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OK, I just read this completely amazing book by Nathan Yau. He has been running the dataflowing.com website for some years now and it is an excellent lesson for anybody that wants to communicate their science to others (e.g. me).
Now the book is out and it is an easy-reading, step-by-step explanation how to create great visualisations that get your point across immediately and also lots of warnings about what you can get wrong.
What I found most interesting is how Yau explains that some visualisations of the same data are much better than other visualisations of the same data. He clearly demonstrates this throughout the book. The text is clear, the examples are appropriate. As you might expect the layout is excellent and the way that the data is presented in exactly how you might like to present it yourself.
I cannot recommend this book highly enough. Go get yourself a copy if you have any kind of data you wish to present.
You can pick up a copy here on Amazon.
I haven’t had my DNA sequenced or tested by 23andMe, though I have some analysis done by National Geographic in the past.
What 23andMe do is they use a MicroArray chip to explore your genome for particular kinds of genetic variants. What this means in effect is that they take some cells from you, break them open gently, extract the DNA fraction of the cell, amplifying the DNA, then seeing which kinds of DNA are in the sample. Their technology uses an array of DNA on a glass slide. There are 1 million different kinds of DNA molecule on this small slide, each spot on the slide having a different DNA sequence. When they wash your DNA although the slide, if you have DNA that corresponds with a spot then it will stick to the spot. This gives you your genetic type.
Their service used to be very expensive but now they are charging $99. Which is very inexpensive. It is being promoted as a mechanism for finding out your ancestry. Naturally your DNA contains lots of other kinds of information apart from ancestry. Recently they asked their customers if they had male pattern baldness to take a photograph of their head. I’m presuming that because this is the world’s largest repository of genetic information that they cannot find some genetic determinants associated with baldness.
This is all fine as long as the information is safe. Thought I am not sure how strong legislation is for this kind of science. I’m not worried right now but I’m certainly going to keep an eye on what is happening.
Lots more to be seen at http://www.microbialart.com/
This is not going to be an easy post to write, and I really hope I do it justice.
The Apple/Mac community lost one of it’s finest podcasters today. Tim Verpoorten wasn’t the first Apple/Mac podcaster, but he was one of the very earliest generation. I think it would be fair to call him a father figure to many of us who followed. I know he was one of the podcasters who inspired me to pick up the microphone myself, and I doubt I’m alone in that.
Tim had been unwell for some time, and hung up his microphone to concentrate on his health a while ago, but we all hoped it would just be a temporary hiatus. I don’t think any of us in the community wanted to believe we’d heard the last of Tim’s distinctive and friendly voice.
Every good Apple/Mac podcast brings something unique to the table, and Tim’s Mac Review Cast brought fantastic reviews week after week after week for years and years. Tim had a knack for finding great apps, particularly free ones, and he was able to find and review them at a truly impressive rate. Most people can mange either quantity or quality, but Tim could do both at the same time. Although he reviewed many many apps, you could always tell when an app really appealed to him. Those apps were almost never large apps with lots of features, but small apps that did just one thing, but did it really well. It’s fair to say Tim had a bit of a thing for menubar apps.
Because I learned about so many great apps on the Mac Review Cast, I regularly look up at my menu bar, or into my dock, and think of Tim. One app in particular that I’ll always associate with him is the light-weight Mac-like text editor Smultron. I’d almost given up on finding an editor like this for the Mac, when I heard Tim review Smultron, and gave it a go. It was love at first sight, and that cute red strawberry icon will always bring back fond memories of Tim.
Tim was one of the founders of the Mac Round Table Podcast (MRT), and it was through that podcast that I was fortunate enough to get to ‘work’ (play more like) with Tim. One of the great things about the MRT is how different all the contributors are, and how that opens up some great conversations. We often agreed on things, but when it comes to temperament, I think myself and Tim were polar opposites – I’m know for being the cranky Irishman (sorta) who’s prone to impassioned (and hopefully entertaining) rants, while Tim was always as cool as a cucumber – I can’t remember him ever getting flapped, and I can’t remember him ever having a bad word to say about anyone. I think it’s much easier to go on a rant than it is to remain calm and collected, and I greatly admired Tim’s coolness.
I never met Tim in the real world, yet I feel I’ve lost a friend. The Mac community has certainly lost one of it’s finest ambassadors, but my thoughts are with the Verpoorten family tonight – their loss is so much greater than ours.
I don’t want to freak you all out with this, but if you don’t see the video, you won’t believe it.
This is a new Japanese Candy Fad.
SCIENCE my friends, this is science.
You seek the ten thousand things?
Then start at the edges
with long, even strokes.
The flow will carry you,
from the shoulders of one,
to the arms of another.
See the path where it isn’t.
Follow in straight lines
toward the centre.
And as you journey,
shrink to nothing,
until nothing’s not done.
The Journal of Improbable research has published a phylogenetic analysis of Pokemon characters, using bayesian inference implemented in the MrBayes software. Apparently, the work was mainly carried out by an undergraduate student. I have been trying to get my hands on the data matrix, since I think it would be a useful teaching tool and also because I would like to do some analyses on it – like look at variation in the rate of change in various characters, the likelihood that some characters were horizontally transferred, etc.
So, if you know where I can find the data matrix, please let me know.
Some great T-shirt designs from “Teach the Controversy” website. Using sarcasm to counter the creationist/intelligent design arguments that such nonsense should be taught in science classes.
You can see the full website here.
Software only becomes valuable when you ship it to customers. Before then it’s just a costly accumulation of hard work and assumptions.
Shipping unlocks a feedback loop that confirms or challenges those assumptions. It makes new things possible for your customers, and gives you the opportunity to focus on the next thing.
Shipping brings life to your team, to your product, and to your customers. Shipping is your company’s heartbeat.
The scramble to get that one last feature done, the late nights, the compromises, the sinking feeling when we realise something major is broken, the post-mortems… It’s agony, but if it was easy everyone would do it. Shipping exposes mistakes. We’re nervous about it, and our natural reaction is to do it reluctantly and infrequently, which actually carries higher risk, causing more reluctance in the future.
Not too long ago, shipping software involved actual ships, disks, and printed manuals. It happened perhaps once a year. Bug fixes weren’t automatic over the internet like today. Everything was slower and more controlled. The cost of shipping was massive, the consequence of a mistake was large. Today, the cost of shipping has approached zero. Most people can deploy in seconds or minutes with a single command or button click. With a little thought you can do that without your customers noticing, and with automated monitoring you’ll find out immediately if something goes wrong.
Despite the cost of shipping approaching zero, many people still ship software guided by very old habits.
The cadence at which you ship defines your company. A yearly cadence results in a very structured approach to the design->build->test cycle. A few months of building, while the rest is spend fixing. Engineers can join and leave before seeing their hard work end up in the hands of customers. The approach to design becomes one of anticipating all possible needs, rather than focusing and iterating on the important ones.
An obstacle downstream propagates upstream. If you’re not allowed to implement new ideas, you stop having them.
- Paul Graham
The right approach to shipping has a positive influence on your company’s productivity and your team’s happiness & job satisfaction. Shipping infrequently is an obstacle. Ship slow, and you’ll introduce challenges that push you to ship even slower. Ship frequently, and see positive effects everywhere in your company. For example, lets examine how behaviour changes along with shipping frequency, while handling a simple request from a customer.
Lets say a customer gets in touch to say “No matter what I do, I cannot save my name correctly, I think it doesn’t like hyphens“. In a company where you ship continuously, you see this and think Simple — I’ll tweak a test and a regex pattern, get a quick code review from my buddy beside me, merge to mainline, and 1 minute later when it’s deployed to production, reply to the customer: “Sorry about this, it’s fixed now, thanks for letting us know“. They’ll reply: “Wow, thanks for fixing so quickly“. High fives all around!
If we stretch the time to production (TTP) out a little, even to 10 minutes, the behaviour changes. You either do the same, but reply saying it’ll be fixed with our next deploy (probably 10 minutes) – or you wait, so that you can communicate with certainty. The waiting is time where you’ll shift focus to something else, but have the baggage of having to follow up. Perhaps you’ll think, I’ll have a quick coffee, then move on to something else afterwards. Even though your deployments are entirely automated, you lose time because of waiting and losing focus.
If TTP is hours, the behaviour changes again. No longer can you say with certainty when the change will be out there, so you’re tempted to batch up with other similar small changes. You postpone replying until you get time to do it, sometimes forgetting about it. You’re less likely to take prompt action, wow’ing the customer, and you pay some mental cost for having it on a todo list. Since getting to production takes hours now, your team will start restricting to morning only deploys, so miss that slot and it’s further delays.
If TTP is days, it exacerbates that further – perhaps you’ll reply “Thanks for letting us know. We’ll fix this in our next sprint”. It gets bundled in with a whole load of other small low, priority items, you spend more time debating estimates, and priorities, than the first guy took to fix it and reply to the customer. Miss the beginning of week deploy window and further slippage. The larger releases bring higher risk, you’ll tell your customer it’s fixed, only to later require rolling back because of a separate change. Your bug database gets bigger and bigger, with little details that you’ll probably never fix.
When TTP is weeks, it exaggerates that even further – perhaps you’ll reply “Sorry about this, I’ll let the development team know” or something equally lame from your customer’s standpoint. Deep down you realise nothing will be fixed, and the job of talking to customers becomes a cost or hassle, rather than an opportunity to improve your product and nurture happy loyal customers.
Better approaches to writing or testing software help us iterate more quickly and confidently, but the benefits are quite local to engineering teams. Continuous shipping on the other hand, touches all parts of your company, as do the benefits, and the behaviours it enables and encourages.
Linkedin’s transition to continuous deployment is linked to their recent financial success.
Good products, are a side effect of combining good people with an idea in an environment that helps those people to kick ass. Your attitude to shipping is a big part of that environment you create.
Shipping breathes life into how we think. The feedback loop helps us learn, gain confidence in making quick decisions, and build momentum. Momentum in product improvements excites and engages our customers. Seeing quickly the benefits of our hard work, motivates us to do more. Building a team where people can work hard and move fast attracts others to join you – hiring gets easier.
Shipping continuously isn’t an achievement you unlock and then move on. You’ve got to constantly obsess about it. If you believe in the benefits it brings, you’ll be driven to shrink 20 minutes down to 1 minute or less, you’ll consider ‘ability to ship‘ as an equal to ‘does it scale‘ when building new systems. And you’ll do that because of all the life it breathes into your company and your product.
Shipping is your company’s heartbeat.
This is an animated gif of the internet as it works day and night. The information is based on ping rates from 420,000 machines worldwide and it was a pretty illegal thing to do. If you want to read more about it, you can do so here.
These are the exchanges between the crew of the Starship Enterprise and Commander Hadfield of the International space station.
First up is William Shatner who tweeted Commander Hadfield:
Then a couple of days later, Leonard Nimoy made his contribution:
I just listened to Sheryl Sandberg from the TED Symposium in 2010 where her fame as a “feminism rebooted” advocate started (at least in the eyes of the popular press).
In this talk Sandberg said that women needed to do three things:
1. Sit at the table – i.e. Don’t sit back come forward and make your presence felt.
2. Make your partner a real partner – i.e. make sure that whoever your partner is, that you both participate in this relationship in an equal way.
3. Don’t drop out before you absolutely have to – if a woman plans on getting pregnant, for instance, then this is a discrete event that needs to be dealt with when it comes along. don’t put off doing stuff you might like to do simply because you think it might interfere with something else that hasn’t even happened yet.
I have mixed feelings about her message. First of all, it seems to advocate that there is more worth in pursuing career options than in pursuing home options. So, being a pluralist, I am not sure I like the message that there is only one way to achieve things in this life.
Putting all that aside, I think her advice applies equally to men and women – put yourself forward, make sure you have as much balance as you can have in life and it ain’t over ’till it’s over.
There are perception biases in Science. Famously, two versions of a CV were circulated to both male and female researchers and they were asked their opinion of the CV. The two versions differed only in the name at the top – in one case it was male and in one case it was female. There was a small but significant difference in how the recruiters viewed the two versions of the CV, with the female version being ranked lower. This bias was evidence irrespective of whether the recruiter was male or female – even female recruiters manifested this bias.
So, what is the lesson, or is there one? Well, we can say for certain that there is a bias. OK, but are these recruiters factoring in the differences between male and female scientific output in their evaluation of the CV? Are they employing something like a Bayesian framework in their evaluation? Is their prior experience that on average women publish fewer papers influencing their evaluation of the CV? So, even though both CVs have the exact same number of publications cited, do the recruiters feel that this won’t last? Is this wrong? More provocatively, is this right?
Scientific peer-review is about the science and I am pretty sure, though not 100% sure, there is very little gender-bias in this process. In any case, most papers are multi-authored these days. Therefore, I think that publication output is a fairly fair representation of a person’s ability to take on a project and bring it to conclusion. The lower publication rate among female grad students might be factored into these priors – the recruiters might be pessimistic about female researchers likelihood of staying the course. If their goal is to do the best possible recruiting job for their place of employment, then are they right to factor this probability in?
Obviously, it is simply not on to discriminate in any way – effort and reward should be tightly linked and should be blind to everything else. So, what is cause and what is effect? Are women being held back, or are they holding back, as Sheryl Sandberg implies?
We can see that there are more Female PhD students in the biological sciences, for instance, but far fewer professors (the number of post-docs is about even). So, women begin to leave the research workforce generally before children are a consideration. Is this happening because the career path for a research scientist is notoriously uncertain and this uncertainty is a greater worry for females than males (believe me it is a worry for males too)?
Once they start working in research, does an intrinsic dislike for research science develop in a greater proportion of females than males and this causes the higher drop-out levels? Are women leaving in numbers simply because it is a kind of job that looks OK on the surface, but the reality is nothing of the kind. I worked in the lab for about 8 years and believe me there is nothing more soul-destroying than a carefully planned experiment that comes up with nothing. Does this kind of continuous crushing defeat affect women more than men?
Is there an issue with the fact that most profs are male and that female students do not fare well with a male supervisor? I don’t know if any study has been performed on the influence of supervisor gender in affecting grad student outcome. Do female researchers tend to perform better in laboratories where there is a female prof? I don’t know the answer to this one, but it would certainly help my thinking.
Are young female scientists pessimistic about their future because they don’t see enough successful women at the top and they think “Meh, no woman ever gets there, so why should I try?”. How about mid-career female scientists? Because there are fewer female senior scientists than mid-career females, so the process of stopping is not restricted to females in their early stages.
Can all this change in the future?
You can get Sandberg’s book by clicking the image below.
There shall be a judge for every crime,
and whosoever sins shall be found.
Let them be stripped, pieces put on display,
their children taken away.
They shall be paraded before the people,
that all may see this is a sinner.
Then let the healing by hammer begin
the forge will burn their edges away.
Run again and all is well.