AIDA Dashboard

By Angelo Salatino | • 5 minute read

The AIDA Dashboard is a web application that allows users to visualize several kind of analytics about a specific conference (see Figure 1). The backend is developed in Python, while the frontend is in HTML5 and Javascript.

The AIDA Dashboard builds on the Academia/Industry DynAmics knowledge graph (AIDA), a large knowledge base describing 14M articles and 8M patents in the field of Computer Science according to the research topics drawn from CSO. 4M articles and 5M patents are also classified according to the type of the author’s affiliations (academy, industry, or collaborative) and 66 industrial sectors drawn from INDUSO, which was specifically designed to support AIDA.

AIDA was generated by integrating several knowledge graphs and bibliographic corpora, including Microsoft Academic Graph (MAG), Dimensions, DBpedia, CSO, and the Global Research Identifier Database (GRID).

AIDA Dashboard is highly scalable and allows to browse the different facets of a conference according to seven tabs: Overview, Citation Analysis, Organizations, Authors, Topics, Similar Conferences, and Industry.

Figure 1: The Overview of the International Semantic Web Conference according to the AIDA Dashboard.

 

Figure 1 shows the Overview tab. This is the main view of a conference that provides introductory information about its performance, the main authors and organization, and the conference rank in its main fields in terms of average citations for paper during the last five years.

The Citation Analysis tab reports the evolution in time of several citation-based metrics such as the impact factor and the average citations for paper. It also shows the evolution of the rank and the percentile of the conference in different fields. For instance, the Conference on Neural Information Processing Systems (NeurIPS) is currently the second conference in terms of average citations in Neural Network, the third in Machine Learning, and the twelfth in Artificial Intelligence. This visualization is typically used by Springer Nature editors to assess the performance of conferences within different communities and to identify emerging conferences.

The Organizations and Authors tabs show several analytics about the main institutions and researchers active in the conference. Organizations can be filtered according to their type (academia or industry) and are associated with their number of publications, citations, and average citations for paper. The researchers are associated with similar analytics, but also with their H-index and H5-index, in order to quickly identify high impact researchers. Editors use this information to understand the quality of researchers and organizations attracted by the conferences. This is particularly important for assessing relatively young conferences that may not have developed yet a strong citation record.

The Topic tab allows users to analyse the topic trends in time. Specifically it shows two selections of topics: frequent topics and fingerprint topics. The first is the set of topics which appear more frequently in the conference. The second is the set of most distinctive topics of the conference. It is obtained by computing the difference between the topic distribution of the conference and the one of the full dataset.

When searching, the dashboard prompts also research areas, e.g., The Web. Clicking on such a research area, the dashboard redirects users to the advanced search panel, allowing them to browse and compare venues based on such a field. The user can browse the different venues using the selection menus and switch between journals and conferences with the button in the upper right. Journals and conferences can be ranked according several metrics, including:

  • average citations received in the last five years,
  • average articles published in the last 5 years,
  • h5-index,
  • the average h5-index of the relevant organisations,
  • the average h5-index of the relevant authors.

The last two metrics are not typically offered by alternative systems, but are very useful to identify emergent venues that are attracting strong research groups but may not have yet received a good number of citations.

 

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