Writing Involves Reading

A lot of people think that ideas simply come into my head from nowhere and then I write them down. At some point, usually after three or four hours with several coffee breaks thrown in, I go fishing or do something else with my life. Somehow, the books just magically appear on sites such as Amazon and in the bookstores.

Unfortunately, writing isn’t quite that simple. During any given week I probably spend a minimum of 14 hours reading, often times more. I don’t just read computer science books either. In fact, many of my best ideas come from non-computer sources. It’s hard to say what will make a good source for ideas for my particular kind and style of writing. I’ve actually had poems influence me and more than a few fiction books. I once created a section of a chapter based on an idea I got from a Tom Clancy novel. The point is that writers are engaged in two-way communication. We get input from all sorts of sources, use that input to create new ideas and concepts, and then write those new bits of information down for others to read.

Reading differs from research. When an author researches something, the focus is direct and narrow. The goal is to obtain specific information. Reading is far more general. There really isn’t a focus, just communication. In reading a book or magazine, I might find a new technique for presenting information or a perspective I hadn’t considered before. The goal is to obtain experiences; to explore the world of print in an unfettered manner. The result is often enhanced creativity.

Of course, just as no one is able to get up in the morning and say, “Today I will be brilliant!” with any level of serious intent, reading may not produce any lasting effect at all. The communication may be an ephemeral experience of pleasure, joy, or some other emotion. Even in this case, letting the subconscious mind work while keeping the conscious mind entertained is a good idea. Sometimes a reading session, followed by a walk or some other activity, yields a solution to a writing problem that has nothing to do with the reading or the walking, but simply the allocation of time to the needs of the subconscious mind.

The bottom line is that if you want to become a writer, then you really must engage in writing activities because writing is as much about practice as it is talent. However, you must engage in other forms of communication as well or your skills will top out at some level and you’ll never fully realize your potential. Reading is truly a fundamental part of writing. Let me know your thoughts on reading as part of building skills in writing at John@JohnMuellerBooks.com.

 

Facing the Blank Page

Most writers face writer’s block at some point. You have a blank page that’s waiting for you to fill it and you have a vague notion of what you want to say, but the text simply doesn’t come out right. So, you write, and write some more, and write still more, and hours later you still have a blank page. Yes, you’ve written many words during that time—all of them good words—just not the right words.

Every piece of writing I do starts with an outline. Even my articles start with an outline. Creating outlines help you focus your thoughts. More importantly, they help you to see how your thoughts will flow from one idea to the next. Sometimes, if you’re honest with yourself, you’ll discover that you really don’t have anything more than a vague idea that will never become an article, white paper, book, or some other piece of writing. Of course, that’s really the reason for this exercise—to see if you have enough information to even begin writing. If you don’t have enough information, then you need to research your topic more. Research can take all sorts of forms that include everyone from reading other texts on the topic, to doing interviews, to playing. That’s right, even playing is an essential part of the writer’s toolbox, but this is a kind of practical play that has specific goals.

Once you do have an outline and you’re certain that the outline will work, you need to mark it up. My outlines often contain links to resources that I want to emphasize while I write (or at least use as sources of inspiration). A lot of writers take this approach because again, it helps focus your thoughts. However, an outline should also contain other kinds of information. For example, if a particular section is supposed to elicit a particular emotion, then make sure you document it. You should also include information from your proposal (book goals) and your reader profile (who will read a particular section) in the outline. Your marked up outline will help you understand just what it is that you really want to write. In reading your outline, you can start to see holes in the coverage, logic errors, and ideas that simply don’t fit.

Moving your outline entries to the blank page will help you start the writing process. Convert the entries to headings and subheadings. Ensure that the presentation of the headings and subheadings is consistent with the piece as a whole. Unfortunately, you can still end up with writer’s block. Yes, now you have some good words on the page, but no real content. An outline is simply a synopsis of your ideas in a formalized presentation after all.

Write the introduction and the summary to the piece next. The introduction is an advertisement designed to entice the reader into moving forward. However, it also acts as a starting point. The summary doesn’t just summarize the material in the piece—it provides the reader with direction on what to do next. People should view a good summary as a call to action. By creating the introduction and the summary, you create the starting and ending points for your piece—the content starts to become a matter of drawing a line between the two from a writing perspective.

At this point, you have enough material that you could possibly ask for help. Try reading your piece to someone else. Reading material aloud uses a different part of the brain than reading the same material silently. Discussing the material with someone else places a different emphasis on the material. The other party can sometimes provide good suggestions. You may not use the suggestions directly, but listening carefully can often present you with creative ideas that you wouldn’t have considered otherwise.

It’s important not to overwork the piece. Sometimes you need to do something else for a while. Yes, you always want to spend time in research and thinking your piece through, some writing is often done in the subconscious. Fill your head up with as many creative ideas, fascinating thoughts, and facts that you can, and then do something that actually will take your conscious mind off the topic. You might watch a television show or movie, go for a while. have coffee with a friend, take a nap, or do any of a number of other things. The important thing is to forget about the book for a while. Often, you’ll find that the now semi-blank page doesn’t present a problem when you return. Let me hear about your ideas for dealing with the blank page at John@JohnMuellerBooks.com.

 

Finding and Employing Data Science Tools

Python for Data Science for Dummies introduces you to a number of common libraries used for data science experimentation and discovery. Most of these libraries also figure prominently as part of a data scientist’s toolbox because they provide common functionality needed for every application. However, these libraries are only the tip of the data science toolbox. Because data science is such a new technology, you can find all sorts of tools to perform a wide range of tasks, but there is little standardization and some of these tools are hard to categorize so that you know where they fit within your toolbox. That’s why I was excited to see, The data science ecosystem, the first of a three part series of articles that describe some of the tools available for use in data science projects. You can find the other two parts of the article at:

The problem for people who want to explore data science and machine learning today might not be the lack of tools, but the lack of creativity in using them. In order to explore data science, it’s important to understand that the tools only work when your prepare the data properly, employ the correct algorithm, and define reasonable goals. No matter how hard you try, data science and machine learning can’t provide you with the correct numeric sequences for the next five lottery wins. However, data science can help you locate potential sources of fraud in an organization. The article, Machine learning and the strategic snake oil reserve, sums up what may be the biggest problem with data science today—people expect miracles without putting in the required work. Fortunately, there are new tools on the horizon to make languages, such as Python, and products, such as Hadoop, easier for even the less creative mind to use (see Python and Hadoop project puts data scientists first).

Even with a great imagination, the tools available today may not do the job you want as well as they should because the underlying hardware isn’t capable of performing the required tasks. The process is further hampered by a misuse of the skills that data scientists provide (see You’re hiring the wrong data scientists for details). As a result, you need a large number of specialized tools in order to perform tasks that shouldn’t require them. However, that’s the reason why you need to know about the availability of these tools so that you can produce useful results on today’s hardware with a minimum of fuss. Asking the question, “How would Alan Turing fix A.I.?” helps you understand the complexities of the data science and machine learning environments.

Data science, machine learning, data scientists with even greater skills, and better hardware will keep the momentum going well into the future. As the Internet of Things (IoT) continues to move forward and the problem of what to do with all that data becomes even larger, data science will take on a larger role in everyone’s daily life. Count on reading more articles like, Google a step closer to developing machines with human-like intelligence, that describe the proliferation of new hardware and new tools to make the full potential of data science and machine learning a reality. In the meantime, getting the tools you need and exploring the ways in which you can creatively use data science to solve problems is the best way to go for now. Let me know your thoughts on the future of data science at John@JohnMuellerBooks.com.

 

Understanding the Effects of REM Sleep on Writing

A lot of people wonder how authors sometimes make the creative leaps they do in books. Of course, part of it is natural gift. Writing does involve some element of innate ability—a requirement that has been proven to my satisfaction more than a few times. Another part of the creative leap is mindset. When you spend a great deal of energy looking for something, you’re bound to eventually find it. We can target how our minds process information and therefore, control the resulting output to some degree. Hard work also comes into play—the best authors research their topic heavily (even in the fiction arena).

However, the obvious factors alone can’t account for the creative leap. Something more is at work than these elements. Over the years I’ve come to understand that part of what makes me a good author is my subconscious. An ability to take information stored during my waking hours and turn it into patterns as I sleep is part of the writing process for me and most likely many other authors as well (whether they realize it or not).

Sleep alone isn’t enough to generate the informational patterns, however. Over the years I’ve read articles such as REM Sleep Stimulates Creativity and Sleeping on it – how REM sleep boosts creative problem-solving. In fact, because the topic interests me so much, I’ve probably read a hundred or so such articles and a few books as well (such as, A Whack on the Side of the Head: How You Can Be More Creative). Getting sufficient Rapid Eye Movement (REM) sleep is an essential part of the creative process. In graphing my own productivity over the years, I’ve found a correlation between the quantity of REM sleep (and most especially, remembered dreams) and the quality of my output. Sometimes quantity is also affected by REM sleep, but the best writing I’ve done is when I’ve had enough REM sleep.

The onset of REM sleep usually occurs about 90 minutes after falling asleep. The sleep cycle varies between light and REM sleep depending on the person. A number of other factors also seem to play a role in my own personal sleep cycle. For example, I tend to get more REM sleep after a day of moderate physical exertion, mixed with plenty of research time (non-writing time). Eating no more than two hours before I go to bed is also a factor and I also try to create a restful environment conducive to sleep. In fact, more than once I’ve taken a two hour nap after performing research to overcome writer’s block. The technique works quite often. (Shorter nap times don’t appear to provide any advantage because the REM sleep cycle may not even occur or is of insufficient length to derive a solution to the problem at hand.)

As part of the dreaming cycle, I’m often able to employ lucid dreaming techniques (or what is commonly called directed dreaming). However, more often than not I simply wake with the answers to the questions I had when I went to sleep and quickly write them down. It’s a technique authors have used successfully over the centuries to great effect.

The point is that REM sleep is a required component for many creative endeavors. It’s not just authors who require REM sleep, but anyone who is involved in any sort of creative effort. A lack of REM sleep may be why engineers on a team are unable to create a useful solution to problems or why developers write buggy code. There is certainly nothing mysterious about the process, except why more people don’t employ it.

What is your take on REM sleep? Do you ever stuff your head full of information and then go take a nap to solve problems? If not, would you be willing to give the technique a try after reading this article? Let me know your thoughts (and the results of any experiments) at John@JohnMuellerBooks.com.

 

Thinking of All the Possibilities in Software Design

A number of books on my shelf, some of which I’ve written, broach the topic of divergent thinking. Unfortunately, many developers (and many more managers) don’t really grasp the ideas behind divergent thinking. Simply put, divergent thinking starts with a single premise and views as many permutations of that premise as possible. Most developers don’t take the time to use divergent thinking as part of the development process because they don’t see a use for it. In fact, most books fall short of even discussing the potential for divergent thinking, much less naming it as a specific element of application design. I’ve explored the topic before and a reader recently reminded me of an article I wrote on the topic entitled, Divergent Versus Convergent Thinking: Which Is Better for Software Design?.

The process that most developers rely upon is convergent thinking, which is where you convert general goals and needs into specific solutions that appear within a single application. The difference between the two modes of thinking is that divergent thinking begins with a single specific premise, while convergent thinking begins with a number of general premises. More specifically, divergent thinking is the process you use to consider all of the possibilities before you use convergent thinking to create specific solutions to those possibilities.

There is an actual cycle between divergent and convergent thinking. You use divergent thinking when you start a project to ensure you discover as many possibly ways to address user requirements as possible. Once you have a number of possibilities, you use convergent thinking to consider the solutions for those possibilities in the form of a design. The process will point out those possibilities that will work and those that don’t. Maintaining a middle ground between extremes of divergent and convergent thinking will help create unique solutions, yet keep the project on track and maintain project team integrity. Managing the cycle is the job of the person in charge of the project, who is often the CIO, but could be some other management position. So, the manager has to be knowledgeable about software design in order for the process to work as anticipated.

One of the reasons that many applications fail today is the lack of divergent thinking as part of the software design process. We’re all too busy thinking about solutions, rather than possibilities. Yet, the creative mind and the creative process is based on divergent thinking. The reason we’re getting the same solutions rehashed in a million different ways (resulting in a lack of interest in new solutions) is the lack of divergent thinking in the development process.

In fact, I’d go so far as to say that most developers have never even heard of divergent thinking (and never heard convergent thinking called by that name). With this in mind, I’ve decided to provide some resources you can use to learn more about divergent thinking and possibly add it to your application design process.

 

These are just four of several hundred articles I located on divergent thinking online. I chose these particular four articles because they represent a range of ideas that most developers will find helpful, especially the idea of not applying stereotypical processes when trying to use divergent thinking. Stereotypes tend to block creative flow, which is partly what divergent thinking is all about.

The bottom line is that until divergent thinking is made part of the software design process, we’ll continue to suffer through rehashed versions of the current solutions. What is your view of divergent thinking? Do you see it as a useful tool or something best avoided? Let me know your thoughts at John@JohnMuellerBooks.com.

 

Pondering Practical Play

People often ask me where I get ideas for my books or come up with solutions for business needs. The answer is simultaneously easy and difficult. One of the topics I don’t discuss often enough in books such as C# Design and Development is the need for play. If you don’t play, then you’re not spending your time wisely because play opens the mind to possibilities that you might not have considered. The essence of play is thinking about the impossible and making it happen. Many adults think that play is just for children, but play is for everyone.

I’m not talking about the sort of play that many people think about today. Exercising your thumb muscles during a video game isn’t the sort of play that promotes creative thought. Mindlessly watching the television doesn’t work either. The sort of play I’m talking about is where you look at something and decide to do the impossible with it. When a child plays, a block of wood can become nearly anything. A stick becomes a broomstick for riding, a sword for fighting, a flagpole with a banner attached (whether there is a banner to see or not), a magic wand, or literally thousands of other items. The stick is still a stick, but play makes it into something more.

Do you take time anymore to watch a spider spin a web? When was the last time you decided to imagine shapes in clouds? The colors that you see—are they really as dull as you think? These sorts of questions are answered during play. I played in another post on this blog. Read the Quick Sugar Free Cupcakes post again and you’ll see that I played with the batter until I created something that pleased both Rebecca and me. No, they weren’t the most exotic cupcakes ever made, but that isn’t the point of playdoing something new and interesting is what play is all about.

Practical play is goal-oriented. I’m currently writing a series of posts about a program named GrabAPicture that I created during play time. My only goal when I started creating that application (and many others on my system) was to see what I could do and what it would take to do it. I played with the code until I created an interesting application from it. How many developers take time to play today? If we had more developers playing, perhaps many of the problems that we’re facing today would already be fixed. So, I started GrabAPicture with a goalto change my desktop wallpaper in a certain way, but I didn’t place any restrictions on how I achieved my goal or how long I’d play until I was happy with it. The idea was to spend some time writing code for no other reason than the sheer joy of doing so.

In most cases, practical play is also more artistic, than scientific or concrete. Decorating eggs my not seem very practical, but I experimented with various color combinations as part of the process. The knowledge I gained has changed some of the things I do in my books. An idea experienced while decorating eggs has had a practical outcome in the way that I view color in my books. This is what play is all about.

Play is an essential part of the human experience. When you play, you free yourself from the bonds that normally keep you from thinking with your whole mind. A person who is playing is relaxed and free to think outside the normal boundaries that we set for ourselves. Some of the most influential thinkers throughout history have played. Read about Einstein and Edison as just two examples. You’ll find that they both played while others kept to the grindstone. How do you play? Let me know at John@JohnMuellerBooks.com.