A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management

Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analysis possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and almost neglect the human in the analysis process. Outcomes from research in information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics.

[1]  B. Bloom Taxonomy of educational objectives , 1956 .

[2]  Thomas Ertl,et al.  Visual patent trend analysis for informed decision making in technology management , 2017 .

[3]  Qiang Zhang,et al.  TIARA: a visual exploratory text analytic system , 2010, KDD '10.

[4]  Ryen W. White,et al.  Exploratory Search: Beyond the Query-Response Paradigm , 2009, Exploratory Search: Beyond the Query-Response Paradigm.

[5]  Wim Vanderbauwhede,et al.  A survey of patent users: an analysis of tasks, behavior, search functionality and system requirements , 2010, IIiX.

[6]  M. Sheelagh T. Carpendale,et al.  SparkClouds: Visualizing Trends in Tag Clouds , 2010, IEEE Transactions on Visualization and Computer Graphics.

[7]  Arjan Kuijper,et al.  Visual trend analysis with digital libraries , 2015, I-KNOW.

[8]  Holger Ernst,et al.  Patent information for strategic technology management , 2003 .

[9]  Kawa Nazemi,et al.  Visual Analytics for Analyzing Technological Trends from Text , 2019, 2019 23rd International Conference Information Visualisation (IV).

[10]  Martin Wattenberg,et al.  Parallel Tag Clouds to explore and analyze faceted text corpora , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[11]  Lucy T. Nowell,et al.  ThemeRiver: Visualizing Thematic Changes in Large Document Collections , 2002, IEEE Trans. Vis. Comput. Graph..

[12]  Gary Marchionini,et al.  Exploratory search , 2006, Commun. ACM.

[13]  Fulvio Corno,et al.  Review of the state-of-the-art in patent information and forthcoming evolutions in intelligent patent informatics , 2010 .

[14]  Hansjörg Schmauder,et al.  Visual analysis of microblog content using time-varying co-occurrence highlighting in tag clouds , 2012, AVI.

[15]  Shimei Pan,et al.  TIARA: Interactive, Topic-Based Visual Text Summarization and Analysis , 2012, TIST.

[16]  Frank van Ham,et al.  “Search, Show Context, Expand on Demand”: Supporting Large Graph Exploration with Degree-of-Interest , 2009, IEEE Transactions on Visualization and Computer Graphics.

[17]  Qi Han,et al.  CiteRivers: Visual Analytics of Citation Patterns , 2016, IEEE Transactions on Visualization and Computer Graphics.

[18]  William Ribarsky,et al.  ParallelTopics: A probabilistic approach to exploring document collections , 2011, 2011 IEEE Conference on Visual Analytics Science and Technology (VAST).

[19]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[20]  J. Bruner The act of discovery. , 1961 .