My daily readings 02/26/2012

  • tags: information Knowledge connection devonThink

    • I recommend Take Control of Getting Started with DEVONthink 2. I just dove in with what seemed a logical structure of folders and went to town. It’s extremely easy to dump in information via a copious variety of convenient means. Great searching and the “See Also” feature is brilliant for finding unexpected connections.
  • Collect, Connect, Create

    tags: information management Knowledge thinking

      • Nerds are fucking funny. It’s another point from The Nerd Handbook that I suggest is related to the relevancy engine, but I never explain. Let’s try now.


        The processing of relevancy has three steps and it’s the third where the magic happens:



        1. Collect the Relevant
        2. Research and Index if necessary
        3. Connect the Relevant in Efficient and Entertaining Ways


        So, how is The Funny created in this flow? It’s a big question: what is funny? I’d say there are two big classifications of funny. There are jokes and there’s wit. Jokes are memorized comedy retold with moxy. Wit is original comedy created in real-time and delivered with precise timing. Nerds are fucking witty because they connect the relevant to the present quickly and in clever ways.

  • tags: Note Knowledge

    • We are currently using Microsoft SharePoint sevices 2003 at my group to manage our knowledge base, you know, all our internal documents about formal and less formal procedures and tasks, but it is very suboptimal and difficult to search. How do you handle that kind of information to be easy to produce and, above all, easy to find?

      Thanks for all your responses.

    • The Atlassion products (Confluence and Jira) were awesome at my last startup. I’m using TikiWiki right now for something similar because it fits my budget ($0).
    • We use a MediaWiki install for a lot of general knowledge, and for project-specific stuff we throw it in our Basecamp.


  • tags: information Knowledge discovery collect search

      • Services will be get better and better at finding what you want based on a deeper understanding of:


        • What you’re like – as measured by your behavioral profile and trends, including past searches, social connections, browsing history, etc.
        • Who you’re like – search engines will be able to target results based on how you fit into groups of people with similar interests, tastes, and other traits, as collaborative filtering algorithms and the datasets they have at their disposal improve
        • Where you are – as measured by geolocation and other sensors which will increasingly be able to know your altitude, orientation, local temperature, etc.
        • How you feel – as measured by device cameras and mics, which will be able to discern your mood and reactions by your facial expressions and vocal tones, and increasingly other sensors which can measure changes in body temperature, etc.
      • Content

        • What it means – as allowed for by increasingly structured data and improved artificial intelligence, similar content will be clustered together into category hierarchies, allowing search to be more a quick process of selection and elimination, instead of a long exercise in parsing and clicking
        • Where it’s been – ubiquitous and standardized content metadata will allow seamless traceability of the path content has taken, and how it’s changed along the way, which will help identify it’s level of relevancy to other content

        Services will also continue to improve input and output interfaces for carrying out a search, as well as presenting and managing results.

      • Search

        • Conceptual inputs – as semantic metadata on the web improves, faceted searching and filtering by selecting combinations of structured topics, such as people, places, events, things, and ideas will be increasingly possible
        • Audible inputs – already seen in emerging services like Google Voice Actions, Siri, and Shazam, you will be able to use your voice, a clip from a song, and other audio sources as a way to run a search and identify content
        • Visual inputs – already seen in emerging services like Google Goggles, Google Similar Images, and, you will be able to use images and videos, as a way to search for similar content
      • Results

        • Filtering – will enable rapidly narrowing down results, smoothly focusing in on relevant content, removing irrelevant content from view. Microsoft’s Pivot is good example of how this can work and how powerful this can be
        • Visualizing – richer interfaces for presenting content results, such as result data populated into dynamically generated, interactive infographics or visualizers, will enable content to be more naturally consumed and understood
    • The future of search is no search. It is structured knowledge. 

      Having knowledge, rather than found information, requires some political and legal and cultural changes. We think we live in an information society, but most of the real information is hidden and nobody’s required to share it. The stuff we share is mostly second or third hand information, i.e. what somebody thought about something that they heard happened.

      Imagine you had a right to get direct access to the real information, rather than a retold story about it. Imagine that there were tools to facilitate that access. Ask a precise question, get the precise answer right away. That’s the future of search

  • tags: information Knowledge discovery collect

    • It’s an over-generalization, but the message it conveys is accurate. The minority will contribute, more will share, and majority will read. In reviews on retail sites you will find anywhere from 1% up to 30% of customers who buy will write a review. In contrast. on Wikipedia, it’s less than 1% that write content. Regardless of the veracity of the stat, the point to take away is that knowing it’s a minority who will contribute and share — and knowing those numbers don’t have to be this low in every case — you should build strategies to bring those numbers up, and create participation where the content created is valuable to the 90% of readers. BTW…I’d assert the 90% number is wrong too because you have to assume contributors and sharers read this content as well. 100%.
    • I believe that Bradley Horowitz first popularized this back in 2006:…

      He presented the following diagram, using the example of Yahoo Groups:

      I had always thought it was based on hard data from Groups, but re-reading it now I’m unsure if it is his impression or hard statistical data.

    • Anecdotal evidence from crowdsourcing style projects I’ve worked on tend to support the basic principle (if not the exact ratios). The vast majority of the work on projects I have been involved with ends up being performed by a tiny subset of highly active users.
    • Clay Shirky presented this long tail graph in his TED talk “Institutions vs collaboration” analysing contributions to Flickr. The same trend was show cased by Dries Buytaert during Drupalcon Chicago (Marc ’11) analysing community contributions to the making  of Drupal 7. The same trend shows up in all voluntary / community based projects: 1-10% will contribute 70-90% of your content. The very important message of Clay Shirky is that the collaborative platforms / social media lower the barrier and the cost of participation so much that it will empower even those that want just to make a very small contribution ( i guess the “like” is the smallest) to participate … Hence the graph with the very long tail of small contributors in most social media and other online platforms ( Quora is the same )

Posted from Diigo. The rest of my favorite links are here.

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