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Data-Driven Approaches for Analyzing and Managing Scholarly Data: Systems, Methods and Applications
Subevent of ADBIS2017
Dates 2017/09/24 (iCal) - 2017/09/24
Location: Nicosia, Cyprus
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Important dates
Submissions: 2017/05/21
Notification: 2017/06/02
Camera ready due: 2017/06/25
Workshop chairs: Andreas Behrend, Christoph Lange
Table of Contents

The main goals of AMSD 2017 are to facilitate the access of scholarly data, to enhance the ability to assess the quality of scholarly data and to foster the development of analysis tools for scholarly data. With this workshop we encourage researchers from different fields (data management, information retrieval, digital libraries, graph databases, machine learning, recommender systems, visualization, etc.) to combine the resources in order to exploit the possibilities of scholarly data. We invite researchers to apply and adapt existing tools and techniques as well as to develop new concepts and applications for managing, analyzing and visualizing scholarly data.

Topics and Themes

Data Management

  • Data models for the description and the linking of scholarly data
  • Curation, annotation, and provenance of scholarly data
  • Description of citations and citation networks
  • Description and use of provenance information of scholarly data
  • Integration of scholarly data
  • Usage of semantic web techniques to open and interlink scholarly data in digital libraries and bibliographic websites
  • Modelling licenses for scholarly documents and data
  • Applications for the (semi-)automatic annotation of scientific papers
  • Uniform systems combining multiple forms of scholarly data
  • Accessing scholarly information from multiple devices (PC, tablet, smartphones)
  • Novel user interfaces for interaction with paper, metadata, content, and data


  • Assessing the quality and/or trust of scholarly data
  • Pattern discovery of scholarly data
  • Citation analysis, prediction, and visualization
  • Scientific claims identification from textual contents
  • New indicators for measuring the quality and relevance of research
  • Comparison between standard metrics (e.g., h-index, impact factor, citation counting) and alternative metrics in real-case scenarios
  • Automatic or semi-automatic approaches to making sense of research dynamics
  • Content- and data-based semantic similarity of scholarly papers
  • Automatic semantic enhancement of existing scholarly libraries and papers
  • Reconstruction, forecasting and monitoring of scholarly data
  • Recommender systems for scientific events
  • Applications for making sense of scholarly data

Important Dates

Submission Deadline: May 21st, 2017

Acceptance Notification: June 2nd, 2017

Camera-Ready Submission: June 25th, 2017

Submission Details

Submissions should present original results and substantial new work not currently under review or published elsewhere. This workshop accepts the following kind of papers covering one or more of the above mentioned topics:

  • full papers (up to 12 pages)
  • position papers (up to 8 pages)
  • demo papers (up to 6 pages)
  • poster papers (up to 2 pages)

All accepted ADBIS 2017 workshop papers will be published by Springer in 'Communications in Computer and Information Science'. The best papers will be invited to be published in a special section of the International Journal of Applied Mathematics and Computer Science (AMCS).



  • Andreas Behrend, University of Bonn, Bonn, Germany
  • Christoph Lange, Fraunhofer Institute IAIS and University of Bonn, Bonn, Germany
Facts about "AM-SD2017"
AcronymAMSD2017 +
Camera ready dueJune 25, 2017 +
End dateSeptember 24, 2017 +
Event typeWorkshop +
Has coordinates35° 10' 26", 33° 21' 53"Latitude: 35.173930555556
Longitude: 33.364725
Has location cityNicosia +
Has location countryCategory:Cyprus +
Has workshop chairAndreas Behrend + and Christoph Lange +
Homepage +
IsAEvent +
NotificationJune 2, 2017 +
Start dateSeptember 24, 2017 +
Subevent ofADBIS2017 +
Submission deadlineMay 21, 2017 +
TitleData-Driven Approaches for Analyzing and Managing Scholarly Data: Systems, Methods and Applications +