Longhouse 3.5.5

IMG_4566It’s been a whirlwind week here.  Craig, Jamie Kwan and I attended the Heritage Toronto Gala Tuesday night to roll out the first public viewing of Longhouse3.x.  Jamie was my graduate research assistant this year in the Master in Digital Media program here at Ryerson University, who used his architectural training to help visualize the modern interpretation of a 3D longhouse in Longhouse 2.5.  It proved to be a stellar night and full of surprises from a research perspective.  I want to thank Heritage Toronto for the opportunity to present our work and a special thanks to Claire van Nierop and Ron Williamson from ASI for inviting us to be part of their presentation.


Due to some last minute difficulties we had running the Ocular Rift DK2 on our Alienware Laptop, we switched to a monitor setup with XBox360 controllers for people to use for one station and Craig used his HP Laptop and OR DK2 for our virtual reality experience. Both interaction platforms were well received, but the OR obviously was the favourite choice among the 30+ or so people who participated.


We had a wide range of age, genders and Heritage professionals and enthusiasts try the VR experience.  A non scientific observation was that our female participants spent a considerable amount of time within the environment, experiencing and observing all of the aspects of the reimagined longhouse, while our male participants usually donned the VR for it’s “cool” factor and then ran around quickly without taking the time to notice all of the elements within the environment.  As we had older guests and also didn’t know who among our potential visitors might have ocular issues when putting on the headset, we chose to go with a seating position to ensure some stability for those who might encounter balance issues.  Headphones were used to focus the hearing into the virtual space (which was a combination of forest, water, animal and burning fire sounds based on where you were).  The controller was used to move the individual forward or backwards with the head movement dealing primarily with where you would look in VR space.  As one visitor observed, the OR DK2 naturally allowed the Heritage professionals to look up and around, as they would normally do.  One feature we didn’t have was a crouch command to allow people to inspect objects on the ground or below the standard height within the gaming environment.

The video loop above is our latest test of the longhouse within Unity5.  By staging the visualization of items in the longhouse with everyday domestic items such as food and cooking utensils, it started further discussions on potential placement and use of those items within the space.  Additional constraints involved the light and how it would effect shadows and highlights within what would really be a dark environment.  Lastly, Craig had added smoke from all of the fires, but we soon discovered that it really filled the entire space, especially at the 4-5ft level with a dense fog which made it difficult to see the details in the models. We plan to provide a smoke and non-smoke version shortly to demonstrate what it would be like, which would likely be very unpleasant to function in during the long winter months.


We added items such as cooking tools, pots and bowls (even with liquid in some….boiling to come later) but the placement is completely assumed and somewhat random.  We can easily change position and hopefully in the next couple of iterations we should be able to pick up objects and move them elsewhere.  Craig did a wonderful job replicating the bowls and spoons and we used previously modelled Iroquoian ceramics from the Sustainable Archaeology test in Longhouse 2.2, although we did have to vastly simplify the students models for the gaming environment.


One of the major issues we encountered was the complexity and detail we had been adding into the environment.  There has been a lot of thought and detail put into every element and along the way we have tried to optimize the digital assets so that real-time play would not be compromised, but it was clear with the test we did at Heritage Toronto that some creative “faking” will need to happen so as to speed things up virtually. This faking method would be to use texture maps instead of models for things such as bark cordage/rope, using more pre-rendered complex images and greatly reducing the polygon count on each of the objects within the scene.


Another observation was with the outside bark shingles.  They look bright and new and it’s likely that vast amounts of moss and other errant plant material would be growing on the sides, edges and tops of the longhouse.  Rotting of some sort would have taken root as well with the shingles itself and I suspect there would be discolouration due to weathering.  We still need to add the exterior exoskeleton which helps to stabilize and support the shingles.


This test marks a major stage in the research.  We are fairly close to the final product and will likely be spending the next month or so cleaning up the assets, increasing the speed of the virtual interaction and hopefully providing some user abilities at least in this version for users to pick up objects and possibly interact with the environment more substantially.  As an artist, I crave the hyperreal fully rendered images and sequences, but practically to allow for as many people to engage with the research, a gaming engine is needed and thus that hyperreal look becomes more stylized.


I would encourage our weekly readers to post comments or send questions through email.  This is how we are learning about new theories, methods and perspectives which only strengthens the projects goals.  Take a spin through the rendered gaming sequence and feel free to comment!

If you are in Midland Ontario this weekend, don’t forget to attend the Ontario Archaeology Societies Symposium – Circles of Interaction: The Wendat and their Neighbours in the Time of Champlain!






Extracting Useful Data from Twitter for Methodological Evaluation – Part II


11.35: The hashtag RichardIII is now trending on Twitter. This was reported by Telegraph Reporters on Sept 12, 2012 during a minute by minute timeline of the announcement that the University of Leicester Archaeology Team had discovered bones believed to be Richard III buried under a Council parking lot.  Suffice to say, this was seminal event in archaeology, as it was the first time that embedded reporters reported live and in realtime, an archaeological event.  Twitter brought that news to the world.

In the second part of our investigation in extracting useful data from Twitter for methodological evaluation, I’m going to use Topsy again to try and provide a view of digital media, archaeology and public engagement.  Does an event such as this, also help to expose the public to archaeology and archaeologists or are these terms co-opted byproducts of a pop culture event?

To recap, two events occurred surrounding the discovery of Richard III.  The first happend on September 12, 2012 with the University of Leicester announcing that they had discoverer what they believe might be the bones of Richard III, with almost 1565 unique Tweets under the hashtag #richardIII.  The second event was the official news on February 4, 2013 that the archaeological team had confirmed the bones to be Richard III.  On that day, 66,696 Tweets where made world wide.

A couple of things need to be considered with this query.  In Twitter, when users want to “home in” on a subject matter of interest, they tend to use a hashtag such as #richardiii.  Prior to the original announcement of Richard III bones being discovered, the hashtag #richardiii was used by a various assortment of users who primarily discussed the works of Shakespeare and specifically the play The Tragedy of Richard the Third.  In the course of the archaeological discovery, this hashtag was hijacked by people wanting to connect or Tweet about the discovery of the bones and the subsequent news related to that discovery.  More importantly however, that hashtag was not the only way people Tweeted about Richard III.

Keywords are important when mining Twitter data.  Using additional related terms such as “Richard III”, “King Richard III” and “King Richard” a fuller picture begins to emerge of the extent of Twitter activity surrounding the archaeological event.  By combining total Twitter counts of just these four terms, total number of Tweets jumps to 430,079 over a 24hr period.


Essentially we are looking at the gross number of actual Tweets that contained the search terms above over a 24 hour period.  However, the story doesn’t stop there.  Inferences can be made on how many Twitter users were actually exposed to the Richard III terms above on Feb 4, 2013, buy taking the gross number of followers of each Twitter user who posted any message with “#richardIII”, “Richard III”, “King Richard III” and “King Richard”.  Using this methodology employed by Topsy, the system estimates that 1,280,087,045 Twitter users were exposed to a Tweet of some sort on Feb 4 around this archaeological event.


Topsy’s describes its methodology this way; Topsy calculates exposure by summing the follower counts of all the authors of tweets that match the keywords being queried. This calculation returns overall gross exposure (vs. unduplicated net exposure) so multiple tweets from the same author or authors with common followers may result in audience duplication.  To better understand the margin of error, Topsy would have to predict and/or calculate how many times the same Tweet was distributed by the same author.  As with using the search terms “#richardIII”, “Richard III”, “King Richard III” and “King Richard”, there is no clear indication on how much duplication within the gross calculation has been made.

Finally, one of the interesting elements from an anthropological perspective of this type of real-time, machine language data mining, is the ability to estimate gross number of Tweets from country of origin and the positive, neutral or negative value of the qualitative or quantisized Tweet.  Let’s first look at the geographic makeup of Tweets over a 24hr period on Feb 4, 2013.


Twitter can “geo-tag” a Tweet and generally there is a 90% confidence that all Tweets from a certain country is correct.  Topsy states;  The Geographic view shows country-level metrics at a high confidence and coverage rates. The confidence rate will be 90%, meaning that 90% of tweets that are geo-tagged by country are correct based on our validation methods. The targeted coverage will be 90%, meaning that 90% of tweets that come from Twitter will be geo-tagged at the country level at the 90% confidence rate.  So when using this methodology, researchers must also be cognizant that “volume” is qualitative in nature and not quantitative.

Going beyond the margins of error however, it is interesting to see that the largest amount of Tweets were generated (328,340) from the United States.  Next was the actual country of origin of the archaeological event, with 49,439 UK Tweets.  Surprisingly, Indonesia had the third largest amount of original Tweets on the subject.  Next was France and then Canada.  The Canadian ranking of 5th was surprising, solely for the fact that the actual identification of Richard III’s remains would not have been possible without the DNA sample from Canadian Michael Ibsen, who is a 17th great-grand-nephew of Richard’s older sister — Anne of York.

If you compare the top 5 Tweets listed beside the geographic total, 4 out of the 5 original Tweets are from the UK and one is from the USA.  Unfortunately, also out of the top 5 Tweets, 3 are jokes about Richard III’s situation.  Which brings us to the skewing factor.  If one dives down into the actual quantitative gross counts, to examine the qualitative nature of the actual Tweet, a substantial amount of Tweets turn out to be original or retold jokes!  This was not lost on some as this Feb 4th post almost 16hrs from the original UK announcement in Maclean’s Magazine points out Richard III’s skeleton found; Twitter gets buried in jokes. Now Topsy nor do any Twittter data mining tool set have a “no joke” filter, but there are some interesting observations that can be made to discern how to filter the actual jokes from the data set.


As discussed in Part I of last weeks blog, Topsy and other data mining applications use Sentiment Analysis or natural language processing (NLP) to determine a quantitized value of the actual Tweet.  Topsy uses a NLP methodology that ranks words with a value from 0 to 100.  As Joe Masciocco, Social Analytics Consultant over at Topsy points out; in layman’s terms, we have language coding specialists on staff.  We score every word that comes through within each tweet on a scale from 0-100 (very negative – very positive) we then take a look at how the words interact and score the tweet on a whole from 0-100.  This all happens in real time for all tweets.  Hence Topsy quantitizes the content of the Tweet to determine it’s overall Sentiment (Driscoll et al, 2007).

Again there is no “joke” filter in NL processing, however I did discover something interesting when reviewing the graph above the quantitative data displayed by Topsy.  By clicking on the end points of each graphed line, the user can get a listing of the top 5 positive Tweets.  When we go through all four search terms, almost exclusively in this small sample set does the search term #RichardIII reveal where the “jokesters” live!  It seems #RichardIII by the end of Feb 4th has been co-opted yet again, but this time by people looking to plant or supplant a good joke!

Unfortunately like any interesting data, we have only scratched the surface.  In all the jumble of understanding how one archaeological event could potentially expose over 1.2 Billion Twitter followers in a single day to archaeology, we also need to examine how archaeology and archaeologists were effected.  In Part III, I’ll compare our Richard III event alongside mix methods analysis of archaeology and archaeologists to see if there is a correlation between pop event culture and public engagement archaeology.  I leave you with an article from the Washington Post I found in a Tweet from an archaeologist the day after the big event; On social media, archaeologists roll their eyes at Richard III skeleton discovery.




Driscoll, D.L., Appiah-Yeboah, A., Salib, P. and Rupert, D.J., 2007. Merging Qualitative and Quantitative Data in Mixed Methods Research: How To and Why Not. Ecological and Environmental Anthropology 3(1): 19-28.

Extracting Useful Data from Twitter for Methodological Evaluation – Part I

A facial reconstruction of King Richard III, based on an analysis of his recently identified remains and artist portrayals over the years, was unveiled by an eponymous historical society on Tuesday. (Rex Features / AP Images) @SmithsonianMag on Twitter

There has been a lot of talk about “Digital Archaeology” being “Public Archaeology” recently.  As part of my Methods class this semester, I wanted to put that assumption to the test and decided to analyse Twitter feeds on specific subjects against possible uptakes on other subjects.  In the last 365 days, the major archaeological event to occur has been the discovery and more importantly, confirmation of Richard III’s bones buried under a Council parking lot in Leicester.  The story is ripe for public engagement, especially since the Bard skewered Richard III in Tudor times to such an extent that he’s readily seen as a dastardly villain today!

Extracting meaningful data from any source is always a challenge.  With Twitter, it’s as David L. Driscoll et al coined as mixed methods research (2007), both qualitative and quantitative material extracted sometimes in meaningful chunks.  Several tools exist to do this type of analysis, but I found Topsy.com to be a great tool for first time Twitter data extractors like myself.  It’s as easy as typing in a Twitter hashtag or a subject heading and the system generates a report on the quantity and quality of Twitter results for that particular subject.


Doing a scan today on March 7 2013, over the last 365 days, we find that the hashtag, #richardiii has had 96,516 Tweets (as seen above in the chart generated in Topsy).  In that time, as displayed in the graph, there are two major events which help to accelerate and promote Twitter engagement around the topic of Richard III.

RichardIII 365 Twitter Analysis

They roughly occur at the Sept 12, 2012 mark when archaeologists confirm they have discovered what they think are Richard III’s bones and on Feb 4, 2013 when the University of Leicester confirms that DNA testing and physical analysis of the bones by qualitative means through oral histories and written accounts confirm that Richard III has been discovered.

Digging further down, on the Sept 12th, there were 1565 #richardiii Tweets.  Topsy can return data on the top Tweets and the content for that day which reveals the top # of Tweets coming from a journalist from BBC History Magazine who is supposedly embedded with the archaeologists at the moment of discovery.  The second top set of Tweets comes from Medievalists.net who is tweeting news from the Richard III Society about the success of finding Richard III.

Feb4 TopTweetsIn comparison on Feb 4th, when Richard III’s bones where confirmed, there where 66,696 Tweets.  The top tweet with over 1000 tweets and re-tweets was a Twitter handle by the name of @queen_uk Elizabeth Windsor, who’s message was; Don’t even think about putting one under a car park in Slough, which is a tounge-in-cheek reference to the industrial city just North of Windsor.  The second highest was from BBC Breaking News, reporting that the Mayor of Leicester had announced that Richard III was going to be reinterred at Leicester Cathedral (which, as we will see in next weeks blog has some interesting elements of it’s own).  The last three top tweets where from BBC and The Guardian reporting on official archaeological and scientific information.

Now, you’ll notice that the Top Tweets seem to be skewed in the Topsy screen shot above.  This is because Elizabeth Windsor, with 1000K tweets and retweets, actually had the fastest uptake amongst other twitter users.  BBC Breaking News, with over 4K tweets and retweets is the largest volume, yet the news spread slower than the joke.

Topsy also has the ability to breakdown the tweets into quantitative data.  However, as Driscoll et al (2007) discussed, Topsy can also quantitize, albeit with mixed results, the qualitative nature of the tweet into twitter industry accepted terms of Positive, Neutral and Negative Sentiments.  That is, the emotional value of the Tweet as written by the Tweeter through Sentiment Analysis or natural language processing (NLP).

Part II of our exploration into mixed methods research using Twitter analysis next week, I will explore some of the issues around the data generation in Twitter and specifically Topsy as well as see if my assumptions are correct from a Twitter perspective, that when an archaeological event like the discovery of Richard III happens, people become more publicly engaged in archaeology overall.




Driscoll, D.L., Appiah-Yeboah, A., Salib, P. and Rupert, D.J., 2007. Merging Qualitative and Quantitative Data in Mixed Methods Research: How To and Why Not. Ecological and Environmental Anthropology 3(1): 19-28.

TV Producing and Thesis Writing!

Last week was spring break at Western, which gave me some time to get caught up with hunting down current literature for my thesis.  It also gave me a great break from driving between Toronto and London, generally in the weekly Friday snowstorms!  I had however, the opportunity to stop in at Sheridan College to give my yearly lecture on Producing and Business in Animation to the latest cohort of 3D animation students.

I’ve enjoyed giving this lecture for about 10 years now.  As I had the spreadsheets and budgets projected on stage, it dawned on me that maybe, just maybe I could use my 17 years of production management experience in writing my thesis?  After all, to be a Producer you must have highly skilled management, organizational and analytical skills.  And, no matter how many times my wife says only women can multitask successfully,  I think I’ve mastered that one as well.

Students are always amazed when I recount that as an animation expert, my single most used software application now is MS Excel!  Practically every animated project must start by translating the creative and artistic style into schedules and ultimately budgets.  The process becomes repetitive and when one becomes good at it, all a client has to do is mention how many minutes a series is or long a film might be and generally the process can calculate the cost down to the last penny.  Although I miss the creative part, there is a certain artistic mastery in developing a budget and schedule.

I’ve been using an on-line tool called Ref Works, which has been extremely useful in automating the referencing process.  For students and teachers, it’s a free service provided by your university library.  Occasionally it’s a little buggy and I’ve had to develop strategies to get around some deficiencies but overall it’s been an excellent tool.  One particular nifty tool is the ability to link the reference within Ref Works with the actual PDF whether on-line or uploaded as a file.  This little feature has helped to “relocate” reference material quickly when it has been improperly filed on your hard drive.

However, I’ve been thinking about “how” I track those references within my thesis and more importantly “where” to insert those references when needed.  That got me thinking about Excel and Producing.  Essentially my thesis, or any thesis for that matter, consists of parts.  Simplistically it could be an opening, middle and end or conclusion.  However in archaeology we’re about the narrative.  So a good thesis should tell a story, whether it’s about scientific data or a qualitative experience, it’s still a story in which the reader must be engaged.

Excel is great for organizing data, so why not have it organize reference material as well?  The vertical columns can be the overall paper split into thematic sections.  The horizontal columns are subsections in which very specific reference points are made.  Each cell is a specific reference which in pure Excel functionality, can then be referenced and tracked in other cells throughout the entire set of thematic sections.  Visually, it can allow the writer to see weak points in their referencing by the lack of references within a section or if a particular reference is used too much.

Visualizing my references made me then think about all of the infographics out there and how those connections are made between references within a theses.  I found this really neat infographic which provides a good visualization of how data is connected in the writing process.  I think it would be a useful tool to visualize how references within my thesis are interconnected as well!

Copyright Playtime-Arts.com

So I started this blog thinking about how to manage data more effectively using my Animation Producing skills.  Now that I’ve reflected on how to organize my reference data, I’m also keen on how that data is interconnected and more importantly, how I personally make those connections between references.  A visual roadmap if you will to guide the writing process?

As an Animation Producer I’ve been able to incorporate my two favourite things; Excel and Visualization!  Now if I could only hand in an animated thesis, my job would be done!




Missing the Point? It’s the experience Dummy!

The last two weeks I was busily developing and presenting a draft of my proposed Research Flow Chart.  My old age must be setting in, because I find it harder and harder to develop succinct research ideas!  In an attempt to make sense of what I am trying to accomplish, I drafted a short paragraph to flesh out the idea and then to act as a guide for my Flow Chart.

Visualizing Southwestern Ontario Socio-Cultural Implications

in Longhouse Morphology and Use

Understanding Longhouse morphology amongst the Southwestern Ontario archaeological landscape as it relates to extinct and descendent populations is problematic.  Historical accounts can be romanticized or even intentionally misleading while socio-cultural variation within homogeneous cultural groups varies wildly based on outside cultural influences, landscape as well as environmental resources and factors.  Visualization of these variable Longhouse features may provide a unique opportunity to engage all stakeholders (public, private, academic and descendent) in redefining what it means to live within a Longhouse community by experiencing it phenomenologically through the archaeological record.

My research will focus on engaging with the archaeological landscape by creating a 3D virtual tool-set specifically designed to allow stakeholders (public, private, academic and to use a procedural 3D model library in order to build in real-time within 3D space, interactive pre and post contact Longhouses of Southwestern Ontario.  Further, when deployed, stakeholders should be able to experience multiple senses of sound, lighting, environmental and atmospheric controls to focus on the association between the physical structure, spatial relationships and the phenomenological experiences of Longhouse landscapes.

The aim of my project is to develop a new way to engage with the archaeological landscape that will help to broaden our understanding of longhouse construction, community organization and external cultural and environmental influences with an eye towards challenging our current assumptions of longhouse communities within the archaeological record.

Visualizing Longhouse Morphology and Use
Visualizing Longhouse Morphology and Use

Combined with what I think is a good start to a traditional Research Flow Chart, I’m relying heavily on Landscape and Phenomenological Archaeology.  When I initially presented the concept, my colleagues became engaged when I started talking about having stake holders actually experience the environment virtually, but with the aid of sound and smell.  One colleague who has been a site interpreter for Sainte Marie Among the Hurons in Northern Ontario indicated that when school groups first enter their reconstructed longhouses, people stop in the doorway to adjust their eyes……I stopped myself to think, how can I created the same effect in 3D?  Then the museum also uses the smell of a fire burning in the hearth or sweetgrass smouldering along with the sounds of everyday life to bring the landscape to life!  These Phenomenological experiences, combined with visual elements like light, atmospherics (smoke, rain, snow, dust) and texture help to extend that experience.

Maybe it’s the experience that is more important than how one builds that experience?  Can that experience be reproduced repeatedly?  Should it?

It took a while, but I think “it’s the experience Dummy!“, that I’m finally catching onto.



The Methodology before Theory? The search for my Research Question!

This post is going to start with a story.  In 1993, as a newbie field archaeologist, I had as most do, a horrible time differentiating between soil or root stains and post holes.  I can’t tell you how many post holes I mangled, much to the dissatisfaction of my field supervisor.

Sweating every soil stain, I began to wonder if there was a way to visualize in 3D, what we assumed to be post holes to determine if they actually belonged to the archaeological landscape.  A sort of, post hole detection methodology.  More than that, it would give stakeholders an ability to visualize an actual structure as opposed to trying to explain to the client that these stains were important!

It was that frustration which drove me to understanding how to create 3D objects and eventually into a long career in the animation and VFX industry.  Part of that journey included Sheridan College, which I was extremely lucky to attend in the early 90’s at the beginning of the second wave of artistic talent and immense technology.

However, it was my very first job in the industry which has now framed my research methodology to build interactive, real-time 3D Longhouses.  Kim Davidson, an industry legend and founder of Toronto based Side Effects Software, an animation production software company, produced and continues to build upon a procedural animation tool set called Houdini.

In Houdini, any function, from model building to texture map making to compositing or animating can be done procedurally.  What this actually means is that every function has a node or parameter that is never locked and as such, can be reworked at any point in the creation of a model, animation or VFX shot.  All changes “ripple” down the nodal network allowing the user ultimate flexibility without having to recreate or trace their steps again.

Using this methodology, I can theoretically build a Longhouse App with total flexibility allowing for regional, cultural, societal, historical variables in Longhouse construction to be “mashed up”.  This technique can then free stakeholders of all types; archaeologists, descendent groups, researchers and the public to build and more importantly experiment with how Longhouses may have looked and uniquely how one can then interactively engage within that space, always refining based on the individuals own unique perspective.

Procedural Arc Research Tool

This theoretical procedural network simplistically outlines how we can start with a basic field survey of post holes and “build” or more precisely “rebuild” one of multiple variations of Longhouses based on any infinite amount of parameters.

Prototypes for visualizing and manipulating 3D Longhouses constructed from site maps have already proven successful and the next stage will be deployment against a set of research questions.

One such question comes from the Droulers site on the boarder of Quebec and Ontario.  Claude Chapdelaine from the University of Montreal has been researching the site for many years.  The archaeological landscape has yielded some interesting questions regarding Longhouse construction, in particular, how massive structures could be built in and on totally rocky/stoney terrain.

Essentially, there are no soil stains to determine “what” the Longhouses might have looked like.  There are however hearths that have been discovered.  So, is it possible to 3D visualize the dimensions of the Longhouses through hearth positioning only?  The archaeological landscape will quite literally guide and frame my research.

It’s important to note that I’m not simply attempting to reconstruct Longhouses in 3D.  I’m attempting to provide the tools necessary to allow non-archaeologists and archaeologists alike to play with the historical and current data in visual 3D form.  I also hope this technique can be done in both real-time and in stereoscopic 3D, by providing a virtual interface for users to not only build in 3D space but be immersed within it.

As always, any thoughts, opinions, leads to other research or examples of other sites are greatly appreciated!