scholarly journals Ontology Extraction and Usage in the Scholarly Knowledge Domain1

2020 ◽  
Author(s):  
Angelo A. Salatino ◽  
Francesco Osborne ◽  
Enrico Motta
Keyword(s):  
Computer Science ◽  
Metadata Extraction ◽  
Making Sense ◽  
Research Areas ◽  
Ontology Extraction ◽  
Scholarly Data ◽  
High Level

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.

Measuring the interdisciplinarity of Big Data research: a longitudinal study

2018 ◽  
Vol 42 (5) ◽  
pp. 681-696 ◽  
Author(s):  
Jiming Hu ◽  
Yin Zhang
Keyword(s):  
Big Data ◽  
Longitudinal Study ◽  
Computer Science ◽  
Diversity Index ◽  
Interdisciplinary Collaboration ◽  
Research Area ◽  
Content Type ◽  
The Core ◽  
Research Areas ◽  
High Level

Purpose The purpose of this paper is to measure the degree of interdisciplinary collaboration in Big Data research based on the co-occurrences of subject categories using Stirling’s diversity index and specialization index. Design/methodology/approach Interdisciplinarity was measured utilizing the descriptive statistics of disciplines, network indicators showing relationships between disciplines and within individual disciplines, interdisciplinary communities, Stirling’s diversity index and specialization index, and a strategic diagram revealing the development status and trends of discipline communities. Findings Comprehensively considering all results, the degree of interdisciplinarity of Big Data research is increasing over time, particularly, after 2013. There is a high level of interdisciplinarity in Big Data research involving a large number of disciplines, but it is unbalanced in distribution. The interdisciplinary collaborations are not intensive on the whole; most disciplines are aggregated into a few distinct communities with computer science, business and economics, mathematics, and biotechnology and applied microbiology as the core. Four major discipline communities in Big Data research represent different directions with different development statuses and trends. Community 1, with computer science as the core, is the most mature and central to the whole interdisciplinary network. Accounting for all network indicators, computer science, engineering, business and economics, social sciences, and mathematics are the most important disciplines in Big Data research. Originality/value This study deepens our understanding of the degree and trend of interdisciplinary collaboration in Big Data research through a longitudinal study and quantitative measures based on two indexes. It has practical implications to study and reveal the interdisciplinary phenomenon and characteristics of related developments of a specific research area, or to conduct comparative studies between different research areas.

scholarly journals The Computer Science Ontology: A Comprehensive Automatically-Generated Taxonomy of Research Areas

2020 ◽  
Vol 2 (3) ◽  
pp. 379-416 ◽  
Author(s):  
Angelo A. Salatino ◽  
Thiviyan Thanapalasingam ◽  
Andrea Mannocci ◽  
Aliaksandr Birukou ◽  
Francesco Osborne ◽  
...  
Keyword(s):  
Computer Science ◽  
Web Application ◽  
Large Scale ◽  
Large Data ◽  
Coarse Grained ◽  
Editorial Team ◽  
Data Set ◽  
Research Areas ◽  
Research Communities ◽  
Scholarly Data

Ontologies of research areas are important tools for characterizing, exploring, and analyzing 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 data set 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 visualize 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.

ATTITUDE TO OPEN ACCESS IN RUSSIAN SCHOLARLY COMMUNITY: 2018. SURVEY RESULTS AND ANALYSIS

2018 ◽  
Vol 1 (1) ◽  
pp. 6-21 ◽  
Author(s):  
I. K. Razumova ◽  
N. N. Litvinova ◽  
M. E. Shvartsman ◽  
A. Yu. Kuznetsov
Keyword(s):  
Open Access ◽  
Open Access Publishing ◽  
Scholarly Community ◽  
Research Areas ◽  
Survey Results ◽  
The Difference ◽  
Policies And Programs ◽  
The Uk ◽  
High Level ◽  
Access Policies

Introduction. The paper presents survey results on the awareness towards and practice of Open Access scholarly publishing among Russian academics.Materials and Methods. We employed methods of statistical analysis of survey results. Materials comprise results of data processing of Russian survey conducted in 2018 and published results of the latest international surveys. The survey comprised 1383 respondents from 182 organizations. We performed comparative studies of the responses from academics and research institutions as well as different research areas. The study compares results obtained in Russia with the recently published results of surveys conducted in the United Kingdom and Europe.Results. Our findings show that 95% of Russian respondents support open access, 94% agree to post their publications in open repositories and 75% have experience in open access publishing. We did not find any difference in the awareness and attitude towards open access among seven reference groups. Our analysis revealed the difference in the structure of open access publications of the authors from universities and research institutes. Discussion andConclusions. Results reveal a high level of awareness and support to open access and succeful practice in the open access publications in the Russian scholarly community. The results for Russia demonstrate close similarity with the results of the UK academics. The governmental open access policies and programs would foster the practical realization of the open access in Russia.

Property

2020 ◽  
pp. 276-292
Author(s):  
J. E. Penner
Keyword(s):  
Property Rights ◽  
Case Law ◽  
Property Law ◽  
Private Law ◽  
Making Sense ◽  
The Social ◽  
Bundle Of Rights ◽  
High Level

This chapter discusses property law. It considers the idea that property had a “nominalist” ontology, and it was in danger of “disintegration” as a working legal category for that very reason. Nominalism about property has had a significant impact in U.S. case law. The concern here, however, is whether it is a helpful stance to take as a theorist of property. The chapter argues that it is not. There are indeed “high” level abstractions about property which one cannot plausibly do without if one is to understand property rights and property law doctrine. Moreover, the “bundle of rights” (BOR) challenge does not assist one in making sense of these abstractions. The chapter then looks at the conceptual failure of BOR and the New Private Law as it relates to property. BOR is generally regarded as being underpinned by what might be called the Hohfeld-Honoré synthesis. The synthesis rests upon a fairly serious mistake, which is that while the Hohfeldian examination of jural norms is analytic if it is anything, Honor’s elaboration of the incidents making up ownership is anything but—it is functional. This means that Honoré describes the situation of the owner not principally in terms of his Hohfeldian powers, duties, and rights vis-à-vis others, but in terms of the social or economic advantages that an owner has by virtue of his position, and the terms and limitations of those advantages.

scholarly journals CSO Classifier 3.0: a scalable unsupervised method for classifying documents in terms of research topics

2021 ◽  
Author(s):  
Angelo Salatino ◽  
Francesco Osborne ◽  
Enrico Motta
Keyword(s):  
Computer Science ◽  
Digital Libraries ◽  
Gold Standard ◽  
Research Trends ◽  
Alternative Methods ◽  
Relevant Research ◽  
Research Topics ◽  
Research Papers ◽  
Research Areas ◽  
Unsupervised Approach

AbstractClassifying scientific articles, patents, and other documents according to the relevant research topics is an important task, which enables a variety of functionalities, such as categorising documents in digital libraries, monitoring and predicting research trends, and recommending papers relevant to one or more topics. In this paper, we present the latest version of the CSO Classifier (v3.0), an unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive taxonomy of research areas in the field of Computer Science. The CSO Classifier takes as input the textual components of a research paper (usually title, abstract, and keywords) and returns a set of research topics drawn from the ontology. This new version includes a new component for discarding outlier topics and offers improved scalability. We evaluated the CSO Classifier on a gold standard of manually annotated articles, demonstrating a significant improvement over alternative methods. We also present an overview of applications adopting the CSO Classifier and describe how it can be adapted to other fields.

scholarly journals Bibliometric analysis of the development of nanoscience research in South Africa

2017 ◽  
Vol 113 (11/12) ◽  
Author(s):  
Xolani Makhoba ◽  
Anastassios Pouris
Keyword(s):  
South African ◽  
Web Of Science ◽  
Research Area ◽  
Public Institutions ◽  
Gauteng Province ◽  
Research Areas ◽  
The Usa ◽  
Institutional Profile ◽  
High Level ◽  
The University

Nanotechnology is a fast-growing scientific research area internationally and is classified as an important emerging research area. In response to this importance, South African researchers and institutions have also increased their efforts in this area. A bibliometric study of articles as indexed in the Web of Science considered the development in this field with respect to the growth in literature, collaboration profile and the research areas that are more within the country’s context. We also looked at public institutions that are more active in this arena, including government policy considerations as guided by the National Nanotechnology Strategy launched in 2005. We found that the number of nanotechnology publications have shown a remarkable growth ever since the launch of the strategy. Articles on nanotechnology have been published in numerous journals, with Electrochimica Acta publishing the most, followed by Journal of Nanoscience and Nanotechnology. These publications fall within the traditional domains of chemistry and physics. In terms of the institutional profile and based on publication outputs over the period reviewed, the Council for Scientific and Industrial Research is a leading producer of publications in nanotechnology, followed by the University of the Witwatersrand – institutions that are both based in the Gauteng Province. There is a high level of international collaboration with different countries within this field – the most productive collaboration is with India, followed by the USA and China, as measured through co-authorship.

scholarly journals Human Gaze Assisted Artificial Intelligence: A Review

2020 ◽  
Author(s):  
Ruohan Zhang ◽  
Akanksha Saran ◽  
Bo Liu ◽  
Yifeng Zhu ◽  
Sihang Guo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cognitive State ◽  
Data Sets ◽  
Common Goal ◽  
Research Areas ◽  
Future Challenges ◽  
Potential Applications ◽  
High Level ◽  
And Robotics

Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.

scholarly journals A Framework Uniting Ontology-Based Geodata Integration and Geovisual Analytics

2020 ◽  
Vol 9 (8) ◽  
pp. 474
Author(s):  
Linfang Ding ◽  
Guohui Xiao ◽  
Diego Calvanese ◽  
Liqiu Meng
Keyword(s):  
Data Integration ◽  
Visual Analysis ◽  
Open Data ◽  
Data Access ◽  
Heterogeneous Data ◽  
Geospatial Data ◽  
Making Sense ◽  
Research Areas ◽  
Geovisual Analytics ◽  
Integration Techniques

In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophisticated analysis methods. To address this challenge we rely on two well-established research areas: data integration and geovisual analytics, and propose to adopt an ontology-based approach to decouple the challenges of data access and analytics. Our framework consists of two modules centered around an ontology: (1) an ontology-based data integration (OBDI) module, in which mappings specify the relationship between the underlying data and a domain ontology; (2) a geovisual analytics (GeoVA) module, designed for the exploration of the integrated data, by explicitly making use of standard ontologies. In this framework, ontologies play a central role by providing a coherent view over the heterogeneous data, and by acting as a mediator for visual analysis tasks. We test our framework in a scenario for the investigation of the spatiotemporal patterns of meteorological and traffic data from several open data sources. Initial studies show that our approach is feasible for the exploration and understanding of heterogeneous geospatial data.

scholarly journals Uncertain Certainty?: Making Sense of the European Court of Human Rights’ Standard of Proof

2019 ◽  
Vol 8 (2) ◽  
pp. 155-187
Author(s):  
Christine Bicknell
Keyword(s):  
Human Rights ◽  
Case Law ◽  
Detailed Examination ◽  
Reasonable Doubt ◽  
Standard Of Proof ◽  
Making Sense ◽  
European Court ◽  
Single Standard ◽  
High Level

The European Court of Human Rights (ECtHR) declares a single standard of proof (‘SoP’): proof beyond reasonable doubt (‘brd’). Yet the accuracy of this claim and the threshold’s appropriateness have both been challenged. This article uniquely considers and clarifies the Court’s interpretation and application of its SoP. Demonstrating SoP is capable of both broad and narrow interpretations, it shows the Court interprets SoP only narrowly. This understanding confirms brd as the applicable standard, whose use is then considered through detailed examination of the case law. The analysis shows that although the Court’s conception and approach to brd necessarily accommodate some doubt, violations are found with a consistently high level of certainty. There is however, a striking inconsistency in references made to the Rules of Court. Moreover, the Rules do not fully capture the Court’s approach. Addressing this, as the article proposes, would strengthen both the consistency and legitimacy of relevant decisions.

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