Living Life Like It’s the End

I got into a car accident yesterday. I was driving in the middle lane of a three-lane freeway, and an SUV snuck up to my left and changed into my lane without looking. I swerved to get out of the way, swerved again to try and regain control, spun out, crashed into the median, and watched helplessly as the oncoming traffic headed straight toward me.

Remarkably, neither I nor my friend Pete, who was in the car with me, were hurt. I find it miraculous that I am alive and unharmed. If any number of tiny things had turned out differently, I very well could be dead.

I shared this story this morning with my team at Groupaya, along with a reminder to live in the moment. In response, Kristin Cobble shared some wise words from her friend, Vanda Marlow. Vanda noted that we often go through life as if we are in the middle of our lives, but that we actually may be close to the end. We have no way of knowing.

My accident definitely woke me up to this, but Vanda’s words made me wonder: How would living our lives this way (as if we were near the end rather than the middle) affect our desire to do long-term projects?

For example, my friend, Matthew, was telling me the other day that Square has a 5,000 year vision (about the amount of time that money has existed). If you have a 5,000-year vision, you have no chance of seeing it through (ignoring, for a moment, my nanotechnology friends who believe that we are pretty close to unlocking the secrets of immortality). So why would anyone ever pursue anything like this?

I have two answers to this question. First, there’s the old saw about the journey being more important than the destination. I believe it. The destination can be valuable in shaping your journey, but ultimately, if the journey itself does not bring you alive, it’s probably not worth it.

I remember reading a story about how famed director, Robert Altman, was planning on making a new movie when he died. He was in his 80s and had leukemia. The chances of him finishing that movie were essentially zero, and he died before he even got started. But it didn’t matter to him. He loved making movies, and every step of that journey — whether or not he got to finish — brought him alive.

Second, thinking about impact beyond the length of your life does not render your actions futile. It simply requires that you think differently. You may not be able to live forever (again, nanotechnology not withstanding), but the impact that you have on other people will reverberate long past your own life.

In a strange way, whether or not you are a long-term or short-term thinker, the notion of living your life as if you’re near the end results in the same conclusion: Honor and nurture your relationships. They’re the things that matter most.

Talking Technology

Todd Johnston posted an outstanding summary of our informal session this past Saturday. He mentioned our first exercise, which was to have Todd, Gail Taylor, and Tiffany Von Emmel explain how email worked to Matthew O’Connor and myself, who had had sudden bouts of amnesia. Todd wrote, “This exercise, as you may imagine, did a lot to uncover assumptions, vantage points and metaphors we use to shape our understanding.”    (LX9)

The point of the exercise was two-fold. First, we wanted the group to have a better understanding of how the Internet worked. Second, rather than tell them how it worked, we wanted them to figure it out by thinking through the problem. Most of us have the mental tools to understand technology; we just choose not to use them. We wanted to get them to use them.    (LXA)

What was interesting about the exercise was that they did an excellent job of drawing a basic conceptual picture. However, when Matthew and I started asking probing questions to help fill in the gaps, they abandoned their mental models and started reverting to buzzwords. They mentioned things like packets and algorithms and server farms, all of which demonstrated knowledge of Internet lingo, but none of which was necessary to explain how email worked.    (LXB)

Matthew pointed out that techies often do the same thing. When confronted with basic questions about technology, they often start throwing around concepts and language that aren’t critical to the core question. In these cases, they do this because they’re unaware of the other party’s mental models and are feeling around for context.    (LXC)

Why would non-techies do the same thing? In this particular case, it was for the exact same reason. Even though Matthew and I were playing dumb, they knew that we knew the answers. When we started asking questions, they abandoned their model and started feeling around for the answers we might be looking for, hence the lingo.    (LXD)

When one person has knowledge that the other person doesn’t have, that often results in a power relationship, and power relationships affect how people behave. What makes this relationship dangerous is when people assume that this knowledge is somehow sacred and unattainable. Many non-technical people are guilty of this. It’s evident when people preface their statements, “I’m not a techie,” as if that makes them incapable of understanding technology. It’s an attitude problem that stems from fear.    (LXE)

The important thing is that everyone is capable of understanding technology. Don’t let those supposedly in the know bully you away from being confident in what you understand and what you don’t understand.    (LXF)

On a separate note, Todd also describes Finding Your Hey, an exercise that the band, Phish often performs. Todd first told me this story two years ago, and I dutifully blogged about it, but I didn’t know what it was called, and I didn’t know the exact quote. It’s a wonderful story.    (LXG)

Collaboration as a System

I spent this past Saturday in Sebastopol “tutoring” Gail Taylor, Todd Johnston, and Tiffany Von Emmel on online Collaborative Tools. I lured Matthew O’Connor into helping by boasting of Gail, Todd, and Tiffany’s deep thinking about and practice of collaboration.    (LVC)

One of our exercises was to walk through all of our respective digital workspaces, demonstrating how we read and wrote email, and worked with online tools. I had gotten some idea of how Matthew worked when we paired at the Wikithon earlier this month, but I was still blown away by his walkthrough. He’s really thought deeply about his work processes and has optimized his online workspace accordingly.    (LVD)

Matthew expressed surprise that he was the only one who had done this, especially since I had proclaimed these folks to be gurus. I didn’t have a chance to discuss this with him on Saturday, so I thought I’d post some thoughts about that here.    (LVE)

To be good at collaboration, you have to treat it as a system. That system includes things like communication, community, Knowledge Management, learning, and leadership.    (LVF)

Most Collaborative Tools companies are either in the communication or the Knowledge Management business. They’re usually selling pipes, PIMs, or document management tools. All of those things have something to do with collaboration, but they are not in and of themselves collaboration. Then again, no tools are. A hammer is a tool for hammering, but it is not itself hammering.    (LVG)

When I think about High-Performance Collaboration, I envision groups with excellent Group Information Hygiene. Ideally, you’d also like every member of the group to have outstanding Personal Information Hygiene (like Matthew), but it’s not a prerequisite. You’d like to see every member to be past a certain threshold of competence for all aspects of the system, but I don’t think it’s necessary for everyone to be great at all those things. On a great basketball team, you’d like everyone to be in good shape and have good fundamentals, but some players are going to be superior shooters while others will be great rebounders. It’s not necessary, nor realistic, nor possibly desirable to have 12 Magic Johnsons on a team.    (LVH)

Implicit in my One Small Change post is that there is no one thing. I can think of a number of small, concrete changes that could result in significant improvements in collaboration. This is one of the main reasons why Pattern Languages — collections of named, concrete patterns — are fundamental to The Blue Oxen Way.    (LVI)

Personal Information Hygiene is a critical pattern, because it fosters trust. My advice to groups with trust issues would be to eschew squishy exercises and look at people’s Personal Information Hygiene instead. However, past a certain level, I don’t see great Personal Information Hygiene as being the primary hallmark of a great collaborator.    (LVJ)

Wiki Analytics at the Wikithon

I got to put on my hacker hat for a day (a very rare occurrence for me these days) last Wednesday at the Wikithon. After trolling around for ideas, I decided to work on Wiki Analytics with Matthew O’Connor. We ended up dominating the competition and winning the contest for best hack. (So what if there were only two teams eligible for two prizes?)    (LRI)

https://i1.wp.com/farm1.static.flickr.com/150/386792217_6d63faa621_m.jpg?w=700    (LRJ)

Our driving question was: How can we measure the health of a Wiki? I don’t think there is one best way to use a Wiki, but there might only be three or four. If we can start teasing out patterns of Wiki usage, we can better understand how people collaborate with Wikis, which will help us better facilitate Wiki communities and improve Wiki software. Our goal was to tease out the patterns.    (LRK)

We used data from 266 public Socialtext workspaces and Socialtext‘s internal corporate workspace. You can read the details of our brainstorming and work on the Socialtext STOSS Wiki. Our approach was to simplify our tasks so that we could have something to show at the end of the day. It was decidedly practical, but it also reflected a deeper philosophy about Wiki Analytics. Start simple and evolve. You can learn interesting things from even simple measurements.    (LRL)

Results    (LRM)

We chose to focus on two types of analysis: page name and graph (link) analysis. I hacked on the former; Matthew on the latter.    (LRN)

Frequent followers of this blog have heard me say it before: Link As You Think is what makes Wikis powerful. The better your page names, the more interlinked your repository will be as you Link As You Think. In order to see if I could measure “good” page names, I looked at three things:    (LRO)

  • Length    (LRP)
  • Number of tokens (words)    (LRQ)
  • Number of non-alphanumeric characters    (LRR)

The hypotheses are straightforward. Shorter names are better. Names with fewer tokens (words) are better. Names without non-alphanumeric characters are better. (This last hypothesis is complicated by internationalization.)    (LRS)

You can read the results of my analysis. The workspaces on the index page are ordered largest to smallest. The top two workspaces are full of spam and can be safely ignored. The numbers on the index page are buggy; click through to the individual pages to see the correct numbers.    (LRT)

Matthew studied the graph characteristics of the Wikis, specifically:    (LRU)

  • Number of links (forward and back) versus number of pages    (LRV)
  • Number of islands (clusters of pages that are strongly connected to each other) and their sizes (number of pages on an island)    (LRW)

Islands of one are orphan pages (not linked to anywhere) and are undesirable. Large islands are better (or at least more interesting) than small ones.    (LRX)

You can view Matthew’s results on his site.    (LRY)

Analysis    (LRZ)

To give you an idea of what the stats mean, let’s look at four Wikis:    (LS0)

The mean number of characters and number of tokens for page names on each Wiki were:    (LS5)

  • 21.3 / 3.1 (stoss)    (LS6)
  • 18.6 / 2.4 (speakers)    (LS7)
  • 17.4 / 1.7 (st-rest-docs)    (LS8)
  • 39.3 / 6.7 (ivrwiki)    (LS9)

On the surface, the two Wikis in the middle — stoss and speakers — seem to have hit the sweet spot for page names: between two to three words per name. Since stoss is meant to be a collaborative workspace for a larger community, this seems to be a healthy number. The speakers Wiki is a repository of potential speakers. Since the majority of pages consists of people’s names, the numbers (two, sometimes three words in a page name) make sense.    (LSA)

The remaining two Wikis diverge enough from this minute data set that we can infer some different patterns of usage. st-rest-docs documents Socialtext‘s REST API, so there are a lot of one word page names representing method names. Even though the average number of tokens is smaller, the average name length is comparable to the two Wikis in the middle. This also makes sense, given that the methods in a REST API are actually URI paths, which can get somewhat long.    (LSB)

On the surface, ivrwiki seems to exhibit the classic signs of a newbie dumping ground, with page names that are too long to be useful. However, if you dig deeper, you can see that that’s not the case. The standard deviation of number of tokens is quite large (4.2), indicating a flat distribution curve. In other words, while there are a lot of long names, there are also a lot of short names. If you dig even further, you’ll see that the community is using the Wiki as a question repository, and questions naturally have lots of words. Additionally, there seems to be a lot of more traditionally “Wiki-like” behavior on that Wiki.    (LSC)

This was no accident. The reason I’m showcasing ivrwiki is that Matthew identified it as an “interesting” Wiki from his graph analysis. Look at the numbers. There are three sizes of islands: 19 of one page, one of 16 pages, and one of 353 pages! That’s one big island! It indicates a fairly tight set of linkages across the majority of the pages on a Wiki. Dig a bit deeper, and you can see the hub of the cluster: the Knowledge Base Index page. It links to every page in the knowledge base, and every page in the knowledge base links back to this page.    (LSD)

The st-rest-docs Wiki exhibits similar behavior — one big island of 81 pages. This makes sense, given that this Wiki represents documentation, which is structured in a similar way to the ivrwiki knowledge base.    (LSE)

The stoss Wiki is the most Wiki-like of the four when you dig into the graph analysis. There are five sizes of islands, the largest containing 10 pages. The distribution is fairly regular — based on my guess of what “regular” should be, at least. To really get a sense of what “regular” should be, we’ll need to identify several Wikis that we consider to be “Wiki-like,” and examine those numbers.    (LSF)

Finally, look at the numbers for the speaker Wiki. The numbers are in reverse of the other Wikis. There is basically no clustering; all of the pages consist of islands in and of themselves. At first glance, this is surprising. You would expect it to look somewhat like ivrwiki and st-rest-docs. The reason for the lack of clustering is that this Wiki relies on Socialtext‘s tagging interface for navigation. Tags could be treated as a type of link, but we don’t treat them that way in our analysis.    (LSG)

Thoughts    (LSH)

As with any simplified analysis, there are always caveats. A lot of them are specific to the Wiki implementation. For example, several people at Socialtext use the stoss Wiki as a blog, which creates long page names and thus skews the statistics. Other Wikis may be similar to the speakers Wiki in that they use tags as navigational links.    (LSI)

There’s an open question as to whether or not to consider a Wiki a directed graph or not. We chose the former, but you can make a good argument that the Socialtext Wiki acts as a non-directed graph, or at least a bidirectional one, because Backlinks are displayed on the page itself. The same holds true with any other Wiki depending on the navigational context. If I start at the home page and start navigating around, I can often use the browser back button to go back, or at worst, I can click on “Backlinks” to figure out the context.    (LSJ)

I’m not sure the page name analysis is that interesting by itself. I think it gets very interesting when applied to the specific islands on a Wiki. People may be using a Wiki in a number of different ways, as demonstrated by the ivrwiki. Analysis on each individual cluster will potentially surface the different kinds of behaviors on a Wiki, which is more appropriate than trying to slap on a single archetype if one does not exist.    (LSK)

Finally, what level of clustering is healthy? In systems theory, networks that are either too tightly clustered or too lightly clustered are problematic. With enough analysis, we may be able to speculate on the right number for Wikis.    (LSL)

Matthew and I will release our code at some point, and we’ll hopefully have some time to follow up on it as well. Specifically, I’d like to examine a lot of other Wikis, starting with the ones that Blue Oxen Associates hosts.    (LSM)

There were a lot of other hacks at the Wikithon that were cool. My favorites were Ingy dot Net‘s Social Zork (which was not only hilarious, but is actually potentially useful) and Shawn Devlin‘s Word Cloud, which I hope to use on other Wikis. Christine Herron wrote a good summary of the day’s festivities.    (LSN)

Socialtext 2.0 Released

Congratulations to Ross Mayfield, Peter Kaminski, Adina Levin, and all the excellent folks at Socialtext for the release of Socialtext 2.0. Even bigger props for slipping in “Purple Consulting” in the screencast. I’ve been cranking so hard over the past six months, I didn’t have a chance to congratulate them on their Open Source release last July, so now I get to combine my commentary here. (In fact, I’m sitting on a bunch of Wiki-related posts right now that I need to push out; a lot of really cool stuff has been happening.) That’s good, because I have plenty to say.    (L72)

Socialtext 2.0 is an important release for three reasons. First, it doesn’t just look good, it’s highly usable. Adina and Pete deserve big-time credit for this. They’ve spent months painstakingly experimenting and testing the design. More importantly, they haven’t just focused on making it easy to use, but they’ve also agonized over how to accomodate expert usage as well.    (L73)

Have they succeeded? I think the personal home base concept is great. I love the fact that Backlinks are visible on the page and get lots of love. I love their new Recent Changes interface (and I hope to see a Tag Cloud view of the all pages index in the next release). I hate the fact that a Recent Changes link is not on every Wiki page. Both Pete and Adina are well aware of this beef, and I’m also well aware of their reason for not including it. Testing and user observation will tell what’s better.    (L74)

Second, Socialtext 2.0 has a really cool REST interface. Chris Dent has been boasting about it for months, but I didn’t look at it myself until Kirsten Jones walked me through it last week. (Her WikiWednesday presentation from earlier this month is online.) It really is cool, and it’s also useful. Congrats to Chris, Kirsten, Matthew O’Connor, and Matt Liggett for their excellent work!    (L75)

What’s great about this API is that it could very well serve as a standard URI scheme for all Wikis. This would obviate the need for a separate SOAP or Atom API. You just have a regular Web app, and you get the API behavior for free.    (L76)

For example, Alex Schroeder‘s currently going through the same process that Chris went through a year ago with Atom and OddMuse. An easier way around this problem would be to implement these REST APIs.    (L77)

(This is also a great opportunity for me to mention WikiOhana again, which gained great traction at WikiSym last month and which now has a lively Wiki of its own. PBWiki recently announced its own Wiki API, which is a good thing. We are all part of the same Wiki family. Socialtext and PBWiki need to talk about how their two efforts can work together. That’s the WikiOhana Way.)    (L78)

The third important thing about Socialtext 2.0 is that it’s Open Source. (Big props to Jonas Luster and Andy Lester for finally making this happen.) Here’s the thing. I think the announcement a few months back was overblown by a lot of blogosphere hype. The reality of all corporate Open Source releases is that — in and of themselves — they’re mostly meaningless. Mostly, but not completely. The fact that Socialtext 2.0 is Open Source means that other Wiki implementations can benefit from the great work that the Socialtext developers have done, from the APIs to the user interface. That makes for a healthier ecosystem, which is good for everybody.    (L79)

That said, the reason the actual open sourcing of Socialtext 2.0 (and any proprietary software project) is mostly meaningless is that the license is a critical, but tiny part of what makes Open Source software interesting and important. The big part is the community and collaborative process, and a lot of other things besides an open license are required to make that successful.    (L7A)

Before Socialtext went Open Source, I spent many hours talking to a bunch of people there about the impending release. I wanted to know how committed they were to making this a truly open and collaborative software project, because I felt the potential impact on the Wiki community was enormous. The answer I got was complex. The fact that everyone was willing to talk to me with no strings attached, in and of itself, demonstrated a commitment to openness, and I’m still grateful for that. The code itself will be a short-term bottleneck, as it needs a lot of work before outside developers will find it compelling. I also think the licensing terms are weaker than they need to be, although I also understand the outside pressures that make it so.    (L7B)

In short, I think the spirit is strong within Socialtext to fully realize the potential of this Open Source project, but there are also roadblocks. Hopefully, external pressures won’t squash that spirit. If Socialtext ever fulfills its potential as an Open Source company, it will not only help the ecosystem, but it will also tremendously benefit Socialtext as a business.    (L7C)