Advanced Methods to Extract Value from Scientific Datasets

  • Lucian Perju
  • Marius-Dorian Nicolaescu
  • Florin PopEmail author
  • Ciprian Dobre
  • Sanda Maiduc
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1080)


In these days the scientific community is times bigger comparing with the previous centuries. The need of powerful tools to aggregate and analyse the information about articles, books and other publications becomes greater with each published paper. In this paper we describe a solution for understanding and leveraging this data. The platform integrates the following requirements: data aggregation, data analysis (visualizations, dashboards, graphs), complex and simple searches, and support for data export. The platform brings value to its users due to various reasons such as quick identification of relevant data and in depth analysis on the provided input. Another key feature is the granularity, application being easily configurable for rigorous use cases: just one author, a group of authors or an entire scientific field.


Data analysis Data aggregation Data retrival Big Data Elastic Search Containerization 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Lucian Perju
    • 1
  • Marius-Dorian Nicolaescu
    • 1
    • 2
  • Florin Pop
    • 1
    • 3
    Email author
  • Ciprian Dobre
    • 1
    • 3
  • Sanda Maiduc
    • 1
  1. 1.University Politehnica of BucharestBucharestRomania
  2. 2.Executive Unit for Financing Higher Education, Research, Development and Innovation (UEFISCDI)BucharestRomania
  3. 3.National Institute for Research and Development in Informatics (ICI) BucharestBucharestRomania

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