December 27, 2011
After much planning and beer consumption, InfoCamp PDX is a reality. On Febuary 4, 2012, InfoGeeks from around the Pacific Northwest will converge to talk about information: what it is and how we find it, use it, structure it, design it — really whatever we want, because it’s an unconference.
Hope to see you there!
February 28, 2011
My worlds collide! I just caught up with the current issue of the Journal of Information Architecture — and it’s all about semantics and structured data. As an information architect who has never wireframed a website, I’m excited to see the IA community dive into the world of structured data and ontology. It’s great to see the likes of enterprise information architects and master data management practioners add some semantic tools to their toolkits.
August 11, 2010
I'm almost afraid to click…
August 5, 2010
Here’s a fun catalog of some of the many ways our cognitive processes trip us up. I’ve committed at least 37 of them today alone. How about you?
May 27, 2010
An ontology is a description of the entities in an area of interest, or domain, the attributes of those entities, and the relationships between them. This description is both formal, meaning it can be acted on by a computer, and human-readable.
One of the major strengths of an ontology is that it lets us organize information in terms of the problem we’re trying to solve, not the data we’re collecting. While data remains important in an ontology-based information system, it is structured according to the concepts of the domain, not the table structure of the database it’s stored in. This is important for two reasons: we can formalize relationships between pieces of data that would only be hinted at by foreign keys and naming conventions in a database. More importantly, it frees us to think about our problem space in terms of concepts and abstraction, not data. To take a model-driven approach instead of a data-driven one. Humans think in terms of models, not data. It is models that give meaning to data. As we deal with ever increasing volumes of data, it is models that help us identify what’s important, organize it, hypothesize about it, and discover connections between disparate data.
April 18, 2010
Last week Google began including results from Twitter on their results page. The tweets are accessed through a timeline with a handle you can grab to scroll through results over time.This is incredibly cool. At the same time, I can’t help noticing that while it presents a lot of information, it’s not immediately clear how to construct meaning from it. Google talks about using the results to “’replay’ what people were saying publicly about a topic on Twitter.” That seems to describe the usage model pretty accurately: search, scroll through all results, and make of them what you will. It seems to lend itself to historical or anthropological purposes, rather than traditional search. Here’s some sample tweets returned by searching for “Obama“: This isn’t so great if you’re interested in policy, but highly interesting if you’re investigating the teaparty movement. Ditto with this result:
Up until now, if you were researching a group of people, you would search on the group’s name. With tweets, you really want to search on the topics the group publishes about. So this could change the average information consumer’s search strategies.The Google Blog suggests this search to “relive” Shaun White’s Olympic glory. The idea of reliving it is interesting, because what’s being relived is not the actual moment, but the response of thousands of people to that moment. (And, like everything else, it could really use semantic search to filter out stuff like this: )
To sum up: Twitter on Google is very cool. It will change the way we search, but right now not even Google knows a good way to use it. It dumps a huge amount of raw info on the searcher, and leaves it the individual to navigate, sift, and construct meaning out of it.But, it was only announced this week, and clever people are certainly already at work on innovative ways to build meaning out of the firehose that is the global tweetstream. A semantic search layer? Sentiment analysis? There’s a lot of possibility here. By the time this posts, Google will probably have rolled this out worldwide. Have you tried it? What do you think?