For the month of August 2013, the entire set of 35 columns is available for free.
In its 2.5 year history, the PoV column has established a significant legacy— it is one of the most frequently accessed parts of Nature Methods. The reason I think is clear: the community sees the value in clear and effective visual communication and acknowledges the need for a forum in which best practices in the field are presented practically and accessibly.
Bang Wong, in collaboration with visiting authors (Noam Shoresh, Nils Gehlenborg, Cydney Nielsen and Rikke Schmidt Kjærgaard), has penned 29 columns in the period of August 2010 to December 2012, covering broad topics such as salience, Gestalt principles, color, typography, negative space, layout, and data integration.
When it was A.C. Greyling's turn to speak at a debate in which Christopher Hitchens and Richard Dawkins already made their points, Greyling said
When one gets up to speak this late in a debate, one is a bit tempated to quote that Hungarian M.P. who after a long, long, long discussion in the parliament in Budapest stood up and said, "Everything has been said but not everybody said it yet." (watch on YouTube)
Indeed, this is quite how I feel after being offered to be the new author of Nature Methods Point of View column. Both Bang and Hitchens provide significant inspiration for me, so Greyling's words are particularly fitting.
To improve on the column is impossible. My challenge is to identify useful topics that have not yet been covered. I will be working closely with Nature Methods and Bang to ensure that the columns strike the right balance of topic, tone and timbre.
Don't hesitate to let me know whether PoV continues to hold your interest.
The annoucement of the return of the column, together with its history and a description of me, the new author, are available at the Nature Methods methagora blog.
Humor is kept by repeated reference to my now-dead-but-once-famous pet rat.
For the month of August 2013, the entire set of 35 columns is available for free.
I face problems for using the tools in power point to make nice illustration figures, and in addition how one can enhance the resolution of the figures to print it in a high quality mode.
In my opinion, the most difficult thing is how to draw the good-looking pictures and design the structure of slide to make it simple and substantial in content.
I find it difficult to find the right software to draw pictures.
The most difficult thing for me, when I make a figure, is to arrange the parts of the figure in a way they look nice and understandable.
I think the most difficult part is creating the concept, how to make a figure easy and fast to understand but not lacking all essential parts.
Stepping outside of my own knowledge of what the picture presents and viewing it as someone who sees it for the first time. It's easy to assume that some things are self evident and not making them clear enough in the pictures.
Figures that not are plots can also be tricky to get to look nice.
Anytime you have to draw something in paint, gimp, or other image program it requires a lot of work to make it look even slightly better than crap.
The most difficult thing (in general) is to include as much information as possible and display it in a way that is easy to understand. Figures should be intuitive for the reader, which is sometimes difficult to achieve. There might also be technical difficulties in achieving what you've visualized.
I think the most difficult part for me is to highlight the main idea I would like to express.
For me the most difficult part is making 3-D figures. Also while making figures its hard to decide on the good colors to choose for the figure.
In my opinion, the most difficult part when making a figure is don't know which software we can use and how to use.
The most difficult part for me is to start it! Because I am so meticulous and I am a painter, then it is not so easy to make decision about my figures and which one is better and so on, then finally I give up and put just one figure which of course I don't like...
I think it is difficult to put together my ideas to something that is connected and makes it easier for the viewer to understand.
It is so easy to just get an image from internet. I don’t know what is ok to do. There seems to be different rules in different communities.
To come up with a figure that does not simplify the concept too much at the same time as it does not overwhelm the viewer. To get some ideas for this is the reason why I take the course. ;-)
To me, how to make it easy to understand is the difficult part.
I think it is to save it in the correct format: Raster or vector, png or jpg or pdf... especially if I want to make some changes in the future to the figure.
I think is to choose the most appropriate figure that really help to transmit the information we want. Then, how many words can be good enough for been part of the message. At the beginning I used to use too many.
Apart from the difficulty of making the figure clear and easy to understand, the biggest problem I'm having is the captions. How long and detailed description is appropriate, so it neither steals attention from the figure nor leaves out too much important information.
I think the most difficult part is to have high resolution image once we want to save it. My experience is when finish with drawing, the file size sometimes to large for high quality image and if we downgrade it, the image becomes bad.
The most difficult part when i making a figure is the software using part, I'm not good at computer so that part is annoying for me all the time.
I think the most difficult is to find out how to condensate many ideas in one picture without making it difficult to understand.
The most difficult part is the get the image to not look too amateurish that people focus on that instead of the message.
The most difficult part when doing a figure is to let it speak for itself, i.e. to not have long caption text.
To be able to depict all the desirable results on a single figure is sometimes not that easy. It becomes more critical when a figure is to be fitted within a certain size frame. An exact placing of a figure in some text editors often comes along with difficulties.
The most difficult part when making a figure is to make it simple and still be informative.
Depends a lot on the kind of figure, but generally it is to get clarity in the design, such that the idea is conceived easily. This requires some good outline (usually an iterative process).
The most difficult part to make a figure is the need to express abstract concepts into drawings.
The compromise between include detailed information and at the same time be readable (figures in articles)
To compress all information and ideas you have in your head into short and clear message.
I feel the difficulty in choosing a right resolution of the picture and the angle that could visualize all the details. And also choosing right test/label colour, size, font. Another difficulty for me is continuation from one slide to another.
I believe that my biggest problem would be making nice flux charts. Generally the ones I draw look too crude, it does not look beautiful. I have no concern about making an image that can represent an idea, but making a beautiful image makes it more pleasing to the eyes of the people who will read my work.
It is very difficult to make the figure delicate. I am still not get used to put all the small components together to integrate the figure by the vector software, instead of drawing it out directly.
I think the most difficult part is to make the image simple but yet informative.
I find it very difficult to make an original clarity picture in a particular format after dimensioning it according to the requirement.
Some times it is difficult to limit the size (Bytes) of the picture when going for high clarity remake.
Making the figure as informative as you want while keeping it simple enough to grasp quickly.
For me, the more difficult part is to create a figure that contains or tells all the information that I want to transmit, but keeping the figure simple, clean and not overloaded.
The most difficult for me is make it easily to be understood meanwhile containing the essential information.
The most difficult thing when developing a figure is ... to remove the bloat but keep the message. (Besides the very most difficult: finding out what I want to tell.)
For me the most difficult part is to choose colors with right contrast and to make it more attractive and catchy.
Circos — circular whole-genome information graphics
Circos table viewer — display of tabular data in circular form
Hive plots — rational, quantitative and reproducible network visualization
High dynamic time range photography (HDTR) — imaging the flow of time
Science ♥ design talk at Bloomberg Design Conference 2013 (Bloomberg TV video, and video conversation with Alberto Cairo, moderated by Sam Grobart.)
Brewer palettes — benefit of using perceptual color spaces
Color palettes matter (talk) — learn about color, color spaces and why they matter
Effect of resolution on sequence visualization (handout) — understand how output resolution affects display of highly textured genomic annotations
We look at what happens how uncertainty of two variables combines and how this impacts the increased uncertainty when two samples are compared and highlight the differences between the two-sample and paired t-tests.
When performing any statistical test, it's important to understand and satisfy its requirements. The t-test is very robust with respect to some of its assumptions, but not others. We explore which.
Krzywinski, M. & Altman, N. (2014) Points of Significance: Comparing Samples — Part I Nature Methods 11:215-216.
Krzywinski, M. & Altman, N. (2013) Points of Significance: Significance, P values and t-tests Nature Methods 10:1041-1042.
Beautiful Science explores how our understanding of ourselves and our planet has evolved alongside our ability to represent, graph and map the mass data of the time. The exhibit runs 20 February — 26 May 2014 and is free to the public. There is a good Nature blog writeup about it, a piece in The Guardian, and a great video that explains the the exhibit narrated by Johanna Kieniewicz, the curator.
I am privileged to contribute an information graphic to the exhibit in the Tree of Life section. The piece shows how sequence similarity varies across species as a function of evolutionary distance. The installation is a set of 6 30x30 cm backlit panels. They look terrific.
Quick, name three chart types. Line, bar and scatter come to mind. Perhaps you said pie too—tsk tsk. Nobody ever thinks of the box plot.
Box plots reveal details about data without overloading a figure with a full frequency distribution histogram. They're easy to compare and now easy to make with BoxPlotR (try it). In our fifth Points of Significance column, we take a break from the theory to explain this plot type and—I hope— convince you that they're worth thinking about.
The February issue of Nature Methods kicks the bar chart two more times: Dan Evanko's Kick the Bar Chart Habit editorial and a Points of View: Bar charts and box plots column by Mark Streit and Nils Gehlenborg.
Krzywinski, M. & Altman, N. (2014) Points of Significance: Visualizing samples with box plots Nature Methods 11:119-120.
For specialists, visualizations should expose detail to allow for exploration and inspiration. For enthusiasts, they should provide context, integrate facts and inform. For the layperson, they should capture the essence of the topic, narrate a story and deligt.
Wired's Brandon Keim wrote up a short article about me and some of my work—Circle of Life: The Beautiful New Way to Visualize Biological Data.
Experimental designs that lack power cannot reliably detect real effects. Power of statistical tests is largely unappreciated and many underpowered studies continue to be published.
This month, Naomi and I explain what power is, how it relates to Type I and Type II errors and sample size. By understanding the relationship between these quantities you can design a study that has both low false positive rate and high power.
Krzywinski, M. & Altman, N. (2013) Points of Significance: Power and Sample Size Nature Methods 10:1139-1140.