@conference{611,
  keywords = {dynamic networks, Visual analytics, Adjacency Matrices, Temporal Graphs},
  author = {Nikolaus-Mathias Herl and Velitchko Filipov},
  title = {AdMaTilE: Visualizing Event-Based Adjacency Matrices in a Multiple-Coordinated-Views System},
  abstract = {<p>Conventional dynamic networks represent network changes via a discrete sequence of timeslices, which usually entails loss of information on fine-grained dynamics. Recently, event-based networks emerged as an approach to model this temporal (event-based) information more precisely. Adjacency-matrixbased visualizations of temporal networks are under-investigated in related literature and present a promising research direction for network visualization. Our approach AdMaTilE (Adjacency Matrix and Timeline Explorer) is designed to visualize event-based networks using multiple matrix views, timelines, difference maps, and staged transitions.</p>},
  year = {2024},
  journal = {32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)},
  volume = {320},
  pages = {46:1-46:3},
  month = {2024-09-18 to 2024-09-20},
  address = {Vienna},
  isbn = {978-3-95977-343-0},
  doi = {10.34726/7180},
}