http://sparql.cancerdata.org. SPARQL queries are intrinsically federated, such that we can efficiently cross-reference clinical, DICOM, and radiomics data within a single query, while being agnostic to the original data format and coding system. The federated queries work in the same way even if the RDF data were partitioned across multiple servers and dispersed physical locations. Potential applications The public availability of these data resources is intended to support radiomics features replication, repeatability, and reproducibility studies by the academic community. The example SPARQL queries may be freely used and modified by readers depending on their research question. Data interoperability and reusability are supported by referencing existing public ontologies. The RDF data are readily findable and accessible through the aforementioned link. Scripts used to create the RDF are made available at a code repository linked to this submission: https://gitlab.com/UM-CDS/FAIR-compliant_clinical_radiomics_and_DICOM_metadata.

The Diversity Paradox

Abstract At the core of museum practice is the notion of diversity. However, as this analysis of different types of metadata production shows, contradictory ideas and ideals pervade both metadata production among information specialists (i.e. archivists, metadata managers, curators working in the heritage institutions), and the systems for, and practices of, participatory metadata production. While the discourse on metadata standards is permeated by ideas of objectivity and interoperability the field is, in practice, far from coherent, being marked by a great variety as regards templates, formats and vocabularies. Conversely, the discourse on digital participation in the cultural heritage is permeated with notions of diversity, as means to increase democracy and support variety. In practice, however, the available crowdsourcing platforms are often formulaic offering few possibilities for the crowd to add individual interpretations and their own agenda. This analysis of the practice of producing descriptive metadata reveals the complex, multifaceted implications of notions of diversity for the cultural heritage. Diversity, meaning great variety, is then not solely a positive end in itself but can in fact hinder the distribution and linkability of information and thereby the creation and building of new knowledge. Likewise, participatory activities where heritage institutions reach out to the crowd do not automatically generate diversity as there is no direct correlation between the magnitude of the group and variability. To understand this complexity and acknowledge the, sometimes, contradictory demands and effects related to the notion and norms of diversity is at the core of the making and preservation of our cultural heritage.

What evidence exists on conservation actions to conserve insects? A protocol for a systematic map of literature reviews

BackgroundInsects play a central role in the functioning of terrestrial and freshwater ecosystems and contribute to a multitude of ecosystem services in managed and unmanaged systems Even local declines of insect abundance and richness can have enormous ecological and economic consequences. Evidence-informed conservation actions are essential to prevent potential cascading consequences of insect declines, and to help declining populations recover. Policy-makers rely on syntheses of primary research, such as reviews and meta-analyses, when making decisions about which conservation actions to implement. These evidence reviews vary in their quality, and do not necessarily synthesise the full range of scientific evidence found in the primary literature, which hampers decision-making. This evidence review map will identify, catalogue, and describe evidence reviews that investigate actions and policies to conserve insect biodiversity. This will help policy makers identify relevant reviews and researchers to identify synthesis gaps. It will also generate a list of conservation actions which can feed into future synthesis projects. We will produce an interactive database of evidence reviews, acting as a bibliography for policy-makers, curate a list of insect conservation actions that have been reviewed, and identify synthesis gaps for conservation actions that have not been reviewed.MethodsWe will search for evidence reviews across seven large, generic bibliographic databases, a database of environmental reviews, and five grey literature resources using a search string consisting of an insect substring, a biodiversity or population response substring, an evidence synthesis substring, and a conservation substring. The results will be deduplicated and then screened at title and abstract (concurrently) and full text levels against predefined inclusion criteria. We will initially perform consistency checking on a subset of records at each level to ensure the inclusion criteria are sufficiently clear and understood by multiple reviewers. We will extract a suite of descriptive meta-data from relevant reviews, including a description of the action and information on each review’s focal taxa, biomes, and locations. If resources allow, we will apply the CEESAT critical appraisal tool for evidence reviews to assess validity of individual records and the evidence base as a whole. We will summarise our findings in an interactive database of reviews and other visualisations, including evidence atlases and heat maps (cross tabulations of the volume of evidence across two categorical variables). The findings of the evidence review map will support the identification of synthesis gaps and clusters that may warrant further attention through secondary research.

Worldwide version-controlled database of glacier thickness observations

Abstract. Although worldwide inventories of glacier area have been coordinated internationally for several decades, a similar effort for glacier ice thicknesses was only initiated in 2013. Here, we present the third version of the Glacier Thickness Database (GlaThiDa v3), which includes 3 854 279 thickness measurements distributed over roughly 3000 glaciers worldwide. Overall, 14 % of global glacier area is now within 1 km of a thickness measurement (located on the same glacier) – a significant improvement over GlaThiDa v2, which covered only 6 % of global glacier area and only 1100 glaciers. Improvements in measurement coverage increase the robustness of numerical interpolations and model extrapolations, resulting in better estimates of regional to global glacier volumes and their potential contributions to sea-level rise. In this paper, we summarize the sources and compilation of glacier thickness data and the spatial and temporal coverage of the resulting database. In addition, we detail our use of open-source metadata formats and software tools to describe the data, validate the data format and content against this metadata description, and track changes to the data following modern data management best practices. Archived versions of GlaThiDa are available from the World Glacier Monitoring Service (e.g., v3.1.0, from which this paper was generated: https://doi.org/10.5904/wgms-glathida-2020-10; GlaThiDa Consortium, 2020), while the development version is available on GitLab (https://gitlab.com/wgms/glathida, last access: 9 November 2020).