LP Login

Think Big. Move Fast.

Through Techcrunch, I saw the video “Information R/evolution” embedded below (5minutes, worth watching):

The video’s key message is that when information is stored digitally instead of in a material world, then our assumptions about how to get to information, and how information gets to us, are substantially disrupted, allowing for high quality (and quantity) user generated, organized, curated and disseminated content.

It’s an entertaining video and spot on. However, I think it glosses over one key point about make information truly useful. User generated content, often unstructured, can be very hard to navigate and search through. Adding structure makes the data vastly more meaningful.

Search engines are the best example of how adding structure (a search index) to an unstructured data set (the list of all websites) makes the dataset more useful. Whether that structure is established by link popularity (as Google and all modern search engines do) or by human editors (as Yahoo started out) affects the size and quality of the structure, but even a rudimentary structure built by humans is better than no structure at all.

Social networks are another great example of how adding structure (a social graph) to an unstructured data set (personal home pages) improves the data’s usefulness. There were plenty of successful examples of personal home pages and people directories in the late 90s , including Tripod and AOL’s People Connect, but none of them had the high levels of user engagement that MySpace, Facebook, Bebo and the current generation of social networks have.

One of the key themes of Web 2.0 has been the rise of user generated content. Often this content has been largely unstructured. Unstructured data is hard to navigate by search – you need to rely on the text, and that can be misleading.

Take one of my favorite websites, Yelp, as an example. If I do a search for diabetes near 94111, I get one relevant result (i.e. a doctor) in the top 10 – the rest of the results range from tattoo parlors to ice cream parlors, auto repair to sake stores. All contain the word “diabetes” in a review, some humorously, others incidentally.

This isn’t a one off either; try baseball mitt, TV repair or shotgun. In every case, the search terms show up in the text of the review, which is the best that you can hope for with unstructured data.

Recently I’ve started to become intrigued in companies who are adding structure to unstructured data. There seem to be at least three broad approaches to this problem:

1. User generated structure
2. Inferring structure from knowledge of the domain
3. Inferring structure from user behavior.

I’m not smart enough to know if this is the semantic web or web 3.0, or even if the labels are meaningful. But I do know that finding ways to add or infer structure from data is going to improve the user experience, and that is always something worth watching for.

I’m going to explore the three broad approaches that I’ve seen in subsequent posts, but would love to hear reader’s thoughts on this topic.

I’ve found this post on the structured web by Alex Iskold to be very helpful in thinking about this topic.

20 Responses to Meaning = Data + Structure

Leave a Reply

Your email address will not be published.

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>