How do you read references?
Data Science for Environment and Quality often receives questions and comments about the large number of references.
Some people think, "Isn't it possible to read so many books even if you read every day?", but in my case, I read as follows.
There are times when I find new books on the spot and times when I find them on the internet.
First of all, it is time to find a book by looking at the titles in front of the bookshelf of the library or bookstore and select the book that interests you. I try to pick up books I haven't read before.
Nowadays, we can search our collection on a computer, and books are recommended by various media, but it's strange that there are some books that we encounter only after going to the bookshelf.
Books in bookstores and libraries with many open books (books on bookshelves that general users can freely browse) are often found in this pattern.
I also search for it on the internet. For Japanese books, the search site of the National Diet Library is the most complete.
A book found on the internet cannot be easily read in person. You can either buy it or read it at the library, but the first thing to do is to refer to the information on the internet. If part of the book, such as the table of contents, is available online, it will be valuable information.
I also refer to book reviews on the Internet, but the significance of the book seems to be different for each person. When I actually read a book that was criticized badly, it was a good book for me. And vice versa.
If there is an original book and a commentary for it, I try to look at both the original and the commentary. The commentary has the advantage of being able to learn efficiently, but some of the features of the original book may not be explained.
The National Diet Library is a library that collects all kinds of Japanese books, so I am indebted to them for a long time.
When I pick up a book, look at the table of contents. Now you know what you're talking about.
If most of the content is clearly incomprehensible, or if you think that you don't need this deep knowledge for the time being, don't read any further.
If I can't tell from the table of contents, read the preface and postscript. Also, flip through all the pages. I may stop reading at this point.
Even if I read it this way, you may pick it up again after a few years, thinking, "Isn't it written in detail in that book?"
Books related to data science and machine learning that are made like textbooks are similar, so look at the table of contents and if there is a story (new method, etc.) that I do not know, read from there.
If the author's point of view is unique, I may also check how the author interprets the story we know.
If I are unfamiliar with the book, or if the gist is unclear from the table of contents, preface, or postscript, start reading carefully from the first chapter.
I start reading from the beginning of Chapter 1, and once I understand what kind of book it is, I sometimes switch to skimming.
Skimming is like looking at the context. When I see a terminology or a way of thinking that I have never seen before, I stop and read the surroundings. If there is a summary for each chapter, read it carefully.
It's about once every few years that I carefully read a book from beginning to end.