Strategies for Assembling the Biodiversity Knowledge Graph

This talk explores different strategies for assembling the “biodiversity knowledge graph” (Page 2016). The first is a centralised, crowd-sourced approach using Wikidata as the foundation. Wikidata is becoming increasingly attractive as a knowledge graph for the life sciences (Waagmeester et al. 2020), and I will discuss some of its strengths and limitations, particularly as a source of bibliographic and taxonomic information. For example, Wikidata’s handling of taxonomy is somewhat problematic given the lack of clear separation of taxa and their names. A second approach is to build biodiversity knowledge graphs from scratch, such as OpenBioDiv (Penev et al. 2019) and my own Ozymandias (Page 2019). These approaches use either generalised vocabularies such as schema.org, or domain specific ones such as TaxPub (Catapano 2010) and the Semantic Publishing and Referencing Ontologies (SPAR) (Peroni and Shotton 2018), and to date tend to have restricted focus, whether geographic (e.g., Australian animals in Ozymandias) or temporal (recent taxonomic literature, OpenBioDiv). A growing number of data sources are now using schema.org to describe their data, including ORCID and Zenodo, and efforts to extend schema.org into biology (Bioschemas) suggest we may soon be able to build comprehensive knowledge graphs using just schema.org and its derivatives. A third approach is not to build an entire knowledge graph, but instead focus on constructing small pieces of the graph tightly linked to supporting evidence, for example via annotations. Annotations are increasingly used to mark up both the biomedical literature (e.g., Kim et al. 2015, Venkatesan et al. 2017) and the biodiversity literature (Batista-Navarro et al. 2017). One could argue that taxonomic databases are essentially lists of annotations (“this name appears in this publication on this page”), which suggests we could link literature projects such as the Biodiversity Heritage Library (BHL) to taxonomic databases via annotations. Given that the International Image Interoperability Framework (IIIF) provides a framework for treating publications themselves as a set of annotations (e.g., page images) upon which other annotations can be added (Zundert 2018), this suggests ways that knowledge graphs could lead directly to visualising the links between taxonomy and the taxonomic literature. All three approaches will be discussed, accompanied by working examples.

Deconstructing the Scholarly Paper. Ontologies for Semantic Publishing

Cel/Teza: Celem artykułu jest charakterystyka trzech ontologii opracowanych na potrzeby semantycznego publikowania, których przedmiotem opisu jest artykuł naukowy: SciAnnotDoc, Scholarly Papers Vocabulary with Focus on Qualtitative Analysis, Document Components Ontology.Koncepcja/Metody badań: Przeprowadzona charakterystyka ontologii wpisuje się w koncepcję oceny ontologii opartej na interpretacji obecnych w niej postulatów znaczeniowych. Charakterystyka każdej ontologii obejmuje określenie jej zakresu tematycznego, kontekstu powstania, podstawowych założeń ontologicznych oraz próbę ujawnienia jej postaw epistemicznych.Wyniki i wnioski: Charakterystyka struktur pojęciowych leżących u podstaw trzech ontologii sieciowych, których celem była reprezentacja artykułu naukowego na potrzeby semantycznego publikowania daje obraz modelu konceptualnego tego artefaktu naukowego, w którym przede wszystkim eksponuje się elementy pełniące określoną funkcję retoryczną. W przeanalizowanych przypadkach model IMRaD nie był podstawowym schematem organizacji treści artykułu naukowego. Ujawnienie postaw epistemicznych w procesie projektowania ontologii nie było możliwe we wszystkich przypadkach. Tam, gdzie jednak udało się to określić, widać zarówno postawy obiektywistyczne, jak i interpretatywne, a także obecność determinantów o charakterze pragmatycznym.Oryginalność/Wartość poznawcza: Modelowanie konceptualne, będące jednym z początkowych etapów projektowania ontologii, jest zdeterminowane określoną postawą epistemiczną, tzn. stosunkiem projektanta do rzeczywistości, który za pomocą ontologii stara się odwzorować jej fragment. Ujawnienie takich postaw jest istotne z punktu widzenia zrozumienia kontekstu postulatów znaczeniowych obecnych w ontologiach sieciowych.

OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science

Hundreds of years of biodiversity research have resulted in the accumulation of a substantial pool of communal knowledge; however, most of it is stored in silos isolated from each other, such as published articles or monographs. The need for a system to store and manage collective biodiversity knowledge in a community-agreed and interoperable open format has evolved into the concept of the Open Biodiversity Knowledge Management System (OBKMS). This paper presents OpenBiodiv: An OBKMS that utilizes semantic publishing workflows, text and data mining, common standards, ontology modelling and graph database technologies to establish a robust infrastructure for managing biodiversity knowledge. It is presented as a Linked Open Dataset generated from scientific literature. OpenBiodiv encompasses data extracted from more than 5000 scholarly articles published by Pensoft and many more taxonomic treatments extracted by Plazi from journals of other publishers. The data from both sources are converted to Resource Description Framework (RDF) and integrated in a graph database using the OpenBiodiv-O ontology and an RDF version of the Global Biodiversity Information Facility (GBIF) taxonomic backbone. Through the application of semantic technologies, the project showcases the value of open publishing of Findable, Accessible, Interoperable, Reusable (FAIR) data towards the establishment of open science practices in the biodiversity domain.

Research Articles in Simplified HTML: a Web-first format for HTML-based scholarly articles

PurposeThis paper introduces the Research Articles in Simplified HTML (or RASH), which is a Web-first format for writing HTML-based scholarly papers; it is accompanied by the RASH Framework, a set of tools for interacting with RASH-based articles. The paper also presents an evaluation that involved authors and reviewers of RASH articles submitted to the SAVE-SD 2015 and SAVE-SD 2016 workshops.DesignRASH has been developed aiming to: be easy to learn and use; share scholarly documents (and embedded semantic annotations) through the Web; support its adoption within the existing publishing workflow.FindingsThe evaluation study confirmed that RASH is ready to be adopted in workshops, conferences, and journals and can be quickly learnt by researchers who are familiar with HTML.Research LimitationsThe evaluation study also highlighted some issues in the adoption of RASH, and in general of HTML formats, especially by less technically savvy users. Moreover, additional tools are needed, e.g., for enabling additional conversions from/to existing formats such as OpenXML.Practical ImplicationsRASH (and its Framework) is another step towards enabling the definition of formal representations of the meaning of the content of an article, facilitating its automatic discovery, enabling its linking to semantically related articles, providing access to data within the article in actionable form, and allowing integration of data between papers.Social ImplicationsRASH addresses the intrinsic needs related to the various users of a scholarly article: researchers (focussing on its content), readers (experiencing new ways for browsing it), citizen scientists (reusing available data formally defined within it through semantic annotations), publishers (using the advantages of new technologies as envisioned by the Semantic Publishing movement).ValueRASH helps authors to focus on the organisation of their texts, supports them in the task of semantically enriching the content of articles, and leaves all the issues about validation, visualisation, conversion, and semantic data extraction to the various tools developed within its Framework.

Dpaper: An Authoring Tool for Extractable Digital Papers

PurposeTo develop a structured, rich media digital paper authoring tool with an object-based model that enables interactive, playable, and convertible functions.Design/methodology/approachWe propose Dpaper to organize the content (text, data, rich media, etc.) of dissertation papers as XML and HTML5 files by means of digital objects and digital templates.FindingsDpaper provides a structured-paper editorial platform for the authors of PhDs to organize research materials and to generate various digital paper objects that are playable and reusable. The PhD papers are represented as Web pages and structured XML files, which are marked with semantic tags.Research limitationsThe proposed tool only provides access to a limited number of digital objects. For instance, the tool cannot create equations and graphs, and typesetting is not yet flexible compared to MS Word.Practical implicationsThe Dpaper tool is designed to break through the patterns of unstructured content organization of traditional papers, and makes the paper accessible for not only reading but for exploitation as data, where the document can be extractable and reusable. As a result, Dpaper can make the digital publishing of dissertation texts more flexible and efficient, and their data more assessable.Originality/valueThe Dpaper tool solves the challenge of making a paper structured and object-based in the stage of authoring, and has practical values for semantic publishing.

Research Articles in Simplified HTML: a Web-first format for HTML-based scholarly articles

Purpose: this paper introduces the Research Articles in Simplified HTML (or RASH ), which is a Web-first format for writing HTML-based scholarly papers; it is accompanied by the RASH Framework , a set of tools for interacting with RASH-based articles. The paper also presents an evaluation that involved authors and reviewers of RASH articles submitted to the SAVE-SD 2015 and SAVE-SD 2016 workshops. Design: RASH has been developed aiming to: be easy to learn and use; share scholarly documents (and embedded semantic annotations) through the Web; support its adoption within the existing publishing workflow Findings : the evaluation study confirmed that RASH is ready to be be adopted in workshops, conferences, and journals and can be quickly learnt by researchers who are familiar with HTML. Research limitations: the evaluation study also highlighted some issues in the adoption of RASH, and in general of HTML formats, especially by less technically savvy users. Moreover, additional tools are needed, e.g. for enabling additional conversions from/to existing formats such as OpenXML. Practical implications: RASH (and its Framework) is another step towards enabling the definition of formal representations of the meaning of the content of an article, facilitating its automatic discovery, enabling its linking to semantically related articles, providing access to data within the article in actionable form, and allowing integration of data between papers. Social implications: RASH addresses the intrinsic needs related to the various users of a scholarly article: researchers (focussing on its content), readers (experiencing new ways for browsing it), citizen scientists (reusing available data formally defined within it through semantic annotations), publishers (using the advantages of new technologies as envisioned by the Semantic Publishing movement). Value: RASH helps authors to focus on the organisation of their texts, supports them in the task of semantically enriching the content of articles, and leaves all the issues about validation, visualisation, conversion, and semantic data extraction to the various tools developed within its Framework.