@inproceedings{ceneda_guiding_2016, address = {Baltimore, MD, USA}, title = {Guiding the {Visualization} of {Time}-{Oriented} {Data}}, abstract = {The analysis of industrial processes allows quality assessment and production monitoring. Usually these operations are carried out exploiting time-series data. In this work, we analyze a concrete design study of space efficient and time-aggregating visualizations for the analysis of high-frequency time-series. We derive recommendations to enhance the design process and demonstrate their applicability to our case study.}, booktitle = {Poster {Abstracts} of {IEEE} {Conference} on {Visual} {Analytics} {Science} and {Technology} ({VAST} 2016)}, publisher = {IEEE}, author = {Ceneda, Davide and Aigner, Wolfgang and Bögl, Markus and Gschwandtner, Theresia and Miksch, Silvia}, year = {2016}, note = {Projekt: VisOnFire Projekt: KAVA-Time}, keywords = {2016, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Schriftpublikation, Time-Oriented Data, Visual analytics, peer-reviewed, visualization, ⛔ No DOI found}, }