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Introduction
Data are a set of facts, and provide a partial picture of real-
ity. Whether data are being collected with a certain purpose or
collected data are being utilized, questions regarding what in-
formation the data are conveying, how the data can be used, and
what must be done to include more useful information must
constantly be kept in mind.
Since most data are available to researchers in a raw format,
they must be summarized, organized, and analyzed to usefully
derive information from them. Furthermore, each data set needs
to be presented in a certain way depending on what it is used
for. Planning how the data will be presented is essential before
appropriately processing raw data.
First, a question for which an answer is desired must be
clearly defined. The more detailed the question is, the more
detailed and clearer the results are. A broad question results in
vague answers and results that are hard to interpret. In other
words, a well-defined question is crucial for the data to be well-
understood later. Once a detailed question is ready, the raw data
must be prepared before processing. These days, data are often
summarized, organized, and analyzed with statistical packages
or graphics software. Data must be prepared in such a way they
are properly recognized by the program being used. The pres-
ent study does not discuss this data preparation process, which
involves creating a data frame, creating/changing rows and col-
umns, changing the level of a factor, categorical variable, coding,
dummy variables, variable transformation, data transformation,
missing value, outlier treatment, and noise removal.
We describe the roles and appropriate use of text, tables, and
graphs (graphs, plots, or charts), all of which are commonly used
in reports, articles, posters, and presentations. Furthermore, we
Statistical Round
Data are usually collected in a raw format and thus the inherent information is difficult to understand. Therefore, raw
data need to be summarized, processed, and analyzed. However, no matter how well manipulated, the information de-
rived from the raw data should be presented in an effective format, otherwise, it would be a great loss for both authors
and readers. In this article, the techniques of data and information presentation in textual, tabular, and graphical forms
are introduced. Text is the principal method for explaining findings, outlining trends, and providing contextual informa-
tion. A table is best suited for representing individual information and represents both quantitative and qualitative infor-
mation. A graph is a very effective visual tool as it displays data at a glance, facilitates comparison, and can reveal trends
and relationships within the data such as changes over time, frequency distribution, and correlation or relative share of a
whole. Text, tables, and graphs for data and information presentation are very powerful communication tools. They can
make an article easy to understand, attract and sustain the interest of readers, and efficiently present large amounts of
complex information. Moreover, as journal editors and reviewers glance at these presentations before reading the whole
article, their importance cannot be ignored.
Key Words: Data presentation, Data visualization, Graph, Statistics, Table.
Statistical data presentation
Junyong In1 and Sangseok Lee2
Department of Anesthesiology and Pain Medicine, 1Dongguk University Ilsan Hospital, Goyang, 2Sanggye Paik
Hospital, Inje University College of Medicine, Seoul, Korea
CC This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/
licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright ⓒ the Korean Society of Anesthesiologists, 2017 Online access in http://ekja.org
pISSN 2005-6419 • eISSN 2005-7563
Korean Journal of Anesthesiology
KJA
Corresponding author: Sangseok Lee, M.D.
Department of Anesthesiology and Pain Medicine, Sanggye Paik
Hospital, Inje University College of Medicine, 1342, Dongil-ro,
Nowon-gu, Seoul 01757, Korea
Tel: 82-2-950-1171, Fax: 82-2-950-1323
Email: s2248@paik.ac.kr
ORCID: http://orcid.org/0000-0001-7023-3668
Received: March 20, 2017.
Accepted: April 4, 2017.
Korean J Anesthesiol 2017 June 70(3): 267-276
https://doi.org/10.4097/kjae.2017.70.3.267
268 Online access in http://ekja.org
VOL. 70, NO. 3, JuNe 2017
Data presentation
discuss the issues that must be addressed when presenting vari-
ous kinds of information, and effective methods of presenting
data, which are the end products of research, and of emphasiz-
ing specific information.
Data Presentation
Data can be presented in one of the three ways:
– as text;
– in tabular form; or
– in graphical form.
Methods of presentation must be determined according
to the data format, the method of analysis to be used, and the
information to be emphasized. Inappropriately presented data
fail to clearly convey information to readers and reviewers.
Even when the same information is being conveyed, different
methods of presentation must be employed depending on what
specific information is going to be emphasized. A method of
presentation must be chosen after carefully weighing the advan-
tages and disadvantages of different methods of presentation.
For easy comparison of different methods of presentation, let us
look at a table (Table 1) and a line graph (Fig. 1) that present the
same information [1]. If one wishes to compare or introduce two
values at a certain time point, it is appropriate to use text or the
written language. However, a table is the most appropriate when
all information requires equal attention, and it allows readers
to selectively look at information of their own interest. Graphs
allow readers to understand the overall trend in data, and intui-
tively understand the comparison results between two groups.
One thing to always bear in mind regardless of what method is
used, however, is the simplicity of presentation.
Text presentation
Text is the main method of conveying information as it is
used to explain results and trends, and provide contextual infor-
mation. Data are fundamentally presented in paragraphs or sen-
tences. Text can be used to provide interpretation or emphasize
certain data. If quantitative information to be conveyed consists
of one or two numbers, it is more appropriate to use written lan-
guage than tables or graphs. For instance, information about the
incidence rates of delirium following anesthesia in 2016–2017
can be presented with the use of a few numbers: “The incidence
rate of delirium following anesthesia was 11% in 2016 and 15%
in 2017; no significant difference of incidence rates was found
between the two years.” If this information were to be presented
in a graph or a table, it would occupy an unnecessarily large
space on the page, without enhancing the readers’ understand-
ing of the data. If more data are to be presented, or other infor-
mation such as that regarding data trends are to be conveyed, a
table or a graph would be more appropriate. By nature, data take
longer to read when presented as texts and when the main text
includes a long list of information, readers and reviewers may
have difficulties in understanding the information.
Table 1. Modified Table in Lee and Kim’s Research (Adapted from Korean J Anesthesiol 2017; 70: 39-45)
Var iabl e Group Baseline After drug 1 min 3 min 5 min
SBP C 135.1 ± 13.4 139.2 ± 17.1 186.0 ± 26.6*160.1 ± 23.2*140.7 ± 18.3
D 135.4 ± 23.8 131.9 ± 13.5 165.2 ± 16.2*,
‡
127.9 ± 17.5
‡
108.4 ± 12.6
†
,
‡
DBP C 79.7 ± 9.8 79.4 ± 15.8 104.8 ± 14.9*87.9 ± 15.5*78.9 ± 11.6
D 76.7 ± 8.3 78.4 ± 6.3 97.0 ± 14.5*74.1 ± 8.3
‡
66.5 ± 7.2
†
,
‡
MBP C 100.3 ± 11.9 103.5 ± 16.8 137.2 ± 18.3*116.9 ± 16.2*103.9 ± 13.3
D 97.7 ± 14.9 98.1 ± 8.7 123.4 ± 13.8*,
‡
95.4 ± 11.7
‡
83.4 ± 8.4
†
,
‡
Values are expressed as mean ± SD. Group C: normal saline, Group D: dexmedetomidine. SBP: systolic blood pressure, DBP: diastolic blood pressure,
MBP: mean blood pressure, HR: heart rate. *P < 0.05 indicates a significant increase in each group, compared with the baseline values.
†
P < 0.05
indicates a significant decrease noted in Group D, compared with the baseline values.
‡
P < 0.05 indicates a significant difference between the groups.
Fig. 1. Line graph with whiskers. Changes in systolic blood pressure (SBP)
in the two groups. Group C: normal saline, Group D: dexmedetomidine.
*P < 0.05 indicates a significant increase in each group, compared with
the baseline values.
†
P < 0.05 indicates a significant decrease noted
in Group D, compared with the baseline values.
‡
P < 0.05 indicates
a significant difference between the groups (Adapted from Korean J
Anesthesiol 2017; 70: 39-45).
0
250
200
150
100
50
Baseline
SBP (mmHg)
Periods
After drug 1 min 3 min 5 min
Group C
Group D
*
,
*
*,
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KOReAN J ANeSTHeSIOL In and Lee
Table presentation
Tables, which convey information that has been converted
into words or numbers in rows and columns, have been used for
nearly 2,000 years. Anyone with a sufficient level of literacy can
easily understand the information presented in a table. Tables
are the most appropriate for presenting individual information,
and can present both quantitative and qualitative information.
Examples of qualitative information are the level of sedation [2],
statistical methods/functions [3,4], and intubation conditions
[5].
The strength of tables is that they can accurately present
information that cannot be presented with a graph. A number
such as “132.145852” can be accurately expressed in a table.
Another strength is that information with different units can
be presented together. For instance, blood pressure, heart rate,
number of drugs administered, and anesthesia time can be
presented together in one table. Finally, tables are useful for
summarizing and comparing quantitative information of differ-
ent variables. However, the interpretation of information takes
longer in tables than in graphs, and tables are not appropriate
for studying data trends. Furthermore, since all data are of equal
importance in a table, it is not easy to identify and selectively
choose the information required.
For a general guideline for creating tables, refer to the journal
submission requirements1).
Heat maps for better visualization of information than tables
Heat maps help to further visualize the information pre-
sented in a table by applying colors to the background of cells.
By adjusting the colors or color saturation, information is con-
veyed in a more visible manner, and readers can quickly identify
the information of interest (Table 2). Software such as Excel (in
Microsoft Office, Microsoft, WA, USA) have features that enable
easy creation of heat maps through the options available on the
“conditional formatting” menu.
Graph presentation
Whereas tables can be used for presenting all the informa-
tion, graphs simplify complex information by using images and
emphasizing data patterns or trends, and are useful for summa-
rizing, explaining, or exploring quantitative data. While graphs
are effective for presenting large amounts of data, they can be
used in place of tables to present small sets of data. A graph for-
mat that best presents information must be chosen so that read-
ers and reviewers can easily understand the information. In the
following, we describe frequently used graph formats and the
types of data that are appropriately presented with each format
with examples.
Scatter plot
Scatter plots present data on the x- and y-axes and are used
to investigate an association between two variables. A point
represents each individual or object, and an association between
two variables can be studied by analyzing patterns across mul-
tiple points. A regression line is added to a graph to determine
whether the association between two variables can be explained
or not. Fig. 2 illustrates correlations between pain scoring sys-
tems that are currently used (PSQ, Pain Sensitivity Question-
naire; PASS, Pain Anxiety Symptoms Scale; PCS, Pain Catastro-
phizing Scale) and Geop-Pain Questionnaire (GPQ) with the
correlation coefficient, R, and regression line indicated on the
scatter plot [6]. If multiple points exist at an identical location as
in this example (Fig. 2), the correlation level may not be clear.
In this case, a correlation coefficient or regression line can be
added to further elucidate the correlation.
Bar graph and histogram
A bar graph is used to indicate and compare values in a
discrete category or group, and the frequency or other measure-
ment parameters (i.e. mean). Depending on the number of cat-
egories, and the size or complexity of each category, bars may be
created vertically or horizontally. The height (or length) of a bar
represents the amount of information in a category. Bar graphs
are flexible, and can be used in a grouped or subdivided bar for-
mat in cases of two or more data sets in each category. Fig. 3 is
a representative example of a vertical bar graph, with the x-axis
representing the length of recovery room stay and drug-treated
group, and the y-axis representing the visual analog scale (VAS)
score. The mean and standard deviation of the VAS scores are
expressed as whiskers on the bars (Fig. 3) [7].
1)Instructions to authors in KJA; section 5-(9) Table; https://ekja.org/index.
php?body=instruction
Table 2. Difference between a Regular Table and a Heat Map
Example of a regular table Example of a heat map
SBP DBP MBP HR SBP DBP MBP HR
128 66 87 87 128 66 87 87
125 43 70 85 125 43 70 85
114 52 68 103 114 52 68 103
111 44 66 79 111 44 66 79
139 61 81 90 139 61 81 90
103 44 61 96 103 44 61 96
94 47 61 83 94 47 61 83
All numbers were created by the author. SBP: systolic blood pressure,
DBP: diastolic blood pressure, MBP: mean blood pressure, HR: heart
rate.
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VOL. 70, NO. 3, JuNe 2017
Data presentation
By comparing the endpoints of bars, one can identify the
largest and the smallest categories, and understand gradual dif-
ferences between each category. It is advised to start the x- and
y-axes from 0. Illustration of comparison results in the x- and y-
axes that do not start from 0 can deceive readers’ eyes and lead
to overrepresentation of the results.
One form of vertical bar graph is the stacked vertical bar
graph. A stack vertical bar graph is used to compare the sum
of each category, and analyze parts of a category. While stacked
vertical bar graphs are excellent from the aspect of visualization,
they do not have a reference line, making comparison of parts of
various categories challenging (Fig. 4) [8].
Pie chart
A pie chart, which is used to represent nominal data (in other
words, data classified in different categories), visually represents
a distribution of categories. It is generally the most appropriate
format for representing information grouped into a small num-
ber of categories. It is also used for data that have no other way
Fig. 2. Scatter plot of GPQ scores and the other questionnaires. Score 1: sensitivity, 2: experience, 3: other. GPQ: Geop-Pain Questionnaire, PSQ: Pain
Sensitivity Questionnaire, PASS: Pain Anxiety Symptoms Scale, PCS: Pain Catastrophizing Scale (Adapted from Korean J Anesthesiol 2016; 69:
492-505).
0
25
20
15
10
5
060 120
PSQ score
15030
GPQ score 1
90
0
25
20
15
10
5
040
PASS score
8020
GPQ score 2
60
0
25
20
15
10
5
020 40
PCS score
5010
GPQ score 3
30
0
70
60
50
40
30
20
10
060 120
PSQ score
15030
GPQ total score
90
0
70
60 60
50 50
40 40
30 30
20 20
10 10
040
PASS score
8020
GPQ total score
60
0
70
020 40
PCS score
5010 30
GPQ total score
r=0.296 (P = 0.002) r=0.625 (P < 0.001) r=0.627 (P < 0.001)
r=0.294 (P = 0.002) r=0.647 (P < 0.001) r=0.621 (P < 0.001)
Fig. 3. Multiple bar graph with whiskers. Pain scores in the recovery
room. *P < 0.05 compared with the control group. The nefopam group
showed significant lower visual analogue scale (VAS) score at 0, 5, 15, 30,
45 and 60 minutes on postanesthesia care unit compared with the control
group (Adapted from Korean J Anesthesiol 2016; 69: 480-6. Fig. 2).
0
6
5
4
3
2
1
05
VAS score
Time after surgery in PACU (min)
15 30 45 60
*
Control
Nefopam
Ketamine
*
*
*
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KOReAN J ANeSTHeSIOL In and Lee
of being represented aside from a table (i.e. frequency table).
Fig. 5 illustrates the distribution of regular waste from operation
rooms by their weight [8]. A pie chart is also commonly used to
illustrate the number of votes each candidate won in an election.
Line plot with whiskers
A line plot is useful for representing time-series data such
as monthly precipitation and yearly unemployment rates; in
other words, it is used to study variables that are observed over
time. Line graphs are especially useful for studying patterns and
trends across data that include climatic influence, large changes
or turning points, and are also appropriate for representing not
only time-series data, but also data measured over the progres-
sion of a continuous variable such as distance. As can be seen in
Fig. 1, mean and standard deviation of systolic blood pressure
are indicated for each time point, which enables readers to easily
understand changes of systolic pressure over time [1]. If data are
collected at a regular interval, values in between the measure-
ments can be estimated. In a line graph, the x-axis represents
the continuous variable, while the y-axis represents the scale
and measurement values. It is also useful to represent multiple
data sets on a single line graph to compare and analyze patterns
across different data sets.
Box and whisker chart
A box and whisker chart does not make any assumptions
about the underlying statistical distribution, and represents
variations in samples of a population; therefore, it is appropri-
ate for representing nonparametric data. AA box and whisker
chart consists of boxes that represent interquartile range (one
Fig. 4. Stacked bar graph. Compressed volume of each component
from the three operations. We checked the compressed volume of each
component from the three operations; pelviscopy (with radical vaginal
hysterectomy), laparoscopic anterior resection of the colon, and TKRA.
TKRA: total knee replacement arthroplasty, RMW: regulated medical
waste (Adapted from Korean J Anesthesiol 2017; 70: 100-4).
0
200
150
100
50
Pelviscopy Colon resection
Compressed volume (L)
TKRA
Cardboard
Plastics
Clear wrap
Blue wrap
RMW
Fig. 5. Pie chart. Total weight of each component from the three
operations. RMW: regulated medical waste (Adapted from Korean J
Anesthesiol 2017; 70: 100-4).
RMW
Blue wrap
Clear wrap
Plastics
Cardboard
29,344 g
2,102 g
2,838 g
2,388 g
1,564 g
Fig. 6. Box graph with whiskers. This graph is a standardized way of
displaying the distribution of data based on the five-number summary;
minimum, first quartile, median, third quartile, and maximum. The
central rectangle represents from the first quartile to the third quartile
(the interquartile range [IQR]). A segment inside the rectangle shows
the median and "whiskers" above and below the box show the locations
of the minimum and maximum.
Maximum
75th percentile
Mean
Median
25th percentile
Minimum
+
Fig. 7. Box graph with whiskers. Calculated volume of desflurane
consumed during the observation period. The groups differed
significantly. Data are expressed as median, minimum, first inter-
quartile, third interquartile, and maximum values. *P < 0.05 (Adapted
from Korean J Anesthesiol 2017; 70: 27-32).
0
60
40
20
Control Droperidol
Calculated amount of consumption
volume of desflurane (ml)
*
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Data presentation
to three), the median and the mean of the data, and whiskers
presented as lines outside of the boxes. Whiskers can be used to
present the largest and smallest values in a set of data or only a
part of the data (i.e. 95% of all the data). Data that are excluded
from the data set are presented as individual points and are
called outliers. The spacing at both ends of the box indicates
Fig. 8. Simple pie chart (A) versus 3D pie
chart (B). In the 3D pie chart, slices at
the rear of the chart appear smaller than
those at the front because of the false
perspective.
A
BA C D E
Cause of death
B
Cause of death
BA C D E
Fig. 9. Clarification of a graph. Virtual data are presented as mean with standard deviations. (A) A graph with default settings. (B) The axes are
separated from each other. The data at 0 are displayed clearly. (C) The points and whiskers are jittered to avoid overlapping. Although one side of the
whiskers are removed, it is still easy to understand. However, this graph still has unnecessary blank space. (D) The lines are expressed in various ways.
A break is put in the y-axis. MBP: mean blood pressure.
0
120
60
50
40
30
20
10
0123
MBP (mmHg)
Time (h)
4
A
Group A
Group B
Group C
120
100
80
60
40
20
123
MBP (mmHg)
Time (h)
4
C
Group A
Group B
Group C
110
100
90
80
70
0
0
120
110
100
90
80
70
60
50
40
30
20
10
123
MBP (mmHg)
Time (h)
4
B
120
100
80
60
123
MBP (mmHg)
Time (h)
4
D
Group A
Group B
Group C
Group A
Group B
Group C
0
0
0
0
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KOReAN J ANeSTHeSIOL In and Lee
dispersion in the data. The relative location of the median dem-
onstrated within the box indicates skewness (Fig. 6). The box
and whisker chart provided as an example represents calculated
volumes of an anesthetic, desflurane, consumed over the course
of the observation period (Fig. 7) [9].
Three-dimensional effects
Most of the recently introduced statistical packages and
graphics software have the three-dimensional (3D) effect feature.
The 3D effects can add depth and perspective to a graph. How-
ever, since they may make reading and interpreting data more
difficult, they must only be used after careful consideration. The
application of 3D effects on a pie chart makes distinguishing the
size of each slice difficult. Even if slices are of similar sizes, slices
farther from the front of the pie chart may appear smaller than
the slices closer to the front (Fig. 8).
Drawing a graph: example
Finally, we explain how to create a graph by using a line
graph as an example (Fig. 9). In Fig. 9, the mean values of arte-
rial pressure were randomly produced and assumed to have
been measured on an hourly basis. In many graphs, the x- and
y-axes meet at the zero point (Fig. 9A). In this case, informa-
tion regarding the mean and standard deviation of mean arte-
rial pressure measurements corresponding to t = 0 cannot be
conveyed as the values overlap with the y-axis. The data can be
clearly exposed by separating the zero point (Fig. 9B). In Fig.
9B, the mean and standard deviation of different groups overlap
and cannot be clearly distinguished from each other. Separat-
ing the data sets and presenting standard deviations in a single
direction prevents overlapping and, therefore, reduces the visual
inconvenience. Doing so also reduces the excessive number of
Fig. 10. An example of misleading graphs. Both plots use the same data set. (A) The readers might be thinking that the heart rates at 1 min are higher
than others. (B) The heart rates are very stable during the study. The readers should check the scale of the y-axis and baseline values when they look at
the graphs.
90
80
After drug 1 min 3 min
Heart rate (beats/min)
Periods
5 min
A
Group C
Group D
Baseline
70
100
50
After drug 1 min 3 min
Heart rate (beats/min)
Periods
5 min
B
Group C
Group D
0
Baseline
Table 3. Types of Charts depending on the Method of Analysis of the Data
Analysis Subgroup Number of variables Typ e
Comparison Among items Two per items Variable width column chart
One per item Bar/column chart
Over time Many periods Circular area/line chart
Few periods Column/line chart
Relationship Tw o Scatter chart
Three Bubble chart
Distribution Single Column/line histogram
Two Scatter chart
Three Three-dimensional area chart
Comparison Changing over time Only relative differences matter Stacked 100% column chart
Relative and absolute differences matter Stacked column chart
Static Simple share of total Pie chart
Accumulation Waterfall chart
Components of components Stacked 100% column chart with subcomponents
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VOL. 70, NO. 3, JuNe 2017
Data presentation
ticks on the y-axis, increasing the legibility of the graph (Fig.
9C). In the last graph, different shapes were used for the lines
connecting different time points to further allow the data to be
distinguished, and the y-axis was shortened to get rid of the un-
necessary empty space present in the previous graphs (Fig. 9D).
A graph can be made easier to interpret by assigning each group
to a different color, changing the shape of a point, or including
graphs of different formats [10]. The use of random settings for
the scale in a graph may lead to inappropriate presentation or
presentation of data that can deceive readers’ eyes (Fig. 10).
Owing to the lack of space, we could not discuss all types of
graphs, but have focused on describing graphs that are frequent-
ly used in scholarly articles. We have summarized the commonly
used types of graphs according to the method of data analysis in
Table 3. For general guidelines on graph designs, please refer to
the journal submission requirements2).
Conclusions
Text, tables, and graphs are effective communication media
that present and convey data and information. They aid readers
in understanding the content of research, sustain their interest,
and effectively present large quantities of complex information.
As journal editors and reviewers will scan through these pre-
sentations before reading the entire text, their importance can-
not be disregarded. For this reason, authors must pay as close
attention to selecting appropriate methods of data presentation
as when they were collecting data of good quality and analyzing
them. In addition, having a well-established understanding of
different methods of data presentation and their appropriate use
will enable one to develop the ability to recognize and interpret
inappropriately presented data or data presented in such a way
that it deceives readers’ eyes [11].
ORCID
Junyong In, http://orcid.org/0000-0001-7403-4287
Sangseok Lee, http://orcid.org/0000-0001-7023-3668
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KOReAN J ANeSTHeSIOL In and Lee
Appendix
Output for Presentation
Discovery and communication are the two objectives of data
visualization. In the discovery phase, various types of graphs
must be tried to understand the rough and overall information
the data are conveying. The communication phase is focused on
presenting the discovered information in a summarized form.
During this phase, it is necessary to polish images including
graphs, pictures, and videos, and consider the fact that the imag-
es may look different when printed than how appear on a com-
puter screen. In this appendix, we discuss important concepts
that one must be familiar with to print graphs appropriately.
The KJA asks that pictures and images meet the following
requirement before submission3)
“Figures and photographs should be submitted as ‘TIFF’
files. Submit files of figures and photographs separately from
the text of the paper. Width of figure should be 84 mm (one
column). Contrast of photos or graphs should be at least 600
dpi. Contrast of line drawings should be at least 1,200 dpi.
The Powerpoint file (ppt, pptx) is also acceptable.”
Unfortunately, without sufficient knowledge of computer
graphics, it is not easy to understand the submission require-
ment above. Therefore, it is necessary to develop an understand-
ing of image resolution, image format (bitmap and vector im-
ages), and the corresponding file specifications.
Resolution
Resolution is often mentioned to describe the quality of im-
ages containing graphs or CT/MRI scans, and video files. The
higher the resolution, the clearer and closer to reality the im-
age is, while the opposite is true for low resolutions. The most
representative unit used to describe a resolution is “dpi” (dots
per inch): this literally translates to the number of dots required
to constitute 1 inch. The greater the number of dots, the higher
the resolution. The KJA submission requirements recommend
600 dpi for images, and 1,200 dpi4) for graphs. In other words,
resolutions in which 600 or 1,200 dots constitute one inch are
required for submission.
There are requirements for the horizontal length of an image
in addition to the resolution requirements. While there are no
requirements for the vertical length of an image, it must not ex-
ceed the vertical length of a page. The width of a column on one
side of a printed page is 84 mm, or 3.3 inches (84/25.4 mm
≒
3.3
inches). Therefore, a graph must have a resolution in which 1,200
dots constitute 1 inch, and have a width of 3.3 inches.
Bitmap and Vector
Methods of image construction are important. Bitmap im-
ages can be considered as images drawn on section paper. En-
larging the image will enlarge the picture along with the grid,
resulting in a lower resolution; in other words, aliasing occurs.
On the other hand, reducing the size of the image will reduce
the size of the picture, while increasing the resolution. In other
words, resolution and the size of an image are inversely propor-
tionate to one another in bitmap images, and it is a drawback of
bitmap images that resolution must be considered when adjust-
ing the size of an image. To enlarge an image while maintaining
the same resolution, the size and resolution of the image must be
determined before saving the image. An image that has already
been created cannot avoid changes to its resolution according to
changes in size. Enlarging an image while maintaining the same
resolution will increase the number of horizontal and vertical
dots, ultimately increasing the number of pixels5) of the image,
and the file size. In other words, the file size of a bitmap image is
affected by the size and resolution of the image (file extensions
include JPG [JPEG]6), PNG7), GIF8), and TIF [TIFF]9). To avoid
this complexity, the width of an image can be set to 4 inches and
its resolution to 900 dpi to satisfy the submission requirements
of most journals [12].
Vector images overcome the shortcomings of bitmap images.
Vector images are created based on mathematical operations of
line segments and areas between different points, and are not
affected by aliasing or pixelation. Furthermore, they result in a
smaller file size that is not affected by the size of the image. They
are commonly used for drawings and illustrations (file exten-
sions include EPS10), CGM11), and SVG12)).
Finally, the PDF13) is a file format developed by Adobe Sys-
tems (Adobe Systems, San Jose, CA, USA) for electronic docu-
ments, and can contain general documents, text, drawings,
images, and fonts. They can also contain bitmap and vector im-
ages. While vector images are used by researchers when working
3)Instructions to Authors in KJA; section 6-1)-(10) Figures and illustrations
in Manuscript preparation; https://ekja.org/index.php?body=instruction
4)Resolution; in KJA, it is represented by “contrast.”
5)Pixel is a minimum unit of an image and contains information of a
dot and color. It is derived by multiplying the number of vertical and
horizontal dots regardless of image size. For example, Full High Definition
(FHD) monitor has 1920 × 1080 dots
≒
2.07 million pixel.
6)Joint Photographic Experts Group.
7)Portable Network Graphics.
8)Graphics Interchange Format
9)Tagged Image File Format; TIFF
10)Encapsulated PostScript.
11)Computer Graphics Metafile.
12)Scalable Vector Graphics.
13)Portable Document Format.
276 Online access in http://ekja.org
VOL. 70, NO. 3, JuNe 2017
Data presentation
in Powerpoint, they are saved as 960 × 720 dots when saved in
TIFF format in Powerpoint. This results in a resolution that is
inappropriate for printing on a paper medium. To save high-
resolution bitmap images, the image must be saved as a PDF file
instead of a TIFF, and the saved PDF file must be imported into
an imaging processing program such as PhotoshopTM (Adobe
Systems, San Jose, CA, USA) to be saved in TIFF format [12].
