Supporting editorial activities at Springer Nature

The Open University team and Springer Nature have launched a new research project with the aim of developing new innovative solutions to support editorial activities at Springer Nature. The project will be lead by Enrico Motta and Francesco Osborne and will start on May 2018.

The SKM3 team and Springer Nature have been collaborating since 2015 in the development of an array of semantically-enhanced solutions supporting editors in i) classifying proceedings and other editorial products with respect to the relevant research areas and ii) taking informed decisions about their marketing strategy. These solutions include:

  1. The creation of a portal for releasing the Computer Science Ontology (CSO), a large-scale ontology of research areas that was automatically generated using the Klink-2 algorithm on the Rexplore dataset. The portal will enable to browse, download, and offer feedback on CSO. Currently, we provide two versions of CSO: CSO 1.0 (stable, 15k topics and 96k relationships), and CSO 2.0 (last version, 26k topics, 226k relationships). You can browse CSO on the CSO Portal.
  2. The CSO Classifier is a new unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive ontology of research areas in the field of Computer Science. The CSO Classifier takes as input the metadata associated with a research paper (title, abstract, keywords) and returns a selection of research concepts drawn from the ontology. A web application for trying the CSO Classifier is available at https://cso.kmi.open.ac.uk/classify/.
  3. The development of Smart Topic Miner, a tool which uses semantic web technologies to classify scholarly publications on the basis of a very large automatically generated ontology of research areas. It was developed to support the Springer Nature Computer Science editorial team in classifying proceedings. A demo of the system is available at http://stm-demo.kmi.open.ac.uk.
  4. The Smart Book Recommender, which assists editors in deciding which editorial products should be marketed in a specific venue. It takes as input the proceedings of a conference and suggests books, journals, and other conference proceedings which are likely to be relevant to the attendees of the conference in question. A demo for SBR is available at http://rexplore.kmi.open.ac.uk/SBR-demo/.
  5. An automatically generated ontology of research topics in the Engineering field. To this end, we plan to create a new version of Klink, which is an algorithm that combines semantic technologies, machine learning, and knowledge from external sources to automatically generate a fully populated ontology of research areas.

In May 2019, as evidence for this successful collaboration, we renewed it with further objectives, including the creation variety of analytics solutions for analysing conferences, journals, books, organisations, topics and other research entities. In particular, we will focus on a Conference Dashboard, which will support editors in assessing the quality, impact, and trends of conferences. We will also focus on segmenting Springer Nature customers based on their interest (content they read) and support the Marketing department in tailoring their product packages.

We are very excited to renew the collaboration with Springer Nature and we look forward to producing together excellent research solutions and innovative applications.

Relevant papers

Springer Nature collaboration

Computer Science Ontology

CSO Classifier

Smart Topic Miner

Smart Book recommender

Klink algorithm

PhD work funded by Springer Nature