# New (RMarkdown) post from OS X 10.10 (Yosemite)

This is my first post on OSX 10.10 (nick name: Yosemite). Yep I always late…

As I did mostly, I blog using RMarkdown. It allows you to manipulate your source file in to a structured text and convert it to almost any formats: odt, docx, pdf, html, etc.

Basically you can make any docs containing:

• outline
• bullets and numbering
• basics formatting:
• make it bold = bold,
• or italic = italic,
• even make an superscript symbol = superscript and off course subscript subscript ,
• strikethrough
• write equations: $Q = CA(dh/dl)$
• insert a link: DasaptaErwinBlog
• insert a figure:
• insert a quote or lines of code: quote from Einstein
• insert a table:
Name Age (ya)
Rex 65,000,000
Mankind 100.000
me 39
wife 35
Radit 8
Bila 4
- make a chart out of it
Name <- c('Rex', 'Mankind', 'Me', 'Wife', 'Radit', 'Bila')
Age <- c(65, 0.1, 39, 35, 8, 4)
df <- data.frame(Name, Age)
plot(df, main="Age comparison", xlab="Species", ylab="Age (mya)")


• and a whole lot more

Another good thing is you can built the entire doc in plain text (ASCII). So it’s:

• light weight: in kb
• connected to any word-processor:
• Libreoffice
• MS office
• or text-editor:
• notepad
• wordpad
• virus-free

//

# Minimal LaTeX Packages

(image from: CTAN.org)

Dear friends,

I’ve been using LaTeX (with TeX Studio) for about two years now. I use it mostly for long-formatted document. And by long, I mean more than five pages with several headings and subheadings. More light editing or letter, I use LibreOffice. As a typesetter (not a word processor), most begineer will bump into what package to use, or not to use, or a case of redundant packages.

So here I share what minimal packages that I used daily:

documentclass[a4paper]{scrartcl} usepackage[ascii]{inputenc} % keyboard encoding tool usepackage[T1]{fontenc} % keyboard encoding tool usepackage[english]{babel} % language setting tool usepackage{amsmath,amssymb,amsfonts,textcomp} % math font type tools usepackage{color} % font color tool usepackage{array,hhline} % tabular tool usepackage{hyperref} % hyperlink tool usepackage{graphicx} % figure insertion tool usepackage[authoryear]{natbib} % bibliography tool

One can always search for another similar packages, other than the ones that listed above, but bare in mind that there are probably thousands of packages. So you might want to do a little research on a package before decide to use it.

Other applications a used in my writing are:

• Zotero as reference manager. We have to convert the database to bibtex format, but it has an extension to work with LibreOffice or Microsoft Office.
• Evernote as web clipper
• MoU (on Mac) or Re-Text (on Ubuntu) for Markdown editor

Try LaTeX and leave “point and click” for a while. You might like it.

# Google’s {not Grey’s} Anatomy

(from personal collection)

Dear friends, I write this post related to the previous post:

Our subject today is Google Scholar. It was a a freely accessible web search engine that specialises in indexing scholarly literature across an array of publishing formats and disciplines. The beta version of it was released in November 2004.

What it does? It indexes peer-reviewed online journals of Europe and America’s largest scholarly publishers, books and other non-peer reviewed journals. Then its scope was broaden to literature entries from across the globe.

The following list is the complete list of what will show up on your screen as soon as you hit enter:

1. Articles in conventional1 peer-reviewed journals (eg: Journal of Hydrology, Journal of Environmental Earth Science, etc).
2. Articles in open access2 peer-reviewed journals (eg: Hydrology and Earth System SciencesEnvironmental Research Letters, etc)
3. Books and or e-books (eg: Time Series eBookForecast eBook)
4. Articles in conference proceedings (eg: European Geosciences UnionAmerican Geophysical Union, etc)

All the above three entries are called published materials. Number 1, 2 are your main targets and number 3 is the next best thing. You can use number 4 only if it has the full paper, not just the abstract. However, you can always cite them if you feel like you understand the abstract completely.

Whereas the following list is the non-published materials:

1. Thesis, dissertations. Authors have all the rights to upload their thesis on their blogs or other website.
2. Project reports. Some institutions make their reports available for download. Some are in the form of executive summary, but many times you would find a complete report uploaded in pdf format.
3. Newspaper articles.
4. Personal blogs (eg this blog, Budi RahardjoWaskita AdijartoKieran Healy’s blogRob Hyndman. This is another thing that I want to say. Everyday I find more and more prominent researcher maintains a blog about their work.

See you in the next post: Google’s Anatomy-2

1. Conventional journal: free for authors, but readers must pay to download
2. Open Access journal: free for readers, but authors must pay for submission

— This post was written using: Re-Text on Ubuntu 13.10 —

# An example of Markdown text file

This is an example of my short article in John Gruber’s Markdown markup using ReText on Ubuntu 13.10. You can see the output in pdf as attached. The following code is formatted by Hilite me.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 --- title: Reclaiming our water author: Dasapta Erwin Irawan date: 20 June 2014 --- Reclaiming our water ============= Did you know that Sydney Olympic Park reclaims water since 2000?} I took my daughter for a swim yesterday at The Sydney Aquatic Center. Before we go, I did a quick checked on its website to see their maintenance schedule. Then I saw an interesting information about its water management system (http://www.sopa.nsw.gov.au/our_park/environment/water) Sydney Olympic Park's water system has been managed under Water Reclamation and Management Scheme (WRAMS). The scheme was started in 2000 and was Australia’s first large-scale urban water treatment scheme. The system was following the integrated water model issued by Sydney Olympic Park Management (see the following figure). It covers not only the sport facilities but also the surrounding supporting elements: settlements, hotels and apartments. WRAMS recycles water from sewage and stormwater for irrigation, ornamental water fountains and toilet flushing applications across all the connected facilities in the park and in the suburb of Newington. This water is supplied to customers through separate meters and at a considerably low cost. Statistically, WRAMS saves more than 850 million litres of potable water yearly by avoiding its use for non-drinking purposes. Then the sewer-mining function of WRAMS treats approximately 550 million litres of sewage annually. All of this water would have been discharged to open water, otherwise. Can you imagine how is the plumbing system in that place. ![Sydney Olympic Park Integrated Water System](intwatersystem.png) What is water reclamation. It begins with the word reclaim. According to the online dictionary, it means to retrieve or recover (something) that "previously" or "potentially" lost. In this case "water lost" would be the problem. So then water reclamation is a process by which wastewater from a facility or a communal of facilities (it can be homes and/or businesses) is cleaned using biological and chemical treatment so that the water can be returned to the environment safely to keep the water balance in the system. This first small reclamation system was first introduced in 1932 in Golden Gate Park in San Francisco, while the first Australia's water recycle innitiative was started in 1977. Then it vastly develop from just a settling pond technology, chemical additive, to high-tech selective membrane. 

# Markdown: Writing starts in “plain” Re-text

Dear friends,

Don’t expect fancy stuff in this post. It’s just my way to show you how powerful “plain” text can be these days. I wrote this post using Re-Text 4.1.2 on Ubuntu 13.10.

The following text is the source Markdown text file. I’m still learning on how to use in-text ciation, inserting bibliography, in-text figure and text referencing, table of content (TOC), and list of figures/tables.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 Bibliography Part 2: Playing with your keywords. A Google Scholar examples === * Author: Dasapta Erwin Irawan(@dasaptaerwin), Andriyanti, Rizal Debrian, Iwan Setiawan * Affiliation: Department of Geology, Institut Teknologi Bandung, Indonesia * Composed using: [ReText 4.1.2](http://sourceforge.net/projects/retext/), [Linux Ubuntu 13.10](http://releases.ubuntu.com/13.10/) * How to cite: >Irawan, D., Andriyanti, Setiawan, I. and Debrian, R. (2014). Bibliography Part 2: Playing with your keywords. A Google Scholar examples. [online] My little online books. Available at: http://goo.gl/fYT7dW [Accessed {your access date}]. #1. Intro Dear friends, We've talked about how overwhelming first search is. Tonnes of links with no idea on how to screen in it. Well that's why we call it _brainstorming_ everyone ([have a look at this here](http://www.wikihow.com/Brainstorm)). This post is related to the previous post: 1. [Bibliography Part 0: Why is it important (In Indonesia language)](http://derwinirawan.wordpress.com/2013/01/14/mengapa-daftar-pustaka-penting/) 2. [Bibliography Part 1: First search is always overwhelming](http://onlinewaterbook.wordpress.com/2014/06/29/part-1-one-more-thing-we-need-to-know-about-bibliography/) I tried out these keywords on [Google Scholar](scholar.google.com) and captured the results as see in the following images: 1. geothermal west java 2. geothermal (AND) west java 3. geothermal (IN TITLE) west java #2. geothermal west java Use the above keywords if you want to see the broad image of the subject geothermal **(AND/OR)** west java. Google Scholar (Gscholar) will look for any entries with the both words online. So you would see _all_ materials with both words or individual word anywhere in the text (see Figure \ref{Figure 1}): * could be in the title, * could be in the abstract, * or it could be in the body text ![Figure 1](/media/dasapta/DATA/2014-SYDNEY/2014-blogpost/blog-bibliography/gscholar1.png "Keywords: geothermal west java") #3. geothermal (AND) west java Use these keywords with __(AND)__ operator to command Gscholar to _only_ look for materials with both words anywhere in each entries. You can see a total of 5940 results. Kind of give you a major headache doesn't it. But the first 5 to 10 result pages will show only you materials with both keywords, and then you can see that the later pages show only one of the keyword (see Figure \ref{Figure 2}). ![Figure 2](/media/dasapta/DATA/2014-SYDNEY/2014-blogpost/blog-bibliography/gscholar2.png "Keywords: geothermal (AND) west java") So there you go, your first screened Gscholar results. #4. geothermal (IN TITLE) west java Use these keywords with __(IN TITLE)__ operator to command Gscholar to _only_ look for materials with both words in the title on each entry (see see Figure \ref{Figure 3}). ![Figure 3](/media/dasapta/DATA/2014-SYDNEY/2014-blogpost/blog-bibliography/gscholar3.png "Keywords: geothermal (AND) west java") I recommend to use this operator for initial search to increase the chance of getting what you need. 

From the following attachments, we can see that Re-Text can convert md file to odt and pdf file smoothly. However for those of you that still use Ms.Word, you can use pandoc. It’s a cool way to convert md file to almost any format you can thing of, including doc format.

Herewith I attached:

1. blogbib.pdf: converted by Re-Text)
2. blogbib-html: converted by Re-Text, change the extension to html first
3. blogbib.odt: converted by Re-Text, you can open it with LibreOffice or OpenOffice
4. blogbib.doc: converted by Pandoc using pandoc blogbib.md -o blogbib.doc in your Linux/Mac terminal and Windows prompt.

# WTF: Playing with your keywords (Bibliography Part 2)

Bibliography Part 2: Playing with your keywords. A Google Scholar examples

Irawan, D., Andriyanti, Setiawan, I. and Debrian, R. (2014). Bibliography Part 2: Playing with your keywords. A Google Scholar examples. [online] My little online books. Available at: http://goo.gl/fYT7dW [Accessed {your access date}].

# 1. Intro

Dear friends,

We’ve talked about how overwhelming it is  to use un-planned keyword in your research. Tonnes of links with no idea on how to screen in it. Well that’s why we call it brainstorming (have a look at this here).

This post is related to the previous post:

I tried out these keywords on Google Scholar and captured the results as see in the following images:

1. geothermal west java
2. geothermal (AND) west java
3. geothermal (IN TITLE) west java

# 2. geothermal west java

Use the above keywords if you want to see the broad image of the subject geothermal (AND/OR) west java. Google Scholar (Gscholar) will look for any entries with the both words online. So you would see all materials with both words or individual word anywhere in the text (see Figure ref{Figure 1}):

• could be in the title,
• could be in the abstract,
• or it could be in the body text

# 3. geothermal (AND) west java

Use these keywords with (AND) operator to command Gscholar to only look for materials with both words anywhere in each entries. You can see a total of 5940 results. Kind of give you a major headache doesn’t it. But the first 5 to 10 result pages will show only you materials with both keywords, and then you can see that the later pages show only one of the keyword (see Figure ref{Figure 2}).

So there you go, your first screened Gscholar results.

# 4. geothermal (IN TITLE) west java

Use these keywords with (IN TITLE) operator to command Gscholar to only look for materials with both words in the title on each entry (see see Figure ref{Figure 3}).

I recommend to use this operator for initial search to increase the chance of getting what you need.

# #R: Simple #bibliometric comparation

**Using: Google Scholar (GS), Microsoft Academic (MSA), Scopus (SCP), and Web of Science (WOS)

Table of Contents

# Introduction

All kinds of research, researcher must have a strong understanding of preceeding research on the same or similar subject. Master and PhD student, as a kind of researcher, must compose a literature review before they hold permit to start their research. Usually we use the term literature review as a form of formal written document that summarises all previous related researches.

The general steps are:

• searching articles with certain criteria.
• published article on reputable journals.
• presented abstract on reputable conferences.
• extract the results from each article, what data is used in it, and how the author analyse it.
• summarise and compile the result to mark a baseline for your research.

However if we dig deeper, we can find that there are at least two kinds of literature review:

• Annotated bibliography: What is an annotated bibliography? These are several good definitions on the term:

An annotated bibliography provides a brief account of the available research on a given topic. It is a list of research sources that includes concise descriptions and evaluations of each source.UNSW

Another definition even gives an average sum of words:

An annotated bibliography is a list of citations to books, articles, and documents. Each citation is followed by a brief (usually about 150 words) descriptive and evaluative paragraph, the annotation. The purpose of the annotation is to inform the reader of the relevance, accuracy, and quality of the sources cited. Cornell Univ.

• Systematic review: [I will add this later on]

# Hands on

Now we get to the real part, searching for references. There are so many ways to get related readings and references. The old-fashioned way is to go to your university library. Tempting huh 🙂 I would suggest this as the best way. Not only you will get the one document that you have been looking for, but also you will feel the atmosphere in there. Although there are more online documents nowadays, but still I would sit still nlibrary (if I have time). You might by any chance get the oldest record on whatever you are looking for. Then there is always be internet as the backbone of researcher around the globe. The problem is, where to find it.

• Search Engine: Google, the most obvious man???s best friend. Off course there are others, like: Bing, Microsoft Academic and our old mate Yahoo. You might want to visit list of search engine. But be careful with using Google, because it crawls on any documents that matched with our keyword. So it could be a real scientific paper on a scientific journal, or a newsletter or simply an email in a miling list. But starting from November 2004, Google has make improvement on the matter by launching Google Scholar. Now you can get more refined result with this tools. Five years later, in December 2009, Microsoft launched Microsoft Academic. Citation database or scientific database: we???re already familiar with Scopus, Science direct, Proquest, or Web of Science. You can start with both links, since different company would likely have different database and searching algorithm. If you are working or affiliating to a university that has subscription to any of the database, then you have eliminated half of your problem :-).
• Citation database or scientific database: we are already familiar with Scopus, Science direct, Proquest, or Web of Science. You can start with both links, since different company would likely have different database and searching algorithm. If you are working or affiliating to a university that has subscription to any of the database, then you have eliminated half of your problem :-).
• Or your university has a cross-referencing system that access multiple databases in the internet. You are the lucky one :-). Just type in the keyword in it then you get more results from multiple resources. I???ll continue later on with my own case of reference searching.

# Google Scholar

add the result later

# Microsoft Academics

Following my previous post on simple bibliometric with GS Google Scholar, this time I try to do the same steps with MSA Microsoft Academic. The pros in using MSA is that it offers categorization of scientific entries. This is not available with GS. In this post I tabulated and compared each category with several keywords. Here I used the following keywords:

1. West Java
2. Bandung
3. Citarum
4. Cikapundung
5. Groundwater Bandung
6. Groundwater Citarum
7. Groundwater Cikapundung
8. Health Bandung

The following list contains the categories that automatically built by MSA:

1. Agriculture Science (agsci)
2. Arts & Humanities (arthum)
3. Biology (bio)
4. Chemistry (chem)
5. Computer Science (comsci)
6. Economics & Business (ecobus)
7. Engineering (eng)
8. Environmental Sciences (envsci)
9. Geosciences (geosci)
10. Mathematics (math)
11. Material Science (matsci)
12. Medicine (med)
13. Multidisciplinary (muldis)
14. Physics (phy)
15. Social Science (socsci)

I worked around this with the following codes.

# load library
library("lattice")
library("gridExtra")


I use LibreOffice to prepare the data. Basically every keyword consists of 15 observations (see the result from head(bib)).

# load data
bib = read.csv("20140523b-summary references.csv", header = T)
head(bib)

##   no               fields2 fields     key dbase sum
## 1  1  Agriculture Science   agsci Bandung msacd  16
## 2  2    Arts & Humanities  arthum Bandung msacd  44
## 3  3              Biology     bio Bandung msacd 129
## 4  4            Chemistry    chem Bandung msacd 153
## 5  5     Computer Science  comsci Bandung msacd 406
## 6  6 Economics & Business  ecobus Bandung msacd  44


I did the subsetting for each keyword.

# subsetting data
bib.wj = subset(bib, bib$key == "West Java") bib.bdg = subset(bib, bib$key == "Bandung")
bib.ctr = subset(bib, bib$key == "Citarum") bib.ckp = subset(bib, bib$key == "Cikapundung")
bib.gwbdg = subset(bib, bib$key == "Groundwater Bandung") bib.gwctr = subset(bib, bib$key == "Groundwater Citarum")
bib.gwckp = subset(bib, bib$key == "Groundwater Cikapundung") bib.healthbdg = subset(bib, bib$key == "Health Bandung")


I used lattice and gridExtra package for plotting. You may use another package, but you have to change the codes.

# plotting
plot1 = xyplot(bib.wj$fields ~ bib.wj$sum, pch = 21, fill = "red", xlim = c(0,
8000), main = "key: West Java")
plot2 = xyplot(bib.bdg$fields ~ bib.bdg$sum, pch = 21, fill = "red", xlim = c(0,
8000), main = "key: Bandung")
plot3 = xyplot(bib.ctr$fields ~ bib.ctr$sum, pch = 21, fill = "red", xlim = c(0,
8000), main = "key: Citarum")
grid.arrange(plot1, plot2, plot3, ncol = 3)



plot4 = xyplot(bib.gwbdg$fields ~ bib.gwbdg$sum, pch = 21, fill = "red", xlim = c(0,
50), main = "key: Groundwater Bandung")
plot5 = xyplot(bib.gwctr$fields ~ bib.gwctr$sum, pch = 21, fill = "red", xlim = c(0,
50), main = "key: Groundwater Citarum")
plot6 = xyplot(bib.healthbdg$fields ~ bib.healthbdg$sum, pch = 21, fill = "red",
xlim = c(0, 50), main = "key: Health Bandung")
grid.arrange(plot4, plot5, plot6, ncol = 3)



plot7 = xyplot(bib.ckp$fields ~ bib.ckp$sum, pch = 21, fill = "red", xlim = c(0,
10), main = "key: Cikapundung")
plot8 = xyplot(bib.gwckp$fields ~ bib.gwckp$sum, pch = 21, fill = "red", xlim = c(0,
10), main = "key: Groundwater Cikapundung")
grid.arrange(plot7, plot8, ncol = 3)


# Scopus

add the result later

# Web of Science

add the result later

Note:

• OS : Ubuntu 13.10
• R studio Version : 0.98.507
• R base Version : 3.1.0 (2014-04-10)