We’ve known for years that Google uses classification in its search algorithms and in its ancillary services but today Google finally came clean with its new Knowledge Graph service “With the Knowledge Graph, Google can better understand your query, so we can summarize relevant content around that topic, including key facts you’re likely to need for that particular thing. For example, if you’re looking for Marie Curie, you’ll see when she was born and died, but you’ll also get details on her education and scientific discoveries.” Is that taxonomy work or is that taxonomy work?

Sitting behind Knowledge Graph is a 500 million entity ontology, with 3.5 billion defined relationships and attributes – though the words ontology or taxonomy are never used. Exciting in itself, as it evidently exploits the growing maturity of the semantic web and linked data, and the intelligence you can extract from billions of search patterns, to enhance taxonomy work in unprecedented ways. But also a major vindication for the faithful few who have remained steadfast in their belief in taxonomy over magic. BTW, I’m hoping to explore some of these “taxonomy beyond the enterprise” themes in a keynote at Taxonomy Bootcamp later this year. The times they are a changing!

We’ve known for years that Google uses classification in its search algorithms and in its ancillary services but today Google finally came clean with its new Knowledge Graph service “With the Knowledge Graph, Google can better understand your query, so we can summarize relevant content around that topic, including key facts you’re likely to need for that particular thing. For example, if you’re looking for Marie Curie, you’ll see when she was born and died, but you’ll also get details on her education and scientific discoveries.” Is that taxonomy work or is that taxonomy work?

Sitting behind Knowledge Graph is a 500 million entity ontology, with 3.5 billion defined relationships and attributes – though the words ontology or taxonomy are never used. Exciting in itself, as it evidently exploits the growing maturity of the semantic web and linked data, and the intelligence you can extract from billions of search patterns, to enhance taxonomy work in unprecedented ways. But also a major vindication for the faithful few who have remained steadfast in their belief in taxonomy over magic. BTW, I’m hoping to explore some of these “taxonomy beyond the enterprise” themes in a keynote at Taxonomy Bootcamp later this year. The times they are a changing!

Patrick’s taxonomy development infographic has sparked off a little friendly competition in the office. The infographic you see above is my attempt at explaining the different pieces of an intranet puzzle that KM practitioners may have to deal with, and how they all fit together.

This is the link to the pdf version – Intranet_Poster.pdf. Note that it is formatted for A2 size and you will need to set your printer to print within paper size for smaller sizes.

I would like to commend Patrick for his sportsmanship, for even though my poster is evidently better than his, it did not hold him back from providing some of the explanations that you see on the poster.

Here is a poster design I’ve been working on for a while – it summarises the empirical, evidence based taxonomy development process we recommend.

This is the link to an A4 pdf version.
This is the link to an A3 pdf version.

We’re going to look at costs/prices for printing this on high quality poster paper and shipping it if there’s a demand. Let us know!

Here is a poster design I’ve been working on for a while – it summarises the empirical, evidence based taxonomy development process we recommend.

This is the link to an A4 pdf version.
This is the link to an A3 pdf version.

We’re going to look at costs/prices for printing this on high quality poster paper and shipping it if there’s a demand. Let us know!

Since a few months there is a big trend on the web: visualisation of data and information. It is definitely not a new trend, though it is accelerating fast; new tools like visua.ly have been launched and Pinterest has developed to the third most popular social sharing tool in 2012. Why is this the trend happening, and what can we learn from it in the context of knowledge sharing and social collaboration?

In our current world two things are happening: we are exposed to much more data and information; and we are overwhelmed with these with an increasing speed. Pictures, photos, illustrations, visualisations are not only eye-catching but also help us to grasp the content much faster. In the past, overviews of news have been a simple list of headlines. Illustrations help readers to make quick (not necessarily right) decisions to jump to an article or not. Many tools take advantage of that and two show-cases are Pulse News and Google Currents.

What does this mean for knowledge management and social collaboration?

Myself, I have started using Stacks on delicious.com; I chose this tool mainly because I already use Delicious for managing my bookmarks and it’s neatly integrated. The stacks display the links in two columns with a paragraph of text plus a photo if available; actually, it looks more like a newspaper than a boring list of links. Please find here an example I have created: the User Adoption stack. This design is much more attractive for our target audience and they will be more willing to continue reading; that is the reason why we should create collections in this way.

Some time back Maish wrote and article about designing collections for the web and I really like the four objectives of collections mentioned: make it easy to contribute, easy to find items; allow grouping of existing and the discovery of new items. Illustrations help especially with the finding and the discovery of news. The people’s visual eye will quickly respond to the items they are most interested in; even before they start reading the headline itself. On the other hand, categorisation help to achieve the other two objectives, contributing and grouping.

Via the status updates, users of social collaboration tools can quickly share links to interesting articles, documents and other resources. This is great sharing and a source of a wealth of interesting information. Though, just a few weeks later it is surprisingly difficult to retrieve these links which could be for example very valuable for people joining a team. Next to the news feed, we should also focus on creating collections of links that are relevant for a certain topic; these collections could be “wiki pages” of links; “wiki” in the sense that a group of people are curating the content and maintaining the links. The links in these collections can be anything from intranet pages, policies, discussion threads, manuals, presentations, people profiles and additional resources from the public web like articles, online tools, etc. To make these link collections attractive, we should use tools that present them in a useful design and make (re-)discovery simple and fast.

In which scenarios could we use these visual link collections? Here some ideas:

• at the start of a project to collect benchmarks and lessons learnt
• when doing research for a new concept or a presentation; and these collections could be shared with the target audience
• company and team introductions referring to to the most important resources
• collections supporting training curricula for specific roles
• publishing of news which is aggregated from various resources
• collections of content for a specific topic which can be shared with customers and employees

Try out one of the mentioned tools and let me know how you would use visual collections.

“At any given technology conference, you will find the following types:

• People with chips on their shoulders about being marginalized by the new trend.
• Long-ignored people who suddenly find that they’ve turned into stars, blinking in the spotlight.
• People who feel under-appreciated and powerless.
• People who cannot believe how much power they suddenly have.
• People who secretly feel like fakes and are feeling either gleeful or ashamed about it.
• People who are cleverly switching out their titles from the last hyped fad for the closest one they can find in the new one.
• People upset that other people are taking credit for their old wine by putting it into new bottles.
• Older people insisting nothing has changed (read: “therefore I am still the expert” ).
• Younger people insisting everything has changed (read “the old fogeys know nothing; hire me instead” ).
• People excited by anything new and shiny, whether or not they understand it.
• Jaded people on paid-for junkets.
• Uber-sociable types for whom it is all one big party.”

Underneath this is another emerging trend. We know that social media is being leveraged as a source of data for marketing and market analysis. This case illustrates how powerful it can be in the use of large scale data for new knowledge creation. Crucially, it cannot do this on its own – the formal world of research and the informal world of social media exchanges need to connect. Helping to span these boundaries is where knowledge organization tools like taxonomies play an essential role.