Category Archives: oa.semantic

[2303.14334] The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces

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Abstract:  Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need for new technology to support the reading process grows. In contrast to the process of finding papers, which has been transformed by Internet technology, the experience of reading research papers has changed little in decades. The PDF format for sharing research papers is widely used due to its portability, but it has significant downsides including: static content, poor accessibility for low-vision readers, and difficulty reading on mobile devices. This paper explores the question “Can recent advances in AI and HCI power intelligent, interactive, and accessible reading interfaces — even for legacy PDFs?” We describe the Semantic Reader Project, a collaborative effort across multiple institutions to explore automatic creation of dynamic reading interfaces for research papers. Through this project, we’ve developed ten research prototype interfaces and conducted usability studies with more than 300 participants and real-world users showing improved reading experiences for scholars. We’ve also released a production reading interface for research papers that will incorporate the best features as they mature. We structure this paper around challenges scholars and the public face when reading research papers — Discovery, Efficiency, Comprehension, Synthesis, and Accessibility — and present an overview of our progress and remaining open challenges.

 

Semantic wikis as flexible database interfaces for biomedical applications | Scientific Reports

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Abstract:  Several challenges prevent extracting knowledge from biomedical resources, including data heterogeneity and the difficulty to obtain and collaborate on data and annotations by medical doctors. Therefore, flexibility in their representation and interconnection is required; it is also essential to be able to interact easily with such data. In recent years, semantic tools have been developed: semantic wikis are collections of wiki pages that can be annotated with properties and so combine flexibility and expressiveness, two desirable aspects when modeling databases, especially in the dynamic biomedical domain. However, semantics and collaborative analysis of biomedical data is still an unsolved challenge. The aim of this work is to create a tool for easing the design and the setup of semantic databases and to give the possibility to enrich them with biostatistical applications. As a side effect, this will also make them reproducible, fostering their application by other research groups. A command-line software has been developed for creating all structures required by Semantic MediaWiki. Besides, a way to expose statistical analyses as R Shiny applications in the interface is provided, along with a facility to export Prolog predicates for reasoning with external tools. The developed software allowed to create a set of biomedical databases for the Neuroscience Department of the University of Padova in a more automated way. They can be extended with additional qualitative and statistical analyses of data, including for instance regressions, geographical distribution of diseases, and clustering. The software is released as open source-code and published under the GPL-3 license at https://github.com/mfalda/tsv2swm.

 

Semantic Annotation of Experimental Methods in Analytical Chemistry | Analytical Chemistry

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Abstract:  A major obstacle for reusing and integrating existing data is finding the data that is most relevant in a given context. The primary metadata resource is the scientific literature describing the experiments that produced the data. To stimulate the development of natural language processing methods for extracting this information from articles, we have manually annotated 100 recent open access publications in Analytical Chemistry as semantic graphs. We focused on articles mentioning mass spectrometry in their experimental sections, as we are particularly interested in the topic, which is also within the domain of several ontologies and controlled vocabularies. The resulting gold standard dataset is publicly available and directly applicable to validating automated methods for retrieving this metadata from the literature. In the process, we also made a number of observations on the structure and description of experiments and open access publication in this journal.

 

Library as Laboratory: Analyzing Biodiversity Literature at Scale

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“Imagine the great library of life, the library that Charles Darwin said was necessary for the “cultivation of natural science” (1847). And imagine that this library is not just hundreds of thousands of books printed from 1500 to the present, but also the data contained in those books that represents all that we know about life on our planet. That library is the Biodiversity Heritage Library (BHL) The Internet Archive has provided an invaluable platform for the BHL to liberate taxonomic names, species descriptions, habitat description and much more. Connecting and harnessing the disparate data from over five-centuries is now BHL’s grand challenge. The unstructured textual data generated at the point of digitization holds immense untapped potential. Tim Berners-Lee provided the world with a semantic roadmap to address this global deluge of dark data and Wikidata is now executing on his vision. As we speak, BHL’s data is undergoing rapid transformation from legacy formats into linked open data, fulfilling the promise to evaporate data silos and foster bioliteracy for all humankind….”

Automated search in the archives: testing a new tool | Europeana Pro

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“Archives Portal Europe, the online repository for archives from and about Europe, aggregates archival material from more than 30 countries and 25 languages – all searchable through one simple search engine.

In order to help researchers navigating this Babylon of languages, Archives Portal Europe have created an automated topic detection tool that expands the keyword search of a single user to create semantic connections with other documents in different languages. This testing session will allow users to preview the tool (currently in its alpha version), test it, and provide fundamental feedback for its development, and will have prizes! …”

OpenCitations: an independent infrastructure organization for open citation data | Zenodo

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“OpenCitations is an independent not-for-profit infrastructure organization for open scholarship dedicated to the publication of open bibliographic and citation data by the use of Semantic Web (Linked Data) technologies. It is also engaged in advocacy for open citations, particularly in its role as a key founding member of the Initiative for Open Citations (I4OC).

In this webinar, Silvio Peroni (Department of Classic Philology and Italian Studies, University of Bologna), who together with David Shotton (Oxford e-Research Centre, University of Oxford) are the Directors of OpenCitations, will explain the data sets, tools, services, and activities of this infrastructure dedicated to the publication of open citation data as Linked Open Data using Semantic Web technologies.

The session is organised by the Evaluation and Metrics special interest group from the European Association for Health Information and Libraries (EAHIL).

Although the webinar is open also to non EAHIL members, we suggest having a look at the association website, and consider joining to be a part of a network for European health information professionals and librarians!”

Open Citations Registration, Wed 2 Feb 2022 at 11:30 | Eventbrite

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“OpenCitations is an independent not-for-profit infrastructure organization for open scholarship dedicated to the publication of open bibliographic and citation data by the use of Semantic Web (Linked Data) technologies. It is also engaged in advocacy for open citations, particularly in its role as a key founding member of the Initiative for Open Citations (I4OC).

In this webinar, Silvio Peroni (Department of Classic Philology and Italian Studies, University of Bologna), who together with David Shotton (Oxford e-Research Centre, University of Oxford) are the Directors of OpenCitations, will explain the data sets, tools, services, and activities of this infrastructure dedicated to the publication of open citation data as Linked Open Data using Semantic Web technologies….”

Linked open data portals: functionalities and user experience in semantic catalogues | Emerald Insight

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Abstract:  Purpose

This study seeks to understand the current state of the development of linked open data (LOD) bibliographic portals to discuss their functionalities, contributions, value-adds and user experience.

Design/methodology/approach

A set of evaluative aspects grouped into three analysis dimensions was established: collections, tools—technologies and standards used—and web user interface. As the object of the study, four projects of diverse nature and volume were selected to help provide a better understanding of the trends in the solutions provided for the end user when accessing linked data collections.

Findings

Publishing LOD through visual interfaces maximises information enrichment, contextualisation and discovery, in addition to improving user experience, because of both increased navigation capabilities and interrelationships between data. These more flexible environments have metamorphosised the visualisation of bibliographic information. However, aspects that needed improvement were observed, primarily relating to (1) a more intuitive interaction, (2) possibilities of greater personalisation, (3) enhanced communication with the user to favour user engagement and (4) experimental spaces of data reuse.

Research limitations/implications

Further quantitative and qualitative studies should be conducted to improve these portals, assess their adaptation to the behaviour of the user and their influence on the use of library collections.

Originality/value

This article investigates the potential of semantic technologies in bibliographic data portals, proposes a methodological model for their evaluation and advances conclusions about the usability and user experience that these platforms provide, compared to classic catalogues.

Beyond VIAF: Wikidata as a Complementary Tool for Authority Control in Libraries

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Abstract:  This paper aims to investigate the reciprocal relationship between VIAF® and Wikidata and their possible roles in the semantic web environment. It deals with their data, their approach, their domain, and their stakeholders, with particular attention to identification as a fundamental goal of Universal Bibliographic Control. After examining interrelationships among VIAF, Wikidata, libraries and other GLAM institutions, a double approach is used to compare VIAF and Wikidata: first, a quantitative analysis of VIAF and Wikidata data on personal entities, presented in eight tables; and second, a qualitative comparison of several general characteristics, such as purpose, scope, organizational and theoretical approach, data harvesting and management (shown in table 9). Quantitative data and qualitative comparison show that VIAF and Wikidata are quite different in their purpose, scope, organizational and theoretical approach, data harvesting, and management. The study highlights the reciprocal role of VIAF and Wikidata and its helpfulness in the worldwide bibliographical context and in the semantic web environment and outlines new perspectives for research and cooperation.

 

CfP: Community-based Knowledge Bases and Knowledge Graphs (submissions due Nov 01, 2021) | Journal of Web Semantics

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The Journal of Web Semantics invites submissions for a special issue on Community-based Knowledge Bases and Knowledge Graphs, edited by Tim Finin, Sebastian Hellmann, David Martin, and Elena Simperl.

Submissions are due by November 01, 2021.

Community-based knowledge bases (KBs) and knowledge graphs (KGs) are critical to many domains. They contain large amounts of information, used in applications as diverse as search, question-answering systems, and conversational agents. They are the backbone of linked open data, helping connect entities from different datasets. Finally, they create rich knowledge engineering ecosystems, making significant, empirical contributions to our understanding of KB/KG science, engineering, and practices.  From here forward, we use “KB” to include both knowledge bases and knowledge graphs. Also, “KB” and “knowledge” encompass both ontology/schema and data.

Community-based KBs come in many shapes and sizes, but they tend to share a number of commonalities:

They are created through the efforts of a group of contributors, following a set of agreed goals, policies, practices, and quality norms.
They are available under open licenses.
They are central to knowledge-sharing networks bringing together various stakeholders.
They serve the needs of a community of users, including, but not restricted to, their contributor base.
Many draw their content from crowdsourced resources (such as Wikipedia, OpenStreetMap).

Examples of community-based KBs include Wikidata, DBpedia, ConceptNet, GeoNames, FrameNet, and Yago. This special issue will highlight recent research, challenges, and opportunities in the field of community-based KBs and the interaction and processes between stakeholders and the KBs.

 

We welcome papers on a wide variety of topics. Papers that focus on the participation of a community of contributors are especially encouraged.

LOPDF: a framework for extracting and producing open data of scientific documents for smart digital libraries [PeerJ]

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Abstract:  Background

Results of scientific experiments and research work, either conducted by individuals or organizations, are published and shared with scientific community in different types of scientific publications such as books, chapters, journals, articles, reference works and reference works entries. One aspect of these documents is their contents and the other is metadata. Metadata of scientific documents could be used to increase mutual cooperation, find people with common interest and research work, and to find scientific documents in the matching domains. The major issue in getting these benefits from metadata of scientific publications is availability of these data in unstructured (or semi-structured) format so that it can not be used to ask smart queries that can help in computing and performing different types of analysis on scientific publications data. Also, acquisition and smart processing of publications data is a complicated as well as time and resource consuming task.

Methods

To address this problem we have developed a generic framework named as Linked Open Publications Data Framework (LOPDF). The LOPDF framework can be used to crawl, process, extract and produce machine understandable data (i.e., LOD) about scientific publications from different publisher specific sources such as portals, XML export and websites. In this paper we present the architecture, process and algorithm that we developed to process textual publications data and to produce semantically enriched data as RDF datasets (i.e., open data).

Results

The resulting datasets can be used to make smart queries by making use of SPARQL protocol. We also present the quantitative as well as qualitative analysis of our resulting datasets which ultimately can be used to compute the research behavior of organizations in rapidly growing knowledge society. Finally, we present the potential usage of producing and processing such open data of scientific publications and how results of performing smart queries on resulting open datasets can be used to compute the impact and perform different types of analysis on scientific publications data.

Towards FAIR protocols and workflows: the OpenPREDICT use case [PeerJ]

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Abstract:  It is essential for the advancement of science that researchers share, reuse and reproduce each other’s workflows and protocols. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of research data, and emphasize the importance of making digital objects findable and reusable by others. The question of how to apply these principles not just to data but also to the workflows and protocols that consume and produce them is still under debate and poses a number of challenges. In this paper we describe a two-fold approach of simultaneously applying the FAIR principles to scientific workflows as well as the involved data. We apply and evaluate our approach on the case of the PREDICT workflow, a highly cited drug repurposing workflow. This includes FAIRification of the involved datasets, as well as applying semantic technologies to represent and store data about the detailed versions of the general protocol, of the concrete workflow instructions, and of their execution traces. We propose a semantic model to address these specific requirements and was evaluated by answering competency questions. This semantic model consists of classes and relations from a number of existing ontologies, including Workflow4ever, PROV, EDAM, and BPMN. This allowed us then to formulate and answer new kinds of competency questions. Our evaluation shows the high degree to which our FAIRified OpenPREDICT workflow now adheres to the FAIR principles and the practicality and usefulness of being able to answer our new competency questions.

 

Google AI Blog: An NLU-Powered Tool to Explore COVID-19 Scientific Literature

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“Due to the COVID-19 pandemic, scientists and researchers around the world are publishing an immense amount of new research in order to understand and combat the disease. While the volume of research is very encouraging, it can be difficult for scientists and researchers to keep up with the rapid pace of new publications. Traditional search engines can be excellent resources for finding real-time information on general COVID-19 questions like “How many COVID-19 cases are there in the United States?”, but can struggle with understanding the meaning behind research-driven queries. Furthermore, searching through the existing corpus of COVID-19 scientific literature with traditional keyword-based approaches can make it difficult to pinpoint relevant evidence for complex queries.

To help address this problem, we are launching the COVID-19 Research Explorer, a semantic search interface on top of the COVID-19 Open Research Dataset (CORD-19), which includes more than 50,000 journal articles and preprints. We have designed the tool with the goal of helping scientists and researchers efficiently pore through articles for answers or evidence to COVID-19-related questions….”