I have just finished writing a small proposal to the rest of my team. I thought it would be interesting to share here:
Introduction
We work in a virtual team. Even though there aren’t many of us, we often have few ideas about what the other people in our team are working on, which people they have met recently and what they are struggling with. The time difference between our main offices make our occasional feelings of being disconnected worse.
This “Narrating Your Work” experiment is an attempt to help overcome these problems.
If you are interested in some background reading, you should probably start with Luis Suarez’ blog post about narrating your work (”it’s all about the easiest way of keeping up with, and nurturing, your working relationships by constantly improving your social capital skills”) and then follow his links to Dave Winer, ambient intimacy and declarative living.
The experiment
“Narrating Your Work” should really be approached as an experiment. When it was first suggested, some people showed some hesitation or worries. We just don’t know whether and how it will work yet. The best way to find out is by trying. In Dutch: “niet geschoten, altijd mis”.
The experiment will have a clear-cut start and will last for two months. After running the experiment we will do a small survey to see what people thought of it: Did it deliver any benefits? If any to whom? Was it a lot of work to write updates? Did it create too much reading to do? Do we want to continue with narrating our work? Etc.
Three ways of participating
It needs to be clear who is participating in the experiment. If you decide to join, you commit to doing one of the following three things (you are allowed to switch between them and you will be “policed”):
Constant flow of updates: Every time you meet somebody who is not in the team, every time you create a new document or every time you do something that is different from just answering your emails, you will write a very short status update to say what you are doing or what you have done. This will create a true “activity stream” around the things you do at work.
Daily updates: At the end of your day you give a one paragraph recap of what you have done, again focusing on the people you have met, the places you have visited or the things you have created.
Weekly updates: On Friday afternoon or on Monday morning you write an update about the week that has just passed. To give this update some structure, it is suggested that you write about two things that went very well, two things that went less well and two things that are worrying to you (or at least will require attention in the next week).
The first option requires the most guts, whereas the last option requires the most diligence: it is not easy to take the time every week to look back at what happened over the last five working days. Are you the type of person who likes to clean the dishes as the day progresses, or are you the type who likes to leave them till there is nothing clean left? Choosing one of the first two options (rather than the third) will give the experiment the greatest chance of success.
Participation only requires the commitment for writing the updates. You are not expected to read all updates of the others, although you might very well be tempted!
How to do it: making it work
To make the work updates easily accessible we will use Yammer. You can do this in two ways:
You can post the work update with the tag #nywlob to your followers. People will see this message when they are following you, when they are watching the company feed or when they follow the nywlob topic.
If you don’t feel comfortable posting publicly to the whole company (or want to say something that needs to stay in the team) then you can post in an unlisted and private group. People will only see this message if they are members of the group and we will only let people in who work in the HRIT LoB and have agreed to join the experiment. Posting in this group will limit your chances of serendipity, so the first method is preferred.
When you are posting an update, please think about the people who might be reading it, so:
When you refer to a person that is already on Yammer, use the @mention technique to turn their name into a link (and notify them of you mentioning them)
If you refer to a person outside of Shell, link to their public LinkedIn profile.
If you mention any document or web page, make sure to add the link to the document so that people can take a look at it.
I am very interested in any comments you might have. Does anybody have any experience with this?
Arjen Vrielink and I write a monthly series titled: Parallax. We both agree on a title for the post and on some other arbitrary restrictions to induce our creative process. Some people would consider Facebook a threat to the open Internet (e.g. Tim Berners-Lee), whereas other people see it as a key tool for promoting democracy in this world (e.g. Wael Ghonim). We decided to each argue both sides of the argument (300 words “for” and 300 words “against”) and then poll our readers to see which argument they find more persuasive. You can read Arjen’s post with the same title here.
Facebook or no Facebook?
For a couple of months now my pragmatic side has been battling with my principled conscience. The matter of contention: whether to keep my Facebook account.
Why I will delete my Facebook account
There are three main problems with Facebook:
It creates a silo-ed version of the web . A big reason why the web works is the way you can link to other pages on the web: you don’t need anybody’s permission. The Berners-Lee video that I linked to earlier gives some great arguments about why this is important. Facebook is a closed silo from this perspective, creating an alternative network that does not have the same characteristics as the Internet. For some young people around me, the web (if not computing) is nearly synonymous with Facebook: they hardly leave the Facebook browser tab. If they do, it is usually to buy something. I am sure that soon you will be able to do that from Facebook too (e.g. Did you know that you can get somebody a Amazon gift certificate to be given to them on their Facebook wall on their birthday which they have registered with Facebook?)
The social graph is too important to be under the governance of a single commercial US-based company . Knowing how you are connected to other people can lead to powerful applications (see below). In fact, the social experiences that this allows are so important that we would be crazy to accept that all this relational data is in the hands of a company that can do with it whatever they want and might even be forced to share this data with the US government. There is no easy way to migrate this social graph into another system and Facebook displays a very proprietary attitude to it. What would happen if Facebook was forced to stop doing business or would decide to start charging people for their services?
Their sphere of influence is not transparent and ever-increasing . Facebook is all over the web now. What news site does not have a “Like” button? If you have a Facebook account and you don’t log out after you have used it, then Facebook is able to see the URLs of the pages you are reading, even if you don’t ever click on the like button. Your attention is mined and commercialized by Facebook. Even if you have very restrictive privacy settings your data will be still be given to any third party app that has managed to seduce one of your many Facebook friends. More and more sites are cropping up that will only allow you to log in using the Facebook login mechanism making it harder to use multiple identities the net. Facebook is becoming so pervasive on the net, that it requires tools like Disconnect or Abine’s TACO to make sure you are staying out of their clutches. Does this feel like a positive development in the way that you can use the web?
Why I will not delete my Facebook account
There are a couple of good reasons for me to keep a Facebook account:
They are past the tipping point . The network effect has come into play. Why should you be on Facebook? Because it is the one and only (global) place where everybody else is! Two years ago I organized a reunion of the very first class I mentored as a teacher. It took weeks of searching using all kinds of media before we got about 50% of the class together. This year we are doing another reunion: within a week we found 95% of the class on Facebook. Facebook facilitates this so-called ambient intimacy with people that you don’t regularly see or talk to, but still want to stay in touch with. What other means of communications has transaction costs that are this low?
They deliver an incredibly innovative service. Facebook deserves a lot of credit for the ideas that they have implemented and for the pace at which they keep innovating their mind-blowingly large scale service. They were the first company that decided to create a web platform for which third parties could write applications, they were the first to see and deliver on the true power of the social graph (turning it inside-out) and they have been creative in the way that they appropriate and add to ideas about activity streams, sharing in groups and even privacy controls (what other web service gives you that level of control over what you want to share?). For somebody like me, fascinated if not captivated by technology and looking through an innovation lens, there is an immense amount over ever-changing functionality to explore.
Having a centralized social graph leads to powerful applications. The first time I realized this was when I played Bejeweled on my iPhone. It allowed me to connect to my Facebook account and suddenly I wasn’t playing against other people at Internet scale (how can anyone score 20.000 points?!), but I was engaged in battles with family, friends and colleagues. Soon there will be a time where every piece of content we consume (books, news, magazines, videos, podcast) will be enriched by this meta-layer of your friends opinions. I call this the social contextualization of content. Facebook’s integration with Pandora was one of the first examples of how this will work. This meta-layer assumes a persistent social graph: you don’t want to keep finding your different groups of relations again and again do you?
[polldaddy poll=4696600]
Anyway, for me it is clear: I don’t want to be a part of Facebook’s success and would prefer it if we all would be using a differently architected solution in the near future. Fully decentralized and distributed systems are in the making everywhere (e.g. Diaspora, Pagekite, StatusNet, Unhosted and Buddycloud) and I will invest some time to explore those further. As I also personally get very little value out of Facebook, it is not hard to act principled in this case: I will be deleting my account.
Update on 10-11-2012: As I still don’t have a Facebook account I’ve deciced to change the title of this post.
Two weeks ago I visited Learning Technologies 2011 in London (blog post forthcoming). This meant I had less time to write down some thoughts on Lak11. I did manage to read most of the reading materials from the syllabus and did some experimenting with the different tools that are out there. Here are my reflections on week 3 and 4 (and a little bit of 5) of the course.
The Semantic Web and Linked Data
This was the main topic of week three of the course. Basically the semantic web has a couple of characteristics. It tries to separate the presentation of the data and the data itself. It does this by structuring the data which then allows linking up all the data. The technical way that this is done is through so-called RDF-triples: a subject, a predicate and an object.
Although he is a better writer than speaker, I still enjoyed this video of Tim Berners-Lee (the inventor of the web) explaining the concept of linked data. His point about the fact that we cannot predict what we are going to make with this technology is well taken: “If we end up only building the things I can imagine, we would have failed“.
The benefits of this are easy to see. In the forums there was a lot of discussion around whether the semantic web is feasible and whether it is actually necessary to put effort into it. People seemed to think that putting in a lot of human effort to make something easier to read for machines is turning the world upside down. I actually don’t think that is strictly true. I don’t believe we need strict ontologies, but I do think we could define more simple machine readable formats and create great interfaces for inputting data into these formats.
Microformats: where are the learning related ones?
These formats actually already exist and they are called microformats. Examples are hCard, hCalendar and hReview. These formats are simple and easy to understand and are created in a transparent and open process. Currently it does require some understanding of how these formats work to be able to use them, but in the near future this functionality will be build into the tools that we use to publish to the web. So just by filling in a little form about yourself you would be able to create an editable piece of text with an embedded hCard microformat.
So where are the learning related formats? I think it would be great to have small microformats that can describe a course or a learning object. I am aware of Dublin Core and IEEE LOM as ways of describing content, but these are a bit too complex (and actually do mix data and presentation is some weird way). Is anybody aware of initiatives to create some more simple formats? Are they built into any existing learning-related products?
Thinking about this has inspired me to add two microformats to my blog. The little text about me now contains machine readable hCard information and the license at the bottom of the sidebar is now machine readable too (using rel=”license”). I will also start to work on building my resume into the hResume format and publish it on my site. Check http://www.hansdezwart.info/qr in a couple of weeks to see how I have been getting on.
Use cases for analytics in corporate learning
Weeks ago Bert De Coutere started creating a set of use cases for analytics in corporate learning. I have been wanting to add some of my own ideas, but wasn’t able to create enough “thinking time” earlier. This week I finally managed to take part in the discussion. Thinking about the problem I noticed that I often found it difficult to make a distinction between learning and improving performance. In the end I decided not to worry about it. I also did not stick to the format: it should be pretty obvious what kind of analytics could deliver these use cases. These are the ideas that I added:
Portfolio management through monitoring search terms
You are responsible for the project management portfolio learning portfolio. In the past you mostly worried about “closing skill gaps” through making sure there were enough courses on the topic. In recent years you have switched to making sure the community is healthy and you have switched from developing “just in case” learning intervention towards “just in time” learning interventions. One thing that really helps you in doing your work is the weekly trending questions/topics/problems list you get in your mailbox. It is an ever-changing list of things that have been discussed and searched for recently in the project management space. It wasn’t until you saw this dashboard that you noticed a sharp increase in demand for information about privacy laws in China. Because of it you were able to create a document with some relevant links that you now show as a recommended result when people search for privacy and China.
Social Contextualization of Content
Whenever you look at any piece of content in your company (e.g. a video on the internal YouTube, an office document from a SharePoint site or news article on the intranet), you will not only see the content itself, but you will also see which other people in the company have seen that content, what tags they gave it, which passages they highlighted or annotated and what rating they gave the piece of content. There are easy ways for you to manage which “social context” you want to see. You can limit it to the people in your direct team, in your personal network or to the experts (either as defined by you or by an algorithm). You love the “aggregated highlights view” where you can see a heat map overlay of the important passages of a document. Another great feature is how you can play back chronologically who looked at each URL (seeing how it spread through the organization).
Data enabled meetings
Just before you go into a meeting you open the invite. Below the title of the meeting and the location you see the list of participants of the meeting. Next to each participant you see which other people in your network they have met with before and which people in your network they have emailed with and how recent those engagements have been. This gives you more context for the meeting. You don’t have to ask the vendor anymore whether your company is already using their product in some other part of the business. The list also jogs your memory: often you vaguely remember speaking to somebody but cannot seem to remember when you spoke and what you spoke about. This tools also gives you easy access to notes on and recordings of past conversations.
Automatic “getting-to-know-yous”
About once a week you get an invite created by “The Connector”. It invites you to get to know a person that you haven’t met before and always picks a convenient time to do it. Each time you and the other invitee accept one of these invites you are both surprised that you have never met before as you operate with similar stakeholders, work in similar topics or have similar challenges. In your settings you have given your preference for face to face meetings, so “The Connector” does not bother you with those video-conferencing sessions that other people seem to like so much.
“Train me now!”
You are in the lobby of the head office waiting for your appointment to arrive. She has just texted you that she will be 10 minutes late as she has been delayed by the traffic. You open the “Train me now!” app and tell it you have 8 minutes to spare. The app looks at the required training that is coming up for you, at the expiration dates of your certificates and at your current projects and interests. It also looks at the most popular pieces of learning content in the company and checks to see if any of your peers have recommended something to you (actually it also sees if they have recommended it to somebody else, because the algorithm has learned that this is a useful signal too), it eliminates anything that is longer than 8 minutes, anything that you have looked at before (and haven’t marked as something that could be shown again to you) and anything from a content provider that is on your blacklist. This all happens in a fraction of a second after which it presents you with a shortlist of videos for you to watch. The fact that you chose the second pick instead of the first is of course something that will get fed back into the system to make an even better recommendation next time.
Using micro formats for CVs
The way that a simple structured data format has been used to capture all CVs in the central HR management system in combination with the API that was put on top of it has allowed a wealth of applications for this structured data.
There are three more titles that I wanted to do, but did not have the chance to do yet.
Using external information inside the company
Suggested learning groups to self-organize
Linking performance data to learning excellence
Book: Head First Data Analytics
I have always been intrigued by O’Reilly’s Head First series of books. I don’t know any other publisher who is that explicit about how their books try to implement research based good practices like an informal style, repetition and the use of visuals. So when I encountered Data Analysis in the series I decided to give it a go. I wrote the following review on Goodreads:
The “Head First” series has a refreshing ambition: to create books that help people learn. They try to do this by following a set of evidence-based learning principles. Things like repetition, visual information and practice are all incorporated into the book. This good introduction to data analysis, in the end only scratches the surface and was a bit too simplistic for my taste. I liked the refreshers around hypothesis testing, solver optimisation in Excel, simple linear regression, cleaning up data and visualisation. The best thing about the book is how it introduced me to the open source multi-platform statistical package “R”.
Learning impact measurement and Knowledge Advisers
The day before Learning Technologies, Bersin and KnowledgeAdvisors organized a seminar about measuring the impact of learning. David Mallon, analyst at Bersin, presented their High-Impact Measurement framework.
Bersin High-Impact Measurement Framework
The thing that I thought was interesting was how the maturity of your measurement strategy is basically a function of how much your learning organization has moved towards performance consulting. How can you measure business impact if your planning and gap analysis isn’t close to the business?
Jeffrey Berk from KnowledgeAdvisors then tried to show how their Metrics that Matter product allows measurement and then dashboarding around all the parts of the Bersin framework. They basically do this by asking participants to fill in surveys after they have attended any kind of learning event. Their name for these surveys is “smart sheets” (an much improved iteration of the familiar “happy sheets”). KnowledgeAdvisors has a complete software as a service based infrastructure for sending out these digital surveys and collating the results. Because they have all this data they can benchmark your scores against yourself or against their other customers (in aggregate of course). They have done all the sensible statistics for you, so you don’t have to filter out the bias on self-reporting or think about cultural differences in the way people respond to these surveys. Another thing you can do is pull in real business data (think things like sales volumes). By doing some fancy regression analysis it is then possible to see what part of the improvement can be attributed with some level of confidence to the learning intervention, allowing you to calculate return on investment (ROI) for the learning programs.
All in all I was quite impressed with the toolset that they can provide and I do think they will probably serve a genuine need for many businesses.
The best question of the day came from Charles Jennings who pointed out to David Mallon that his talk had referred to the increasing importance of learning on the job and informal learning, but that the learning measurement framework only addresses measurement strategies for top-down and formal learning. Why was that the case? Unfortunately I cannot remember Mallon’s answer (which probably does say something about the quality or relevance of it!)
Experimenting with Needlebase, R, Google charts, Gephi and ManyEyes
The first tool that I tried out this week was Needlebase. This tool allows you to create a data model by defining the nodes in the model and their relations. Then you can train it on a web page of your choice to teach it how to scrape the information from the page. Once you have done that Needlebase will go out to collect all the information and will display it in a way that allows you to sort and graph the information. Watch this video to get a better idea of how this works:
I decided to see if I could use Needlebase to get some insights into resources on Delicious that are tagged with the “lak11” tag. Once you understands how it works, it only takes about 10 minutes to create the model and start scraping the page.
I wanted to get answers to the following questions:
Which five users have added the most links and what is the distribution of links over users?
Which twenty links were added the most with a “lak11” tag?
Which twenty links with a “lak11” tag are the most popular on Delicious?
Can the tags be put into a tag cloud based on the frequency of their use?
In which week were the Delicious users the most active when it came to bookmarking “lak11” resources?
Imagine that the answers to the questions above would be all somebody were able to see about this Knowledge and Learning Analytics course. Would they get a relatively balanced idea about the key topics, resources and people related to the course? What are some of the key things that would they would miss?
Unfortunately after I had done all the machine learning (and had written the above) I learned that Delicious explicitly blocks Needlebase from accessing the site. I therefore had to switch plans.
The Twapperkeeper service keeps a copy of all the tweets with a particular tag (Twitter itself only gives access to the last two weeks of messages through its search interface). I manage to train Needlebase to scrape all the tweets, the username, URL to user picture and userid of the person adding the tweet, who the tweet was a reply to, the unique ID of the tweet, the longitude and latitude, the client that was used and the date of the tweet.
I had to change my questions too:
Which ten users have added the most tweets and what is the distribution of tweets over users?
This was easy to get and graph with Needlebase itself:
Top 11 Lak11 Twitter Users
I personally like treemaps for this kind of data, so I tried to create one in IBM’s ManyEyes. Unfortunately they seem to have some persistent issues with their site:
ManyEyes error message
Which twenty links were added the most with a “lak11” tag? Another way of asking this would be: which twenty links created the most buzz?
This was a bit harder because Needlebase did not get the links for me. I had to download all the text into a text file and use some regular expressions to get a list of all the URLs in the tweets. 796 of the 967 tweets had a URL (that is more than 80%), 453 of these were unique. I could then do some manipulations in a spreadsheet (sorting, adding and some appending) to come up with a list. Most of these URLs are shortened, so I had to check them online to get their titles. This is the result:
One problem I noticed is that two of the twenty results were the same URL with a different shortened URLs (the link to the Moodle course and to the Paper.li paper): URL shorteners make the web the more difficult place in many ways.
What other hashtags are used next to Lak11?
Here I used a similar methodology as for the URLs. In the end I had a list of all the tags with their frequencies. I used Wordle and ManyEyes to put them into tag clouds:
Wordle Lak11 HashtagsManyEyes Lak11 Hashtags
Also compare them to tag clouds of the complete texts of the tweets (cleaned up to remove usernames, “RT”, “Lak11” URLs and the # in front of the hash tags):
Which one do you find more insightful? I personally prefer the latter one as it would give somebody who knows nothing about Lak11 a good flavor of the course.
How are the Tweets distributed over time? Is the traffic increasing with time or decreasing?
I decided to just get a simple list of days with the number of tweets per day. As an exercise I wanted to graph it in R. These are the results:
Tweets per day
I couldn’t learn anything interesting from that one.
Imagine that the answers to the questions above would be all somebody were able to see about this Knowledge and Learning Analytics course. Would they get a relatively balanced idea about the key topics, resources and people related to the course? What are some of the key things that would they would miss? If you would automate getting answers to all these question (no more manual writing of regex!) would that be useful for learners and facilitators?
I have to say that I was pleasantly surprised by how fruitful the little exercise with getting the top 20 links was. I really do believe that these links capture much of the best materials of the first couple of weeks of the course. If you would use the Wordle as the single image to give a flavour of the course and then point to the 20 URLs and get the names of the top Twitterers, than you would be off to badly.
Another great resource that I re-encountered in these weeks of the course was the Rosling’s Gapminder project:
Google has acquired some part of that technology and thus allows a similar kind of visualization with their spreadsheet data. What makes the data smart is the way that it shows three variables (x-axis, y-axis and size of the bubble and how they change over time. I thought hard about how I could use the Twitter data in this way, but couldn’t find anything sensible. I still wanted to play with the visualization. So at the World Bank’s Open Data Initiative I could download data about population size, investment in education and unemployment figures for a set of countries per year (they have a nice iPhone app too). When I loaded that data I got the following result:
Click to be able to play the motion graph
The last tool I installed and took a look at was Gephi. I first used SNAPP on the forums of week and exported that data into an XML based format. I then loaded that in Gephi and could play around a bit:
Week 1 forum relations in Gephi
My participation in numbers
I will have to add up my participation for the two (to three) weeks, so in week 3 and week 4 of the course I did 6 Moodle posts, tweeted 3 times about Lak11, wrote 1 blogpost and saved 49 bookmarks to Diigo.
The hours that I have played with all the different tools mentioned above are not mentioned in my self-measurement. However, I did really enjoy playing with these tools and learned a lot of new things.
Bert De Coutere has written a very good book on competences: Homo Competens (I wrote a small review on Goodreads). As a follow up to the book he is interviewing learning professionals about their competences, how they acquired them and how they keep them. I had the honour of being interviewed too (and he kindly allowed me to publish the interview below). You can find the other interviews here.
This is the full interview:
Bert: At what competence domain(s) would you consider yourself “competent”?
Hans: This is a hard question. I have different levels of competence in all kinds of domains. So I am a competent teacher, a relatively competent speaker and a very competent learner. If I would equate (professional) competence with what it is that I do then I would say I am competent in Internet technology with a strong focus on learning and open source.
Bert: Describe moment(s) where you grew the most in a particular competence domain.
Hans: Whenever you start something new, the learning curve is probably steepest. For me these have been the moments I switched jobs or roles in my career. So when I first started teaching in a high school, when I became an external consultant and then when I joined a large multinational company. I love to kickstart that learning process by consuming as much information about the topic as I can, starting with books, subscribing to tens (if not hundreds) of RSS feeds and then connecting to people who are really in the know about a particular topic.
Bert: How did you become good at what you do? How do you stay good?
Hans: You become good in what you do by actually doing it. This should be combined with a natural sense of curiosity, participating in a community of experts and the occasional pause for reflection. The one thing that really helps is a positive attitude towards experimentation. You have to be willing to try something different to be able to make progress, that means you should be afraid of failure.
Bert: Do you care to share any tips for those who want to follow in your footsteps? What went well? What would have been even better if only…?
Hans: Here come the platitudes: What has worked well for me is getting authentic pleasure out of what I do for a living. So if you want to follow in my footsteps (please, why?), start there. The one thing that I wish I had done more in the past is stretch myself a bit more: I am a careful person and I only like doing things that I know I can actually do. I am now trying to embrace those challenges when I get them.
Bert: How do you recognize competent people?
Hans: They usually wear purple outfits. No, seriously…
Bert: Do you see yourself doing something completely different five or ten years from now?
Hans: Looking back at how I thought about myself 10 years ago it would be foolish for me to answer anything but “yes” to this question. In a world where the accelerated change of technology is itself accelerating I don’t think we can imagine what the world of work will look like in ten years from now. So it is very likely I would do something different by that time. I’d like to think my job would still involve me thinking about how I can affect social practice through technology.
Bert: What do you think of the responsibilities of the knowledge professional at one hand, and the employing company at the other hand in terms of competence development?
Hans: This might be a trendy thing to say, but I am really starting to believe that working and learning are turning into the same thing (at least for knowledge workers). So who is responsible for doing the work? The professional! The one thing that the company could (and should) still do is to facilitate this by creating the right environment.
Bert: How would you categorize your professional network? Is it large, or do you keep it small? Is it composed primarily of people you meet regularly face to face, or is it very virtual, or any degree in between?
Hans: My professional network is larger than most of my direct colleagues. I actively work at making it larger: if knowledge resides in networks it only makes sense to work at optimizing that network. I have met most people in my network face to face at some point. Seeing people once a year at a conference is often enough to keep the professional connection alive for the rest of the year and be in touch virtually only.
Bert: Describe your ideal environment to thrive in.
Hans: There are two things I need: autonomy and a decent Internet connection. I get very uncomfortable very quickly if I don’t have either of these things.
Bert: How long did it take you to become good?
Hans: Aptitude has something to do with it. It didn’t take me very long before I was a good teacher, but I have been practicing my juggling skills for years now, and even though I am better at it than 99% of the people that can juggle three balls, I would still not consider myself to be good at it. They say it takes 10,000 hours of practice to become an expert at something, I would say it probably takes about 3,000 hours to become good at something.
Bert: Are you involved in any “sharing” activities? Do you think sharing helps you grow? Did you experience people taking advantage of the things you shared?
Hans: This is what I call the “teacher paradox”: the nature of the teacher-student relationship makes it that the teacher is always the one who learns the most. Thinking about how to share something with the rest of the world forces you to think about things just a little bit harder, gaining a better understanding. I write a blog under a Creative Commons license, have a Twitter account and share a lot external information in our internal Yammer network. “Taking advantage” has two meanings. I sure hope a lot of people have found the things I shared useful and have taken “advantage” of it in that way. I realize people are sometimes scared to share because they think people might “steal” their materials. I think this is a fallacy: I for one have gained way more from sharing than other people have gained from using my stuff.
Bert: How do you feel about the “self-reliant” professional? Do you find the evolution to “self”; self-steering, self-succeeding or self-failing, … a liberating evolution or one that rings alarm bells?
Hans: This is probably the most interesting question of the interview and it deserves much more thought than I will give it here. An increase in autonomy is a good thing and in that sense I like the increasing focus on the “self”. However, to live a fulfilling life you should have some dependence on others. It wouldn’t surprise me if this focus on the “self” is in some way a consequence of the fact that we can now organize ourselves without having organizations to facilitate that process. The focus on “self” can be there now, because our Western world finally enables us to be self-reliant.
Bert: How do you think your competence should be evaluated?
Hans: I should be the first judge of my own competence, other good alternatives would be my professional network, external or internal clients and my direct colleagues.
Bert: Thanks for the interview, Hans. Nice purple suit! (Just kidding.)
Unlike the Android marketplace, Apple’s appstore unfortunately does not allow you try out apps for a couple of minutes and get a refund if you don’t like them. After buying an iPad I wanted to have a good Mindmapping app, but I had no idea which of the six or so options would be the best choice for me. I searched for a site that compared them all, but couldn’t find that either. That’s when I decided to buy them all, use them all and review them all on this blog.
I wanted to make this a definitive review, so I created a companion spreadsheet with all the factual and easily quantifiable information about the different apps. You can find it here (I will not keep it up to date, so if you want to volunteer to do that I can give you access). The spreadsheet will tell you for example whether the app can work with an external screen, if there is an iPhone or Desktop equivalent and what methods and formats are supported for import and export.
iPad mind mapping compared in a spreadsheet
For each of the apps I tested how easy it was to learn and to use, how the mindmaps look, whether it is possible to share the maps easily to other users and locations and whether there are any online services that the maps can sync to. I also gave each of the app a rating (10 is marvellous, whereas 1 is horrible).
This is the offering by the company/man who has feverishly tried to copyright mind mapping and has build an accreditation and consultancy business around helping people leverage mind mapping in their work: Tony Buzan.
The stiff price of the app and the “official” stamp sets high expectations. Unfortunately the app doesn’t deliver. At first glance there is a lot of polish and a professional look (i.e. you get instructions on how to use the app with a slick video, the map overview screen with miniature versions of the mind maps is beautiful), but once you start using it, the shine goes away.
The interface is very counterintuitive. Even very experienced computer users might need to watch the video before they start being capable of inputting data using one of the two input methods. Moving nodes around and deleting them is clumsy. The interface for collapsing branches is shockingly bad. Each node can have a colour set and an icon (from a large collection) but cannot have any notes or URLs attached and can have a note or an URL attached (updated after a comment by Tim Smith).
The external presentation mode shows the map on the external screen and allows the iPad user to decide which topic to show. You cannot edit the map while using the external screen.
Overall it feels like this was built on commission by people with no real love for either mind mapping or the iPad. The people who commissioned the creation of the app, assumedly mind mapping experts from Buzan, should look at some of the other mind mapping apps available and learn that it isn’t only looks that are important.
Pros: Beautiful mind maps, “official” app.
Cons: Hard to use, no interoperability, outrageously expensive
The longer you use this mind mapping app the more you realise that its maker has tried to make the ultimate tool for mind mapping on the iPad. He is striving for perfection and it shows.
Although the app is intuitive to use for beginners, it also has an extensive feature list for power users: From the setting of backgrounds, to keyboard shortcuts (e.g. three times “enter” will create a new sibling node, whereas three times “space” creates a new child).
Maps are organised in folders and can each have an icon for easy recognition. There is no search function yet to find a particular map or its contents.
Adding, moving and copying nodes and branches of nodes is very easy and can be done intuitively in multiple ways. Occasionally the app will misinterpret your intentions, but this is quickly remedied by a quick tap on the undo button.
The nodes can contain all kinds of information, varying from task related items (priority, progress, start- and due date, all with matching icons) to notes, URLs and icons. The colour and shapes are customisable too and can be applied to all children in a branch. It is possible and easy to make links between different nodes. The boundary option is unique and useful: it puts all the nodes in a branch in an outline and colours the background.
iThoughtsHD has its own native file format, but also supports many other mind mapping formats. There are a number of im- and export options. One way that works very well is the Dropbox integration. There is a two-way sync between iThoughtsHD and Dropbox. This is great for backup and also allows an easy way to safely collaborate with someone else on a map using a shared Dropbox folder.
Another iThoughtsHD feature that the other apps are missing is a revision history. iThoughtsHD keeps older versions of your map in case you want to go back in time (although the most recent version of the app seems to have lost this functionality has only made this functionality available when creating a new map (updated after a tweet from the makers of the app)). The app actively advises you not to rely on iTunes for doing a full backup and has a way to send an email with your complete data in an archive. This archive can then be imported in case it is needed.
Pros: Most complete feature set, very rich in its im- and export options
Cons: Could be overkill for some users
This app is relatively new (I believe the web service is still in beta). It is a very simple app with an output that looks similar to MindNode (with the concepts/nodes on narrow lines, rather than in rounded boxes).
The main point of Maptini is that allows for very easy collaboration using either the app or the version in the browser (there is even a way to work in mobile safari). It is incredibly quick to make your map completely public and let anyone else with a Maptini account edit the map.
The editing is simple and fast and there is not a lot to worry about: there are just 6 colours and a delete button. The iPad app does not allow any importing and exporting of different mind maps: this all needs to be done through the web interface.
Collaborative editing in realtime does really work as advertised, so if it is important for you to have multiple people work on the same mind map at the same time, then this app is worth a shot.
Pros: made for collaboration
Cons: no other features than basic map-based outlining
MindMeister started its life on the web: for a yearly subscription fee you can have an unlimited number of mind maps stored online, accessible and editable through any modern browser and sharable with others for realtime collaborative work.
This web-based experience is now also available on mobile devices. The iPad app does not require a subscription with the web-service, but will only allow you to sync six mind maps from the iPad to your online account if you aren’t a subscriber (while not being completely transparent about how to influence which six maps will synched).
Like most (but not all) apps, MindMeister uses the model where you select a node and then click a “plus” to create a child of this node. This means that it always takes two taps to add a child, but what you lose in the number of taps, you gain in consistency. Moving nodes around is easy and the dedicated trashcan button is smartly put far away from the other node-related buttons in the interface. An undo button seems to be missing.
Nodes can be linked to each other, but it is not clear how to remove these links once you have created them (is this possible at all?). There is a good set of icons, the colour is flexible (you can even theme the whole map in one go), you can create direct links to URLs and email addresses and there are task related options. Tasks is something where MindMeister really shines: not only can you note the start/due date, priority, effort and completion, you can also assign the task to other MindMeister users. These tasks then sync to the web and people will get reminders when tasks are due.
The tasks functionality points to the ideal use case for MindMeister: if you work in a small team you could use it for all the minutes of meetings, for all the notes and for all the planning. The collaborative sharing would allow everybody to have the same view. When working through the browser the online collaboration works as fast as GoogleDocs (near instant synchronisation), on the iPad it seems to update a bit slower making it less easy to use with a virtual team.
The “Geistesblitz” functionality gets a lot of marketing in the description in the appstore, but is less useful than it is made out to be. What it allows you to do is to assign a default mind map (this needs to be done online). Whatever you then add in the Geistesblitz screen is added as a child of the “Geistesblitz” node in this default app. Most people will have another app to capture random notes and thoughts like this.
Most other apps with external screen support keep the iPad screen the same and display a version of the map (without any interface elements) on the external screen. MindMeister shows the complete iPad screen on the external screen, including all interface elements.
This is very slick app that is very intuitive and quick to use. The feature set is light: it is impossible to do anything else with a node but give it a colour and there are limited options for im- and export. What it does, it does exceptionally well: it is easy to add nodes and delete them (there is an undo and a dedicated delete button) and moving a node takes no effort too.
The thin and freshly coloured lines on which the text is written are pleasing to the eye. The one thing that could be improved is the fact that auto-lay-outing (the app calls it reorganising) has to be triggered manually whenever the map gets too messy: there is no way to have the app do it continuously.
In most cases a mind map is nothing more than a hierarchical outline and could alternatively be displayed as an indented list. Kudos to MindNode for providing an easy way to navigate the map in list form and to provide a search box allowing you to quickly find a particular piece of information in a large map.
The app allows you to save maps to Dropbox in different formats, but this is only a one-way street: there is no easy way to import maps from Dropbox in a similar manner. This is one of the few apps that supports printing. There is no easy way for collaborative editing.
Pros: Very fast and minimal interface
Cons: Light on features with no advanced lay-out option or “intelligent nodes”
Rating: 7/10
Total Recall
€ 0 for three maps, € 0.79 for unlimited maps by Zyense
Total Recall
The opening map of this mind mapping app has a bit of a childish look (probably caused by the pastel colours and the bubbly nodes). The app is very simple in its functionality.
Each of the bubbles (nodes) can have its colour set and can be connected to any of the other bubbles. These connections are many to many, so with Total Recall you aren’t stuck with a purely hierarchical system, but can create real networks too. Because of this, the automatic lay-outing algorithm is interesting: you press play to start it, after which it starts pulling on all the connections until it has reached some form of equilibrium.
There is no support for an external screen and no other way than email to collaborate with other users.
Pros: Cheap, ability to have multiple connections between nodes
Cons: Very limited functionality, not very fast to use
This is definitely the odd one out in this list of apps. Trout is not made to be similar to anything else, instead it looks and feels like it was written to solve the knowledge management issues that the author himself must have had.
In one way that is great: this is the only app that allows you to record sound snippets with each of the nodes and to add images that can be zoomed. There is an interesting quick direct link to Google search results for the words in the node and the way that you can add your own meaning to both colours and icons is refreshing.
On the other hand it also a bit of a hindrance: this is one of the hardest apps to come to grips with and some of the icons on the buttons are really unclear. There is little or no documentation, so you are left to yourself to find out what a “model” is and how to work with defining icons that can then be sorted in the list view.
This app would mainly be recommended to curious minds.
Pros: Ability to record sound and upload images
Cons: Unclear interface
Rating: 6.5/10
The Verdict:
Three of these tools are really viable for everyday use. If you are interested in a very quick and clean solution that works well, then go for MindNode.
For the individual user who wants to make sure that their maps look good and who needs to be flexible with where the data of the map goes, iThoughtsHD is the best option.
If you work in a small team and you get other people to also subscribe for an account, then MindMeister seems to be the best option.
My costs
It cost me € 51.33 to buy all the apps and do this review of them. As an experiment, I would like the readers of this post to help me carry these costs. Would you be willing to donate a small amount? ((I also would not say “no” to a free MindMeister subscription!). I will remove this button as soon as my costs are recovered.Update 3/1/13: My costs have been recovered (thanks to about 20 generous readers). If you appreciated the reviews, then I would still appreciate a donation.
I have to thank Linux Format for their Roundup feature format, which I used as the inspiration for the way this post is set up.
