Category Archives: oa.ontologies

Mayernik | The Role of Metadata and Vocabulary Standards in Enabling Scientific Data Interoperability: A Study of Earth System Science Data Facilities | Journal of eScience Librarianship

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Abstract:  Objective: Journal publishers within many sciences are increasingly expecting data to be deposited into repositories that support the FAIR principles. Data repositories are thus needing to determine what implications the FAIR principles have on their existing services and systems. Metadata standards and controlled vocabularies are specifically called out as core components of the FAIR principles related to interoperability.

Methods: This paper looks specifically at the ways that metadata standards and controlled vocabularies are used by Earth system science data repositories. Data sets from 55 data facilities were examined to determine which metadata standards and controlled subject / keyword vocabularies were used. 

Results: The findings indicate that only the ISO 19115:2003 and DataCite metadata standards are used by more than 40% of the data facilities, and the NASA Global Change Master Directory (GCMD) keywords are the only keyword vocabulary of broad use within this community. 

Conclusions: These findings raise questions about the extent to which metadata standards and keyword vocabularies can facilitate interoperability beyond narrow sub-sections of the data facility communities. This study also points to systematic challenges related to migration to new standards.

DCMI: Webinar – Applying FAIR Principles to Ontologies

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“This webinar addresses ontologies for the semantic web and how FAIR principles could be applied to ontologies. This includes metadata best practices and registries to publish the ontologies as Linked Open Vocabularies. Objectives are: To become familiar with ontologies for the semantic web and linked data principles; To become familiar with FAIR principles; To understand how FAIR principles could be applied to ontologies.”

Software review: The JATSdecoder package—extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central’s open access database | SpringerLink

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Abstract:  JATSdecoder is a general toolbox which facilitates text extraction and analytical tasks on NISO-JATS coded XML documents. Its function JATSdecoder() outputs metadata, the abstract, the sectioned text and reference list as easy selectable elements. One of the biggest repositories for open access full texts covering biology and the medical and health sciences is PubMed Central (PMC), with more than 3.2 million files. This report provides an overview of the PMC document collection processed with JATSdecoder(). The development of extracted tags is displayed for the full corpus over time and in greater detail for some meta tags. Possibilities and limitations for text miners working with scientific literature are outlined. The NISO-JATS-tags are used quite consistently nowadays and allow a reliable extraction of metadata and text elements. International collaborations are more present than ever. There are obvious errors in the date stamps of some documents. Only about half of all articles from 2020 contain at least one author listed with an author identification code. Since many authors share the same name, the identification of person-related content is problematic, especially for authors with Asian names. JATSdecoder() reliably extracts key metadata and text elements from NISO-JATS coded XML files. When combined with the rich, publicly available content within PMCs database, new monitoring and text mining approaches can be carried out easily. Any selection of article subsets should be carefully performed with in- and exclusion criteria on several NISO-JATS tags, as both the subject and keyword tags are used quite inconsistently.

 

 

OER OpenGLAM Ontologies: Metadata for Educational Justice | Mozilla Festival 2021 Schedule

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Education was already moving online, when covid19 hit; now learners, K-12 to grad school and beyond seek and find knowledge virtually and voraciously, even outside formal schooling. Meanwhile, museum educators open treasuries of educational digital cultural objects to locked-down publics. OER OpenGLAM promises to free knowledge. Openness counters copyright and paywalls, but it can re-entrench cultural appropriation and omissions. Not “neutral,” metadata reproduces particular cultural perspectives and biases. A digital crossroads arises: the colonial legacies of museum collections and academic canons get reproduced in OER–unless interrupted. What is the pedagogical and methodological potential of metadata, for tracing and transcending the plunder and empire embodied in digital cultural heritage objects’ journeys? These encounters teach critical analysis, agency, anticolonial dreaming, indigenous data sovereignty. We invite educators to think through descriptive metadata and geographic taxonomy as useful platforms for recovering, reclaiming, layering, and liberating cultural knowledges and diverse ontologies.

OER OpenGLAM Ontologies: Metadata for Educational Justice | Mozilla Festival 2021 Schedule

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Education was already moving online, when covid19 hit; now learners, K-12 to grad school and beyond seek and find knowledge virtually and voraciously, even outside formal schooling. Meanwhile, museum educators open treasuries of educational digital cultural objects to locked-down publics. OER OpenGLAM promises to free knowledge. Openness counters copyright and paywalls, but it can re-entrench cultural appropriation and omissions. Not “neutral,” metadata reproduces particular cultural perspectives and biases. A digital crossroads arises: the colonial legacies of museum collections and academic canons get reproduced in OER–unless interrupted. What is the pedagogical and methodological potential of metadata, for tracing and transcending the plunder and empire embodied in digital cultural heritage objects’ journeys? These encounters teach critical analysis, agency, anticolonial dreaming, indigenous data sovereignty. We invite educators to think through descriptive metadata and geographic taxonomy as useful platforms for recovering, reclaiming, layering, and liberating cultural knowledges and diverse ontologies.

A protocol for adding knowledge to Wikidata, a case report | bioRxiv

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Abstract:  Pandemics, even more than other scientific questions, require swift integration of knowledge and identifiers. In a setting where there is a large number of loosely connected projects and initiatives, we need a common ground, also known as a “commons”. Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons, but Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modelled with entity schemas represented by shape expressions. As a telling example, we describe the process of aligning resources on the genomics of the SARS-CoV-2 virus and related viruses as well as how shape expressions can be defined for Wikidata helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable, is demonstrated by integrating data from NCBI Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates. Although this workflow is developed and applied in the context of the SARS-CoV-2 pandemic, it was also applied to other human coronaviruses (MERS, SARS, SARS-CoV-2, Human Coronavirus NL63, Human coronavirus 229E, Human coronavirus HKU1, Human coronavirus OC4) to demonstrate its broader applicability.

 

KNOWLEDGE BASE ON EPIDEMICS FROM AMELICA/REDALYC JOURNALS

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“In the face of a global health contingency, the vital role of Open Access is endorsed: to bring knowledge to all corners of the world, to allow science to be quickly and timely accessible so that its contribution is reflected in the improvement of the quality of human life , in saving lives and in the development of a better society for all. Open Access initiatives such as Redalyc have been working towards this goal for 18 years. Today, the AmeliCA/Redalyc alliance reaffirms its commitment to Open Access and continues to develop technology which it is now applied to the semantic dissemination of articles published on topics of interest in epidemiology, pandemics and related topics. This development enable to publish more than 6 thousand articles in Linked Open Data (LOD) format so that they can be processed and interconnected in the LOD knowledge cloud and allow users to browse content and access to full-texts in a thematic discovery service….”
 

AmeliCA/Redalyc1 run an ontology-based algorithm, previously developed called OntoOAI (Becerril-Garci?a & Aguado-Lopez, 2018), on their databases to extract epidemics-related content. The results include: an ontology representation of the knowledge published in 6,557 scientific articles including concepts and relations, as well as their attributes, a directed-graph thematic content browser to access to full-texts and a dataset available at SPARQL endpoint to query the results as part of Linked Open Data….”

 

 

The SPAR Ontologies

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“Over the past eight years, we have been involved in the development of a set of complementary and orthogonal ontologies that can be used for the description of the main areas of the scholarly publishing domain, known as the SPAR (Semantic Publishing and Referencing) Ontologies. In this paper, we introduce this suite of ontologies, discuss the basic principles we have followed for their development, and describe their uptake and usage within the academic, institutional and publishing communities….”