the issue:
Understanding, modelling, visualising time-oriented data has emerged in the recent years as a major interdisciplinary research challenge, often bridging knowledge technology disciplines, geosciences, human sciences, environmental sciences, with a number of key contributions stemming from the infovis and visual analytics communities. Yet handling and visualising temporal aspects, dynamics of change, is nothing like a new issue: a number of masterpieces in the history of data and information visualisation reflect the importance given to that parameter for decades if not centuries. To this date though, time is still sometimes seen as little more than one more attribute - yet another tag added to a piece of information. Noticeably, computer solutions may sometimes have driven the analyst to minimize, deny the complexity of time – multidimensional although appearing to us as unidirectional, running linearly. Accordingly, they may even here and there have altered the analyst‘s depiction of processes, his capacity to view and think temporal aspects.
Furthermore, today, in many areas of research, analysts face dirty time-oriented data (inaccurate, incomplete, erroneous, contradictory, etc.): they may typically face incomplete, untrustworthy, ill-distributed historical evidence; contradictory reports in human testimonies, informational blackouts due to failures in monitoring systems, uncertainties in the early stages of planning activities, etc. The workshop’s goal is to pull together expert views (short and regular talks) on modelling and visualisation challenges encompassing both theoretical approaches (methods, concepts, etc.) and feedbacks from real cases.

To be found in Graz:

The conference is hosted here (Messe Congress Graz , www.mcg.at/en):

see also www.graztourismus.at/en

expected outcomes:
Following a 2012 event by the MoDyS research community, the workshop's expected outcomes include a better acquaintance with relevant work across scientific domains and application fields as well as the emergence of ad-hoc metrics – an attempt to ease the task of cross-examining responses to data quality issues. Ultimately, the initiative wishes to contribute to the strengthening of the community of analysts dealing with quality issues in the context of temporal data and information sets.