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Open Research Knowledge Graph
As we mark the fifth anniversary of the alpha release of the Open Research
Knowledge Graph (ORKG), it is both timely and exhilarating to celebrate the significant
strides made in this pioneering project. We designed this book as a tribute
to the evolution and achievements of the ORKG and as a practical guide encapsulating
its essence in a form that resonates with both the general reader and the
specialist.
The ORKG has opened a new era in the way scholarly knowledge is curated, managed,
and disseminated. By transforming vast arrays of unstructured narrative text
into structured, machine-processable knowledge, the ORKG has emerged as an
essential service with sophisticated functionalities. Over the past five years, our
team has developed the ORKG into a vibrant platform that enhances the accessibility
and visibility of scientific research. This book serves as a non-technical guide
and a comprehensive reference for new and existing users that outlines the
ORKG’s approach, technologies, and its role in revolutionizing scholarly communication.
By elucidating how the ORKG facilitates the collection, enhancement, and
sharing of knowledge, we invite readers to appreciate the value and potential of
this groundbreaking digital tool presented in a tangible form.
Looking ahead, we are thrilled to announce the upcoming unveiling of promising
new features and tools at the fifth-year celebration of the ORKG’s alpha release.
These innovations are set to redefine the boundaries of machine assistance enabled
by research knowledge graphs. Among these enhancements, you can expect
more intuitive interfaces that simplify the user experience, and enhanced machine learning
models that improve the automation and accuracy of data curation.
We also included a glossary tailored to clarifying key terms and concepts associated
with the ORKG to ensure that all readers, regardless of their technical background,
can fully engage with and understand the content presented. This book
transcends the boundaries of a typical technical report. We crafted this as an inspiration
for future applications, a testament to the ongoing evolution in scholarly
communication that invites further collaboration and innovation. Let this book serve
as both your guide and invitation to explore the ORKG as it continues to grow and
shape the landscape of scientific inquiry and communication
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B!SON: A Tool for Open Access Journal Recommendation
Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project
The Computer Science Ontology: A Comprehensive Automatically-Generated Taxonomy of Research Areas
Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 14K topics and 162K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO, we have also released the CSO Classifier, a tool for automatically classifying research papers, and the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO. Users can use the portal to navigate and visualise sections of the ontology, rate topics and relationships, and suggest missing ones. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various research communities engaged with scholarly data
Contexts and Contributions: Building the Distributed Library
This report updates and expands on A Survey of Digital Library Aggregation Services, originally commissioned by the DLF as an internal report in summer 2003, and released to the public later that year. It highlights major developments affecting the ecosystem of scholarly communications and digital libraries since the last survey and provides an analysis of OAI implementation demographics, based on a comparative review of repository registries and cross-archive search services. Secondly, it reviews the state-of-practice for a cohort of digital library aggregation services, grouping them in the context of the problem space to which they most closely adhere. Based in part on responses collected in fall 2005 from an online survey distributed to the original core services, the report investigates the purpose, function and challenges of next-generation aggregation services. On a case-by-case basis, the advances in each service are of interest in isolation from each other, but the report also attempts to situate these services in a larger context and to understand how they fit into a multi-dimensional and interdependent ecosystem supporting the worldwide community of scholars. Finally, the report summarizes the contributions of these services thus far and identifies obstacles requiring further attention to realize the goal of an open, distributed digital library system
Ontology Extraction and Usage in the Scholarly Knowledge Domain
Ontologies of research areas have been proven to be useful resources for analysing and making sense of scholarly data. In this chapter, we present the Computer Science Ontology (CSO), which is the largest ontology of research areas in the field, and discuss a number of applications that build on CSO to support high-level tasks, such as topic classification, metadata extraction, and recommendation of books
BlogForever D2.6: Data Extraction Methodology
This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform
Selected Information Management Resources for Implementing New Knowledge Environments: An Annotated Bibliography
This annotated bibliography reviews scholarly work in the area of building and analyzing digital document collections with the aim of establishing a baseline of knowledge for work in the field of digital humanities. The bibliography is organized around three main topics: data stores, text corpora, and analytical facilitators. Each of these is then further divided into sub-topics to provide a broad snapshot of modern information management techniques for building and analyzing digital documents collections
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