- What representation techniques are suitable for the display of the attributes of archaeological sites and what are their advantages and disadvantages?
- How effective is the extended STC environment for Archaeological data?
- The visual representation of temporal data
- How to display multivariate spatiotemporal data (value patterns vs.
- Magnitudes and vectors from classical mechanics/dynamics---such as
velocity, acceleration, momentum, and curvature---can be calculated
as additional, derived attributes of N-dimensional point records in a
time-ordered data set. Which of these metrics might facilitate
specific visual exploration and analysis tasks?
- How can visual analysis tools encode, in different views/
coordinate spaces, both points and (sub)sequences as a function of
individual metrics or combinations of them? How does simultaneous
encoding of multiple different but related metrics (possibly
including location and time) in a limited number of graphical
channels affect perception and interaction?
- How should visual analysis tools deal with (additional) absence/
noise/uncertainty in the form of invalid values, zeroes,
singularities, etc. in the calculated sequence of values for such
- In order to aggregate and summarize movement data, it is often (always?) necessary to coarsen the spatial component of the data, i.e. use areas instead of points. How (according to what criteria) can such areas be appropriately defined? Two cases should be considered: (a) areas covering the whole territory; (b) areas representing "significant places".
- Is it possible to aggregate and summarize massive movement data without dividing the space into compartments or defining "significant places"? How this could be done?
- Summarization algorithms used for space, time and space-time
typically rely on (arbitrary?) threshold settings. How do we
validated found solutions based on "empircially based" threshold
- How can algorithm settings and/or thresholds that are individually
valid for space or time problems be combined for space-time problems?
- Permitting temporal lags of less than one year would, for this analysis, result in several more matrices and maps. Questions including within year variability could be addressed, yet computation and interpretation investments would increase. In data mining, we don't necessarily know the appropriate temporal aggregation unit (lag) for analysis. Similar to our choice of a global statistic, Ripley's K, to guide the spatial lag parameter of local spatial statistic calculation, how might we visually or computationally introduce a choice of temporal lag parameter for attribute change calculation in the tool?
- Immigrant destinations are not emphasized in the user interface of the tool, but rather presented as a drop-down menu. Not emphasizing the spatial arrangement of destinations permits the tool to be directly applicable to spatio-temporal phenomenon that do not have an origin-destination component. However, does this design present a significant limitation for data mining patterns of immigration?
- Graphical conventions appear to us every day and everywhere. We learned
them to the point that they become a natural language. For example, green,
yellow and red, immediately remind us of the traffic lights indicating a
level of danger. Because those signs become so natural in our lives, would
it be more efficient to use such graphical conventions (even if they don’t
correspond to semiology theory) for information to pop up than good
- To what extend can we customize a visual representation so that it lowers
the attention towards details and puts forward the trends in the data
without any mathematic or statistic manipulations? In other words, the goal
is to direct the user’s attention to the overall reading level allowing,
even forcing, visual aggregation of data and enlightenment of information
simply by changing visual displays of data. A good example would be to
visually group data by displaying all middle categories the same way and
displaying only the extremes categories differently. This would places the
emphasis on extremes and might help to discover some patterns without
changing the number of categories.
- “Business graphics are more colourful, easier to produce and faster than
ever, but the popular basic chart types haven’t changed in decades. Numerous
new visualization techniques have been introduced , but none have been
widely adopted, despite the apparent need for them in business intelligence
applications with large data volumes to report. One problem seems to be that
the more advanced charts are not immediately intuitive for the reader; if
users need special training to understand new chart types, they are not
likely to become mainstream.” (Business Application Research Center, 2007)
Along the same line, are new or unusual geovisualization techniques “really”
useful for non-expert users or decision makers?
- How can you aid a user in associating geographic context with
annotations made in a geovisual analytic environment to better support
capturing and sharing insights derived through the use of the application?
- How might annotations support collaborative use of a geovisual
analytic tool and what tasks can visual representations of this content
help the user perform?
- How can computational approaches aid the user in making sense of
annotation repositories as they grow over time and augment the use a
geovisual analytic environment?
- when interpret the clusters
generated from statistics methods, what other issues we need to
consider, other than reliability and heterogeneous issues;
- how to judge ( or evaluate) the success of the methods that combine
visualization and (spatial) statistics methods
- Clustering is often accompanied with the problem of visually defining size and boundaries associated with the clusters. What are some of these problems, and how do they influence how researchers and the general public view clusters of events?
- What other types of methodologies are available for visualizing clusters in meaningful and statistically significant ways?
- How do geovisual analytics yield more effective hurricane climate
analysis than traditional weather science approaches?
- What are the current limitations of the system described in this
presentation and what potential solutions are envisioned?
- How does the system facilitate space and time analysis?
- Our VA infrastructure provides the opportunity to collaboratively
integrate data and efficiently stream the differences or past
revisions of this data.
- What are the spatio-temporal challenges we should deal with? E.g.,
we see possibilities with the aggregation of time intervals or
interval steps to compare data.
- What interfaces or methods should we support to best assist GVA and
its related data mining, statistics, and optimisation tasks?
- Imagine globally spread research teams performing collaborative GVA.
- What kind of data would they dynamically add to the shared
repository? E.g., one might upload a large set of statistical data,
one might tag a selected area with some text notes, and one might add
a figure or bitmap data;
- What is the degree of interactivity? Is it a asynchronous process
which could be compared to some kind of GVA Wiki(pedia)? Or is it a
synchronous process more comparable to a chat room than a Wiki;
- Are there established workflows with different roles for
collaborative GVA (as seen with other collaborative document authoring
- The need for quantitative evaluations of geovisualisation designs in order to yield
valid scientific results.
- Studying “internal representations”, neurocognitive principles, and cognitive
processes with respect to the design and understanding of geovisualisation
displays as well to the development of geospatial visual analytics tools.
- The effect of information density (number of items displayed) on the user. Is 'less
more' or is 'more more'?
- How to best enable geographic collaboration for visual analytics,
in terms of a user interface?
- Which visual analytic operations should be exposed for sharing
between collaborators, and which are best reserved for a single
- The effectiveness and usability of the structured phrase-driven approach
for data query and visualization for non-IT users.
- What are primitive representation techniques for geo-spatial
visualization in terms of properties and objects in oil reservoirs?