# data[].attributes.body
I would read the abstract first

# data[].attributes.body
do not read word for word, read abstract, and conclusion for big picture then go back to methods and data (highlight what is important)

# data[].attributes.headline
Quick read through, then carefully read the introduction and results, highlighting key phrases and annotate

# data[].attributes.subject
Quick read through, then carefully read the introduction and results, highlighting key phrases and annotate

# data[].attributes.headline
I would look at the sub titles, then just go for it. As I was reading I would look up terms that I don't recognize.

# data[].attributes.subject
I would look at the sub titles, then just go for it. As I was reading I would look up terms that I don't recognize.

# data[].attributes.body
I would read the conclusion first and keep sticky notes available. Sticky notes are extremely helpful with writing down questions and writing down words you may or may not know the answer to

# data[].attributes.headline
I've read a few papers for my lab job. I think the most important thing is to understand the introduction and abstract. Those are the most important easily. If you can understand these sections, the rest will come easy. (:

# data[].attributes.subject
I've read a few papers for my lab job. I think the most important thing is to understand the introduction and abstract. Those are the most important easily. If you can understand these sections, the rest will come easy. (:

# data[].attributes.body
read the abstract, then if that is what you are looking for, you then read the sections that are more specific to the subject you need... there are usually labels

# data[].attributes.headline
read the title first and introduction/conclusion fully ... skim the body and look close at data 

# data[].attributes.subject
read the title first and introduction/conclusion fully ... skim the body and look close at data 

# data[].attributes.body
I skip the introduction and conclusion and focus on the bulk of what i need to know

# data[].attributes.headline
I will read the introduction, abstract, and result. I will check techniques used in the paper on the Internet.

# data[].attributes.subject
I will read the introduction, abstract, and result. I will check techniques used in the paper on the Internet.

# data[].attributes.body
skim any other parts that you feel is necessary for your topic

# data[].attributes.body
I like to read the abstract first because it gives me a good summary as to what the paper is about. If I'm looking for a specific topic, I can use the table of contents or even command f to search a specific word or phrase.

# data[].attributes.body
I usually go straight to the graphs, and then try and fill in with context from there

# data[].attributes.headline
The abstract first would be my strategy, then maybe the introduction. Then go to the conclusion, and go back and try to find significant graphs or figures.

# data[].attributes.subject
The abstract first would be my strategy, then maybe the introduction. Then go to the conclusion, and go back and try to find significant graphs or figures.

# data[].attributes.headline
Figure out what the reading is about before actually reading it

# data[].attributes.subject
Figure out what the reading is about before actually reading it

# data[].attributes.headline
read the abstracts and any headings or conclusions 

# data[].attributes.subject
read the abstracts and any headings or conclusions 

# data[].attributes.headline
Read the abstract! And be prepared to read the paper a few times.

# data[].attributes.subject
Read the abstract! And be prepared to read the paper a few times.

# data[].attributes.headline
read the abstract and first page, skim for relevant information

# data[].attributes.subject
read the abstract and first page, skim for relevant information

# data[].attributes.body
1st to understand the basic structure
2nd to understand the details of things
3rd is to understand the greater meaning of the paper other than the details

# data[].attributes.headline
read abstract, skim headings, read first and last sentences not entire thing

# data[].attributes.subject
read abstract, skim headings, read first and last sentences not entire thing

# data[].attributes.body
reading the abstract first then the conclusions

# data[].attributes.headline
Read quickly and skim but then go through it thouroughly

# data[].attributes.subject
Read quickly and skim but then go through it thouroughly

# data[].attributes.headline
Read the abstract, intro, and discussion

# data[].attributes.subject
Read the abstract, intro, and discussion

# data[].attributes.body
Then I usually read the introduction to get background information. Usually I read the results (checked with methods section) and discussion

# data[].attributes.headline
Read the abstract, look at the topic and authors (to see if it fits what you're looking for), and decide if it applies to your project.

# data[].attributes.subject
Read the abstract, look at the topic and authors (to see if it fits what you're looking for), and decide if it applies to your project.

# data[].attributes.headline
read the title, abstract, introduction, then go on

# data[].attributes.subject
read the title, abstract, introduction, then go on

# data[].attributes.body
I just read the abstract, conclusion, method, and data collection process

# data[].attributes.headline
Read the abstract, title, subtitles, etc

# data[].attributes.subject
Read the abstract, title, subtitles, etc

# data[].attributes.body
I try reading the abstract and find out if it has information that I need.

# data[].attributes.headline
Quick read through of the whole text, and then dive in and annotate/cover challenging subjects. Highlight and review vocab. 

# data[].attributes.subject
Quick read through of the whole text, and then dive in and annotate/cover challenging subjects. Highlight and review vocab. 

# data[].attributes.headline
I skim the article and read the abstract, and then read the article more in depth

# data[].attributes.subject
I skim the article and read the abstract, and then read the article more in depth