Classifying Research Papers with the Computer Science Ontology

The CSO Classifier is an application for automatically classifying academic papers according to the rich taxonomy of topics from CSO. The aim is to facilitate the adoption of CSO across the various communities engaged with scholarly data and to foster the development of new applications based on this knowledge base.

The Computer Science Ontology: A Large-Scale 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 26K topics and 226K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles.

Springer Nature Hack Day – Berlin

On 26-27 April 2018, Francesco Osborne and I attended the third edition of the Springer Nature Hack Day, which was held in its headquarter in Berlin.

The Springer Nature Hack Day is an event that allows researchers, developers, tech companies, and Springer Nature itself, to gather together and tackle current research issues. Offering also opportunities for potential collaborations and networking.

This was my second time attending a hack day organised by Springer Nature. Indeed, with my colleagues Andrea Mannocci and Thiviyan Thanapalasingam, we attended the previous edition, back in November 2017, working on a Venue-centric trends project (read full story here). An extended version of this project has then been presented at the SAVE-SD workshop co-located with The Web Conference 2018 [1].

 

In this edition, the participants pitched six different ideas and projects, centred around “analytics and metrics to measure the impact of science”, such as: Disease Dashboard, Hot Topics (our project), Keyword Recommendation, Data mining for historians, Search-Assist, and Semantic Entity Marker. More information about the whole event can be found in this Springer Nature blog post.

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Supporting Editorial Activities at Springer Nature

The project aims at fostering Springer Nature editorial activities by supporting them with a variety of smart solutions leveraging artificial intelligence, data mining, and semantic technologies. In particular, the KMi team will support Springer Nature editorial team in classifying proceedings and other editorial products, taking informed decisions about their marketing strategy, and improve their internal classification.

AUGUR: Forecasting the Emergence of New Research Topics

“AUGUR: Forecasting the Emergence of New Research Topics” is a paper submitted to the ACM/IEEE Joint Conference on Digital Libraries 2018, presented on June 5 2018, in Fort Worth, TX, USA   Angelo Salatino, Francesco Osborne and Enrico Motta   Abstract Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, … Read more

Computer Science Ontology Portal (or simply CSO Portal)

The Computer Science Ontology Portal (also referred to simply as CSO Portal) is a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. This last feature allows us to periodically review the status ontology and release new version according to the received feedbacks.

Springer Nature video

Couple of months ago, with my team, we attended the Springer Nature HackDay (here is the post). Just not long ago, Springer Nature released a short video featuring us. Summarised is also my interview, in which I discuss the advantages of making scholarly datasets, as SciGraph, available to anyone.

Other media

SpringerNature Hackday – London

On the 29th November 2017, myself with two KMi colleagues (Andrea Mannocci and Thiviyan Thanapalasingam) attended the second edition of SpringerNature HackDay in London (@ SpringerNature Campus).

Aliaksandr Birukou, Executive Editor of Computer Science at Springer Nature and collaborator of our research team at the Knowledge Media Institute, also joined our group on the HackDay.

The whole event aimed at joining together the skills and interests of many developers and researchers with SciGraph, for advancing discovery.

The main web page for the event is here: https://github.com/SN-HackDay/Advancing-discovery-with-research-data (or here in case someone removes it).

As a team, we worked on Venue-centric trends problem. In particular, our projects provides to editors, conference organizers and many others, a dashboard to understand how knowledge flows across countries and continents, who are the main producers and consumers of the research output for a given conference, whether the conference is open to interdisciplinarity, and many other questions.

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