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Tag "GeoTime"

The folks over at Oculus have been very busy developing the GeoTime software. Version 5 was released in the beginning of 2010 and they are going to released the latest update GeoTime 5.1 these days.
It includes some very interesting new features. The two major ones are the Network feature that allows the user to visualise the data as a network besides the time-space visualisation and the second major change is the support of the macOSx platform (see earlier post on mac adventours using GeoTime). This is in a sense a clear statement of independence, if there was critique that GeoTime integrates too closely with ArcGIS. However of course it continues to integrate well with Arc and support for the new ArcGIS 10 comes with the new GeoTime update.

The software is perfectly fitted for the UrbanDiary project that works with GPS tracks of individuals, investigating the spatial extension of everyday routines in the city. It is basically a purely spatial-temporal dataset. In a few easy steps it is possible to see the data visualised in a simultaneously temporal and spatial way, animate it as well as start analysing it.

Image by urbanTick / A view of different GPS tracks over the period of one month, using GeoTime and an OSM base map pulled in via ArcGIS.

The move away from a secondary software import via ArcGIS or Excel was a good move that came with version 5.0. The importing formats have been extended and redesigned with the release of version 5.0 to include CSV, XLS, and SHP file formats as well as the in version 4.0 existing KML. It is now handled directly by GeoTime through a functional assistant. With version 5.1 the import of GPX file format is added. Data from the GPS exported in this format can be loaded and added to a project directly.
The new dialogue allows to filter the data at import. This is useful especially for my crappy overloaded tables in which I tried to record way to much. The selection of just the five essential columns makes for a much more slik workflow.
GeoTIme focuses on temporal data, however the integration with realtime data has only be introduced recently with the 5.0 release. Now users can import live feeds via Geo RSS that automatically updates.

The data is initially visualised in the 3d view as a time-space cube. To interact with time one finds the tools on the left hand side vertically arranged. On the right hand side the menu provides a range of other tools including representation settings, pattern analysis, reporting tools and the new network tool.

Image by Oculus / An example using the new network tool in GeoTime visualising a computer network.

The network tool is a whole new field that has been added to GeoTime with this functionality. This is particularly interesting for the analysis of complex structure that include spatial and non spatial data, such as for example phone call data or financial transaction. In the context of the UrbanDiary project for which GeoTime is used here this new tool becomes interesting for the investigation of combinatory data from GPS and mental maps, as for the analysis of interrelationships between landmarks and actual route. For the visualisation different present network settings are available. Furthermore it integrates with the 3D visualisation of the spatial data and the network graph is directly linked to the time-space cube and highlighted areas correspond across the two visualisations. So specific sections identified for further investigation at one end can be look at from a different perspective at the other end.

For the data analysis in the spatial-temporal section, one of the new features in this 5.1 release is the stationary detector. The data can now be queried for events that have not moved in space over a longer period of time. This is useful for the data verification as well as detection of move and rest patterns.

One of the remaining points of critique is still the graphical representation of the visualisation as well as the range, simplicity and of possible manipulations of it. There have been however, some changes made and for example the colour palette has been extended. But still both the interface and the results are still very technical thought of and rendered. It would not ne a mater of just making it all fancy and colourful with rounded corners, but it would need one strong design direction as a well as an overall visual simplification.

Image by urbanTick / Applying the stationary finder to a track imported via GPX directly into GeoTime. This highlights the areas where the GPS device has not moved more than 100 metres over a period of more than 8 hours. It uses the OSM base map pulled in via the ArcGIS link.

In an comment on GeoTime 4.0, I hade described it as an end-of-the-line analysis tool. This was because the data could not be directly exported to other software packages. This has changed with this most recent update, now CSV export is supported in addition to the KML and screenshot export. The analysed file can be passed on to other software or users which dramatically enhances the usage and the integration of GeoTime.

Image by Oculus / The GeoTime 5.1 Logo.

In this sense the spaceTime aquarium has become a lot more sophisticated with this GeoTime 5.1 release. At the same time, though, it ha become accessibel for a much broader range of specialised fields through the extended palette of tools. It can now integrate in a workflow, be run as stand alone analysis software as well as operate across platforms. GeoTime is a very specialised tool and definitely offers the quickest and most comprehensive set of visualisation and analysis tools for temporal data.

For demos and further information on the GeoTime project use the inks or go HERE or HERE for earlier posts about GeoTime on urbanTick.

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We have been logging Twitter activities in the London area (M25) over an earlier weekend in January with some code Steven Gray has put together. The idea was to log the location based traffic and see what the mapping of it would bring. There are a number of twitter mapping projects out there already, for example twittermap.tv from where the timeLapse of the weekend activity was captured HERE, or the first big mapping project twittervision.com. However, we wanted to focus on a local region, a city, to see what the traffic is and how the location might play a role. The traffic visualisation page tweeTOMeter is part of this interest.

Image by UrbanTick / Screenshot of Twitter data visualised in GeoTime’s space-time aquarium.

One could think of this investigation as following the urban story quite literally, while following the tweets of citizens. However it is quite tricky to make sense of it all. The dataset for the weekend, which covers Friday evening to Monday morning contains some 300’000 tweets. Not all of them are properly geo referenced. Only 1’700 have actual Lat/Long information in the geo tag field. Furthermore some 60’000 have Lat/Long details in their profile tag field and the ret only has a generic profile location, such as London. This probably is because of the relatively new geo support of the Twitter API. Most users still seem to have little interest to include their actual location, as well as a lot of the applications do not yet properly support the format. Interesting seems to be the network. Whom are tweets directed at? It seems to be quite a high average of direct tweets, almost 3 per message. Also who will actually read it, how many followers are there in average?
Working with the real geo referenced tweets, surprisingly they contain quite a bit of movement.
For a quick look at the data it has been visualised in GeoTime. The representation in the time-space aquarium makes the diagonal lines, that suggest movement, very distinguishable from the vertical stationary lines. While looking at the replay in the 2D view the weekend really comes to life and London gets busy.

Similar visualisation, with snippets and names, but without the river Thames, can be fund HERE.
GeoTime here really offers a powerful and very quick way of visualising the data in space and time and offers a whole pallet of different visualisation types, each including a set of tools for analysis and manipulation. Import comes either via ARCGIS or even quicker excel.
The main problem really is the quality of the graphics, the design of the result. Here the user has hardly any choice or possibilities to manipulate anything from colour palette to line style or font. This is a bit annoying especially because the tool is kind of an end of the line analysis tool, after you have prepared the data elsewhere.
The second quick one goes into Google Earth obviously. Here the data again comes from a simple excel spread sheet with a VB macro to write the KML file. This literally takes 5 seconds to do and you have a KML file, including time tags in Google Earth.
This one only plays the locations though, also in a time window of some six hours.

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I will be at the IDRN conference tomorrow at the Royal Geographical Society in London. It is under the title of ‘The use of mapping software & systems in health and academic research’. Mapping in the area of health research has recently become popular. We have seen some experiments earlier this year using data related to the spread of swine flu. Also there is the Google Flu Trends project, monitoring flu outbreaks. Apparently they are pretty good, only I think with Swine Flu they had some problems. Interesting that there is no data available for the United Kingdom on the Google page.
However, I am presenting a poster with the tracking data of the UrbanDiary project. Showing different approaches of visualisation techniques. The normal map using arcGIS, then there is the time-space aquarium viz, done in either Google Earth or GeoTime and the last visualisation is individual movement with the context of the built environment, again using arcGIS.

Image by urbanTick for urbanDiary – click for detailed view

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Finally I managed to get some kind of data from ArcMap linked into GeoTime as a base map. The projection that works is only WGS84, but most of the data we have her obviously is in British National Grid. So some transformation is required. This very often results in some funny shapes and suddenly you go, wow, I haven’t seen greater London as this kind of squashed tomato shape yet. Another problem is to get the transformed files to match up, and so on. It is confusing.
But her we are at least the Greater London area is there and the river Thames.

Image by UrbanTick for UrbanDiary – Location points with river Thames (far left), inner and outer London (centre), London regions (right)

And then even the buildings appear, imported from the Virtual London Model, developed here at CASA. They are slightly out of place but there they are.

Image by UrbanTick for UrbanDiary – zoom Kings Cross with location spots

Next step will be to ad some detailed information to the GeoTime data. At the moment it only represents track point location data. But with the series of interviews that are underway at the moment some more detailed data about the participants activities are available and GeoTime could be quite helpful in relating these different types of information.

Image by UrbanTick for UrbanDiary – lines of activity, zoom Kings Cross (left), Kentish Town East (right)

These Images are screen shots taken from GeoTime with the software’s internal screen grabber. The top view was used to get the displayed GP data to mach properly with the imported base map. For visualization purposes this was seen to be the easiest way o understand what was going on. By switching into 3d view things get complicated and it is difficult to make sense from the combination of data that moves up and down in time and a base layer with a static map. Specially when zooming in to see details. The feature to replay the data can be helpful in this situation though. The map then acts as the division between past and future, basically the present. A location dot is used to mark this position.

Image by UrbanTick for UrbanDiary – 3d view in GeoTime


An update on this mapping topic.

The issues where something I talked about with Curtis from GeoTime. He suggested that a very quick fix is a available through the recourses in ESRI ArchGIS. They actually offer a number of base map under file, free recourses in 9.3 the world street network works quite good for the London location. And after I found the slider to adjust the map transparency I was quite happy with the result.

Image by UrbanTick for UrbanDiary – central London view with ESRI recourse base layer imported from ArcGIS

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I have reinstalled the iMac and set up parallels on it. This allows to run the Mac osX and Windows Vista in a separate window.
And there you go, it allows to install, GeoTime on a Mac. So far I was running it on a windows machine.
I tried a few things, including importing the whole data set from the UrbanDiary project. It works ok, but seems to be slower than the installation on a Windows machine. I will test it some more and see if it is worth working on it on Mac. Next step will be to get the arcGIS integration to work with it on the Mac.

Image by UrbanTick

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After a lot of complicated file manipulations, the data is in a format or better in a location or just is set up to be usable. Well, it is not exactly complicated to handle the data, I was just not quite sure how best to store it. The main problem is the date format, a misinterpretation seems to happen during one of the steps, still have to figure out where exactly.
So it took a few trial and error investigations to figure out what might be usable. The solution for the moment is gpx to csv to database and then to put into Google Earth or GeoTime it has to go back into a csv to Excel.
So from Excel it can simply be linked to GeoTime. While installing GeoTime it will automatically install the GeoTime Excel Plug-In that can then be use to link the open spreadsheet to GeoTime. There is a setup to be made but this is rather straightforward, basically telling GeoTime which column of the spreadsheet contains what kind of information. Several different settings can be saved for later use, which is great, as it is likely that the same source will be used a number of times. Then the data is in GeoTime after some processing. ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

Image by urbanTick – Screen shot from GeoTime

Funny enough, this time the meeting query tool works. After failing to use it in my first go with the Plymouth365 data, I was tempted to get this to work with the new UD data set. And there you go it worked right away. I guess I was just not patient enough with the larger PLY365 set, it probably just takes long, longer than I was willing to wait….
Anyway, interesting who has meet during this first week of data collection. Surprisingly, some people who do not know one another have actually met within a few minutes time difference in the same location. According to the data they just crossed path briefly, but still.

Screen shots from GeoTime, showing meetings in space and time – by urbanTick

Telling from those screen shots, GeoTime’s ability to output information apart from the screen is pretty bad. As a designer and visual person I want much more control over this than this program offers. It is essentially a screen shot in png format. It should at least offer an option to output some vector format to allow further use and especially endless sizing options.

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Today I have finally got round to install and try the software GeoTime on my computer here. Oculous kindly offered a license to run some trials on with my data.
It installed all very smoothly and the process is straight forward. I had to click through a few pages of the tutorial files to get the data to appear in GeoTime, but here it is.

​Image by urbanTick – data Plymouth365 – full extend (I should use a cleaned up data set, those GPS errors pop out too much…)

Image by urbanTick – Data Plymouth365, zoomed in to the city, very colour full

It is the same data set used in visualizations earlier, as in Plymouth aquarium.
The data was imported using excel and following some advice from the tutorial pages. GeoTime seems to be very picky with the kml files. I didn’t get one of those to show. Exporting to kmz works fine and looks good in Google Earth. The exported file is truly time tagged, this means the time feature can be used and the data can be replayed. ​
Image by UrbanTick – GeoTime export to Google Earth

Some analysis functions sound really interesting. I finally got the meeting analysis function to work. This would be very interesting, have to work on this.
Great are the isolating features, where it is possible to only display data with certain characteristics, for example a time frame.

​Image by urbanTick – data Plymouth365

Image by urbanTick

There is more to come, this will occupy the next weeks to work trough my data with this new tool.

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Here are two software examples that are specifically designed to tackle the time-space-visualisation-problem. One of them is GeoTime developed by Oculus a leading and award winning provider of visualisation solutions, as they call themselves on the website. It is aiming at high end users and is as expected not cheap. The other one is a Google Code project called timeMap developed at the MIT in connection with the SIMILE project and freely available.
With GeoTime is it possible to visualize time based tracking data in an aquarium sort of way, as developed by the Lund School in the 70ties. It also uses the third dimension to show the passage of time. So spatial locations are shown as x and y and the time is shown as z coordinate. Only this month Oculus released a brand new version 4, which is said to be completely rebuilt in order to, enhance performance. Interesting could also be the Web 2.0 support. The GeoTime application does integrate with ESRI and Microsoft Products.

Image taken from GeoTime website

The really nice thing about the program, compared to the aquarium visualisations in Google Earth, is that the ground plane is interactive and can be moved in the z dimension. Effectively the plane with the spatial configuration of the surrounding represents the present and divides virtually the past from the future. What is useful is that the connection between activity on the vertically extruded path is always relatively close to the surface that displays the context information.

Image taken from GeoTime website

For information purposes Oculus has published a nice flash presentation to introduce the GeoTime software.

The open source software on the other hand is a set of code that can be used and reused. It is basically a JavaScript library and it uses the SIMILE timeline and displays on Google Maps. Different data sets can be loaded including Json and KML. It reads the location information and the time information.
The time line sis in the top part and is visualized as one or more bands that can be moved horizontally in order to move back and forward in time. The map sits below and displays by default events that are visible in the timeline frame.
By scrolling through the time bands the map adjusts. With some simple code elements it is possible to visualize data interactive.
I had a go with the data from the Christmas aquarium that I used to play with the Google Earth gadget earlier this month.
So with a bit of clipping and pasting from different examples I was able to load the KML file and have it displayed in the browser.

Image by urbanTick – Screenshot of timeMap running some urbanDiary data

There are a lot of possibilities to play around with this code. I am really looking forward to spend some time on this. It is not only the layout and the settings in the code that are exiting, but also the possibilities of integrating different data sets. The recorded tracks could for example be accomplished with some life information feed from online sources, e.g. Flicker, Twitter or News. The KML setting also need to be sorted out. The current production line for GPS track files is not very convenient.
I will try to put he version above live soon on my web space to see how it runs online. In the mean time have a look at these examples.
Timemap examples with Json data – Artists & Authors of the Renaissance, Timeline SMILIE example – The JFK Assassination Timeline.

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