EXPAND: EXploratory Visualization of PAtent Network Dynamics


The EXPAND project addresses highly topical challenges of visual analytics methods in the patent data domain. Aiming on a genuinely dynamical framework for visual analysis and knowledge crystallization, radically new concepts and methods have to be developed to unlock the potential of patent network data, which is characterized by its continuous and event based nature, its richness of attributes and its large scale. While these objectives are ranging high on a scientific and technological research agenda, a user-centred design and evaluation approach will ensure the practical utility and usability of the intended methods and concepts, which will be bundled and evaluated in form of a research prototype. The advancement and future implementation of the prototype into the business partners IT service portfolio will guarantee the exploitation of results as well as the strengthening of economic advantage in the strategic business intelligence market.


This project is supported by the program "FIT-IT Visual Computing" of the Federal Ministry of Transport, Innovation and Technology, under grant no. 835937.


The distributed nature of modern research and development has lead to a highly differentiated knowledge and technology landscape, which forms the complex and continuously evolving environment for individual and organizational actors in the economy, science, and technology realm. Public patent databases, which are regulating these developments by ongoing accumulation of semi-structured patent documents, are a rich source of information that has not been sufficiently leveraged for synoptic science and business analytical tasks yet. Innovative developments of methods are needed to support people like researchers, business executives, investors, IP law attorneys or academia and government policy makers to provide them the means to individually explore current patterns of collaboration and to identify appearances of R&D trends, knowledge flows and possible future developments.

Against the background of prior work, which has focused on statistical or network-based approaches, with static or discrete dynamic procedures only, the EXPAND project centers on an highly demanding intersection of visual analytics and network analysis, that takes on the challenges of continuous and event-based data, containing rich attributes and being of large scale. To do so, radically innovative concepts and methods have to be aligned and integrated into a visual analytical framework, that combines advanced visual techniques (from information visualization and graph drawing domain) and analytical techniques (from data mining and network science), driven by perceptual and cognitive considerations.

The result is expected to enable diverse R&D actors to visually analyze their developing fields of technologies on a continuous empirical basis. The advancement of the research prototype and its future implementation into the business partners IT service portfolio will promote the economic exploitation of results as well as his extension of economic advantage in the strategic business intelligence market.


Paolo Federico, Florian Heimerl, Steffen Koch, Silvia Miksch, "A Survey on Visual Approaches for Analyzing Scientific Literature and Patents", IEEE Transactions on Visualization and Computer Graphics, vol. 23, pp. 2179 – 2198, 2017. paper Video Teaser
Paolo Federico, "Visual Analytics of Dynamic Networks", Faculty of Informatics, vol. PhD in Computer Science, pp. 192, 2017. paper
Paolo Federico, Silvia Miksch, "Evaluation of Two Interaction Techniques for Visualization of Dynamic Graphs", Proc. of the 24th Int. Symp. on Graph Drawing & Network Visualization (GD'16), 2016. paper
Albert Amor-Amorós, Paolo Federico, Silvia Miksch, "Visually-Supported Graph Traversals for Exploratory Analysis", Proceedings of the IEEE Visualization Conference (VIS) - Poster, 2016. paper
Florian Windhager, Albert Amor-Amorós, Michael Smuc, Paolo Federico, Lukas Zenk, Silvia Miksch, "A concept for the exploratory visualization of patent network dynamics", Proceedings of the 6th International Conference on Information Visualization Theory and Applications, 2015. paper
Daniel Archambault, James Abello, Jessie Kennedy, Stephen Kobourov, Kwan-Liu Ma, Silvia Miksch, Chris Muelder, Alexandru Telea, "Temporal Multivariate Networks", Multivariate Network Visualization, pp. 151-174, 2014. paper
Bilal Alsallakh, Silvia Miksch, Andreas Rauber, "Towards a Visualization of Multi-faceted Search Results", Workshop on Knowledge Maps and Information Retrieval (KMIR), vol. 1311, pp. 4, 2014. paper