Network Data Analytics (NDA) 2017

We had a successful meeting of the 2nd International Workshop on Network Data Analytics (NDA) 2017. Thanks to all the workshop participants!

Co-located with the ACM SIGMOD International Conference on Management of Data 2017 at Chicago, Illinois, USA
Workshop Date: Friday, May 19, 2017

  • We are excited to announce that Jiawei Han (Professor, University of Illinois Urbana-Champaign) and Divesh Srivastava (Director of Databases Research, AT&T Labs Research) will be the keynote speakers!
  • Submissions Open (Deadline 9th January (Abstract) and 16th January (Paper)): The submission portal is active now and we have started accepting papers. Please submit your exciting research work to NDA 2017!
  • Our Program Committee has accepted three full and two short papers. See our workshop program!
  • For Registration, please see the SIGMOD/PODS Conference and Workshop registration page. Online Registration Closes 7th April (Early) and 5th May (Late). Hurry Up!


Networks are prevalent in today’s electronic world in a wide variety of domains ranging from Engineering to Social Sciences, Life Sciences to Physical Sciences, Data Analytics and so on. Researchers and practitioners have studied networks in multiple ways like defining network metrics, providing theoretical results and examining problems like pattern mining, link prediction etc. Recently, we have witnessed proliferation of networks in new business domains like Telecommunications, Banking, Retail/Marketing, Healthcare, Transportation etc. Most of these real-world applications give rise to networks which exhibit unique and interesting structures supporting multiple dynamical processes that shape these networks over time. Owing to the tremendous pace of growth of electronic data, (1) Many of these networks are evolving at a rapid pace leading to evolving networks, and (2) Real-world graph data is seldom perfect; rather it is often of dubious quality, thereby being noisy.

Graphs are unarguably one of the most natural ways of representation for such data because of their ability to represent different entity and relationship types, including the temporal relationships necessary to represent the dynamics of a data stream. However, fusing such heterogeneous data into a single graph or multiple related graphs and mining is challenging task. Emerging massive data has made calls for fundamental change to graph data modelling and programming paradigm. APACHE SPARK is one such successful instantiation. Finally, it is interesting to see the applicability of graph based techniques by applying them to even wider range of data like spatial, spatio-temporal and IOT data which did not inherently exhibit network structure by modelling relationships.

This workshop is a forum for exchanging ideas and methods for mining, querying and learning with real-world networks, developing new common understandings of the problems at hand, sharing of data sets where applicable, and leveraging existing knowledge from different disciplines.

In summary, NDA 2017 is aimed at bringing together researchers from academia, industry and government with the following goals:

  • Create a forum for discussing recent advances in (large-scale) graph analysis.
  • Present theoretical and empirical results on generic graph analytics/querying problems pertaining to one or more topics mentioned in the CFP.
  • Bring out issues pertaining to presence of noise in real-life graphs and techniques to address those.
  • Present (possibly with demonstrations) and discuss novel applications of graph analytics in newer domains.
Towards that we would like to encourage applications and demonstrations of relevant real-life systems and research prototypes. We particularly encourage submissions which showcase the need for graph stores over traditional data models like RDBMS or XML performs sub-optimally. 

The workshop areas will be of interest to both theoreticians and practitioners who are interested in the development of novel data-management applications encircling large-scale analytics. More specifically, the intended audience are, but not limited to, computer scientists interested in databases and data mining, machine learning, data streaming, graph theory and algorithms.

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Important dates

  • Abstract Submission :January 9, 2017 January 30, 2017 (Extended)
  • Paper Submission : January 16, 2017 January 30, 2017 (Extended)
  • Notifications : March 6, 2017
  • Camera Ready Submission : March 31, 2017
  • Workshop Date : May 19, 2017
  • All deadlines are 23:59 Hours PST

Workshop Organizers

Akhil AroraXerox Research Centre India
Shourya Roy, American Express Big Data Labs
Arnab BhattacharyaIIT Kanpur

Sponsored by :