Removing the Stench from Mobile Information
Standing in Amsterdam in front of the Dam, I was taking in the remnants of a memorial to Theodore van Gogh (including poetry to Theo). While absorbing what was in front of me, I had a couple people ask me what the flowers and sayings were about. I roughly explained the street murder of Theo van Gogh.
While I was at the Design Engaged conference listening to presentations about mobile information and location-based information I thought a lot about the moment at the Dam. I thought about adding information to the Dam in an electronic means. If one were standing at the Dam you could get a history of the Dam placed by the City of Amsterdam or a historical society. You could get a timeline of memorials and major events at the Dam. You could also get every human annotation.
Would we want every annotation? That question kept running reoccurring and still does. How would one dig through all the digital markings? The scent of information could become the "stench of information" very quickly. Would all messages even be friendly, would they contain viruses? Locations would need their own Google search to find the relevant pieces of information. This would all be done on a mobile phone, those lovely creatures with their still developing processors.
As we move to a world where we can access information by location and in some cases access the information by short range radio signals or touching our devices there needs to be an easy to accept these messages. The messaging needs some predictive understanding on our mobiles or some preparsing of content and messaging done remotely (more on remote access farther down).
If was are going to have some patterning tools built in our mobiles what information would they need to base predictions? It seems the pieces that could make it work are based on trust, value, context, where, time, action, and message pattern. Some of this predictive nature will need some processing power on the mobile or a connection to a service that can provide the muscle to predict based on the following metadata assets of the message.
Trust is based on who left the message and whether you know this person or not. If the person is known do you trust them? This could need an ensured name identification, which could be mobile number, their tagging name crossed with some sort of key that proves the identity, or some combination of known and secure metadata items. It would also be good to have a means to identify the contributor as the (or an) official maintainer of the location (a museum curator annotating galleries in a large museum is one instance). Some trusted social tool could do some predicting of the person's worthiness to us also. The social tools would have to be better than most of today's variants of social networking tools as they do not have the capability for us to have a close friend, but not really like or trust their circle(s) of friends. It would be a good first pass to go through our own list of trusted people and accept a message left by any one of these people. Based on our liking or disliking of the message a rating would be associated with this person to be used over time.
Value is a measure of the worthiness of the information, normally based on the source of the message. Should the person who left the message have a high ranking of content value it could be predicted that the message before us is of high value. If these are message that have been reviews of restaurants and we have liked RacerX previous reviews we found in five other cities and they just gave the restaurant we are in front of a solid review that meets our interests. Does RacerX have all the same interests?
Context is a difficult predictive pattern as there are many contextual elements such as mood, weather, what the information relates to (restaurant reviews, movie reviews, tour recommendations, etc.). Can we set our mood and the weather when predicting our interest in a message. Is our mood always the same in certain locations?
Where we are is more important than location. Yes, do we know where we are? Are we lost? Are we comfortable where we are? These are important questions that may help be a predictor that are somewhat based on our location. Or location is the physical space we occupy, but how we feel about that spot or what is around us at that spot may trigger our desire to not accept a location-based message. Some of us feel very comfortable and grounded in any Chinatown anywhere around the globe and we seek them out in any new city. Knowing that we are in or bordering on a red-light district may trigger a predictive nature that would turn off all location-based messages. Again these are all personal to us and our preferences. Do our preferences stay constant over time?
Time has two variables on two planes. The first plane is our own time variables while the other relates to the time of the messages. One variable is the current moment and the other is historical time series. The current moment may be important to us if it is early morning and we enjoy exploring in the early morning and want to receive information that will augment our explorative nature. Current messages may be more important than historical messages to us. The other variable of historical time and how we treat the past. Some of us want all of our information to be of equal value, while others will want the most current decisions to have a stronger weight so that new events can keep information flowing that is most attune to our current interests and desires. We may have received a virus from one of our recent messages and want to change our patterns of acceptance to reflect our new cautionary nature. We may want to limit how far back we want to read messages.
Action is a very important variable to follow when the possibility of malicious code can damage our mobile or the information we have stored in the mobile or associated with that mobile. Is the item we are about to receive trigger some action on our device or is is a static docile message. Do we want to load active messages into a sandbox on our mobile so the could not infect anything else? Or, do we want to accept the active messages if they meet certain other criteria.
Lastly, message pattern involved the actual content of the message and would predict if we would want to read the information if it is identical or similar to other messages, think attention.xml. If the Dam has 350 messages similar to "I am standing at the Dam" I think we may want to limit that to ones that meet some other criteria or to just one, if we had the option. Do we have predictors that are based on the language patterns in messages? Does our circle of trusted message writers always have the same spellings for certain wordz?
All of these variables could lead to a tight predictive pattern that eases the information that we access. The big question is how is all of this built into a predictive system that works for us the moment we get our mobile device and start using the predictive services? Do we have a questionnaire we fill out that creates our initial settings? Will new phones have ranking buttons for messages and calls (nice to rank calls we received so that our mobile would put certain calls directly into voice mail) so it is an easier interface to set our preferences and patterns.
Getting back to remote access to location-based information seems, for me, to provide some excellent benefits. There are two benefits I see related to setting our predictive patterns. The first is remote access to information could be done through a more interactive device than our mobile. Reading and ranking information from a desktop on a network or a laptop on WiFi could allow us to get through more information more quickly. The second benefit is helping us plan and learn from the location-based information prior to our going to that location so we could absorb the surroundings, like a museum or important architecture, with minimal local interaction with the information. Just think if we could have had our predictive service parse through 350 messages that are located at the Dam and we previews the messages remotely and flagged four that could have interest to us while we are standing at the Dam. That could be the sweet smell of information.
Comments are closed.