Video summary

20230911 KSDC DB & ICPSR 온라인 이용교육(한국과학기술원)

Main summary

Key takeaways

Educational

Main ideas & lessons

1) What KSTC / KSTCTV and ICPSR are (and who they’re for)

  • KSTC (Korea Social Science Data Center) is positioned as a source of credible quantitative social science data, especially survey data and statistical data.
  • ICPSR is presented as a major international quantitative data archive containing survey data from around the world.
  • Both are framed as resources for researchers who need:
    • pre-existing quantitative data (survey/statistics),
    • and, in KSTC’s case, tools to analyze data and run surveys online.

2) Training schedule / structure

  • Total session: 1.5 hours (2:00 PM–3:30 PM)
    • 2:00–3:00: Domestic database KSTC / KSTCTV
    • 3:00–3:30: International database ICPSR

KSTC (KSTCTV) section: key concepts & workflow

A) Login and access method

Goal: access KSTCTV via the KAIST Library site so you’re recognized as logged in.

On campus

  1. Go to KAIST Library homepage
  2. Navigate: Electronic Resources → Databases
  3. Choose the letter “K” and select KSTCTV
  4. Click the KSTCTV URL directly
  5. A “Welcome to KAIST” message appears; being able to use the DB indicates you’re logged in.

Off campus (home/cafe)

  • First log in to KAIST Library homepage
  • Then access KSTCTV the same way and use it.

Check-in instructions during training

  • Participants were asked to:
    • confirm audio (“Can you hear my voice?”) via chat
    • after login, send “Login complete” in chat

B) Overview of KSTCTV database structure (DB menus)

After login as a user (speaker refers to “DBA”), there are four main menus:

  • 1) Find Data
  • 2) Online Analyst (Online Statistical Analysis)
  • 3) Online Survey
  • (The fourth menu is not clearly described in the provided subtitles.)

C) “Find Data” → Survey Data (how to find + what you can download)

What it contains

  • About 2,500 sets of survey data produced in Korea
  • Produced by institutions such as:
    • research institutes, public institutions, government, media outlets, etc.

Search methods

  • Search by survey name / keyword
    • Example keyword: “values”
    • Results show a survey list and download/analysis icons.

Meaning of result icons (download/analysis options)

  • Purple icon: download questionnaire
  • Light blue icon: download survey report generated from the data
  • Green icon: download raw data (primarily SPSS/Excel formats)
  • Orange icon: data usable for analysis via List 3.0 (online statistical tool within the KSTCTV environment; the speaker mainly demonstrates EST 3.0 later)

Example flow demonstrated

  1. Open a survey such as “2022 Korean Consciousness and Values”
  2. Check survey overview info (e.g., sample size, organization, purpose)
  3. View questionnaire online (View Questionnaire)
    • Example shown: Question 6 about attitudes toward marriage (three options)
  4. Download materials from the survey page:
    • questionnaire/report/codebook
    • raw data in SPSS/Excel
  5. Perform analysis:
    • Use Statistical Analysis 3.0 (EST 3.0)

D) EST 3.0 (KSTCTV online statistics): demonstrated analyses

What EST 3.0 is

  • An online statistical analysis program provided by KSTCTV (EST 3.0, developed in-house).
  • Presented as avoiding the need to purchase/use expensive statistical software like SPSS.

Method 1: Frequency analysis (single question)

Purpose

  • Create frequency tables (counts and percentages) for survey responses.

Steps (as shown)

  • Choose Frequency Analysis
  • Select Question 6
  • Move it into the selected variables using arrow buttons
  • Set graph settings if needed
  • Click Analyze

Output

  • Frequency table (e.g., total respondents 5,100)
  • Percentage breakdown by option
  • Graph shown below

Export options

  • Save results as files (speaker mentions Hangul, Excel, PPT, PDF, JPG)
  • Save graphs as well

Method 2: Cross-tabulation (grouping variable, e.g., gender)

Purpose

  • Break down response frequencies by another variable.

Steps (as shown)

  • Use cross-tabulation:
    • Put gender (Question 3) into row variables
    • Put Question 6 into column variable
    • Click Analyze

Output

  • Cross-analysis table split by gender
  • Discussion of differing percentages between men vs women

Statistical significance discussion (null hypothesis + chi-square test)

  • Null hypothesis: “no difference” / not statistically significant
  • Research hypothesis: “difference” / statistically significant
  • Chi-square test (Pearson Chi-Square)
    • In EST 3.0, the speaker instructs:
      • locate the “Chi-Square …” section near the top of the Analyze process
      • check the relevant box
      • run Analyze again to get a test-statistics table
  • Rule of thumb
    • typical significance level = 0.05
    • if p-value < 0.05, the result is statistically significant
  • Example result:
    • p-value shown as 0.000
    • interpreted as a statistically significant gender difference

E) Additional KSTCTV “Find Data” tools beyond survey data

Survey item search

  • Search for specific survey items/questions by keyword across the ~2,500 surveys
  • Example:
    • keyword “health” → ~480 items found
  • Lets users view option scales and how other researchers structured items.

Topic-based search

  • Surveys are grouped into 16 themes
  • Example:
    • topic “politics” → ~280 records

Series data (repeated surveys over time)

  • “Series” = the same survey repeated at regular intervals
  • Example given:
    • World Values Survey
  • Speaker notes:
    • data for seven World Values conferences in Korea were uploaded
    • for other countries, users can use a WBS integrated country file download/link

F) KSTCTV “Statistical Data” (time-series numerical data)

What it is

  • About 1,900 statistical records
  • Produced periodically by credible institutions
  • Includes:
    • government ministries/public corporations/National Statistical Office (domestic)
    • UN, OECD (international)

Search + filtering workflow (as shown)

  1. Go to Statistical Data
  2. Use Statistical Search
  3. Select data sets by keywords:
    • example 1: “travel” → “Number of Overseas Travelers”
    • example 2: “Gross National Income” → “Gross National Income per capita”
  4. Click Check Data
  5. Set time period (example checked from 1990 onward)
  6. View values by year

Statistical analysis demonstrated: correlation

  • Use Statistical Analysis 3.0
  • Conceptually mentioned analysis types:
    • descriptive statistics
    • correlation
    • regression (not fully executed; noted as for causality later)
  • Correlation analysis steps
    • select two datasets
    • click Analyze
  • Interpretation rule used:
    • compare p-value to significance level (0.05)
    • correlation coefficient ranges in [-1, +1]
  • Example results:
    • p-value extremely low (0.0 shown)
    • correlation coefficient +0.728, interpreted as high correlation (rubric: 0.7–<0.9)

Important lesson: correlation vs causation

  • When asked whether overseas travelers increased because GNI per capita increased, the speaker concludes:
    • You cannot interpret correlation as causality.
  • Explanation:
    • correlation indicates association strength
    • causality would require regression analysis (not fully demonstrated)

G) Online Analyst (upload your own data)

When to use it

  • When you have data but don’t have statistical software.

File/data requirements (explicit instructions)

  • Prepare data in Excel format only
  • Row 1: variable names
    • example: “Gender”, “Region”, “School Type”
  • Row 2 onward: only numerical response data
  • No blank spaces in the Excel file
    • if you missed responses/left blanks: fill with a temporary placeholder like 99, then remove later
  • No formatting or formulas inside the Excel file

Upload + analysis workflow

  • Select the prepared Excel file (UI described as entering a data name)
  • Click Analyze
    • system checks upload errors
    • if valid, Statistical Analysis 3.0 loads
    • then use EST 3.0’s analysis methods (speaker states eight methods)

KSTC “Online Survey” section: how to create + run a survey

A) Purpose of Online Survey

  • Create and distribute questionnaires online
  • Collect responses from nationwide participants
  • Provides real-time statistical analysis
  • Download results afterward (frequency, raw data, analysis outputs)

Where surveys are posted

  • Surveys appear as posts
  • Boards for creating surveys:
    • Research Survey
    • Work Survey
    • Education/Test Drive Survey
  • The speaker uses Education/Test Drive Survey for practice.

B) Survey post setup: required fields & configuration

Practical note

  • The speaker warns not to type too fast while listening; focus on understanding.

Step-by-step setup

  1. Fill in:
    • Researcher name
    • Admin password (for managing the survey)
    • Email / contact info
  2. Set response period
    • choose start datetime
    • choose end datetime
  3. Enter survey name
    • practice example: “KSPCTV Usage Training”
    • set Private Survey if you don’t want the name public
  4. Enter:
    • Affiliated organization
    • Description
  5. Choose design:
    • Theme (background image) or
    • Theme Color (color tone)
    • Only one is needed.
  6. Audience & response verification
    • duplicate response verification defaults to None
    • if limiting to one response per person, choose a verification method (email, student ID, IP, etc.)
    • explanation given:
      • with email verification, respondents enter email and duplicates are blocked
  7. Access restriction and city fields are omitted in the demo
  8. Set visibility
    • Public: others can view (speaker describes view-only behavior)
    • Private: not visible to others
  9. Set response limit
    • No Limit or Limit (e.g., accept only 100 responses)
  10. Click Register
  11. A page appears with a QR code
    • completion access is via QR / link

C) Build the questionnaire: item types and creation steps

Questionnaire item types (six types)

  1. Single-choice
  2. Multi-choice
  3. Matrix
  4. Scaled (choose a position on an endpoint scale)
  5. Priority (rank options)
  6. Open-ended

Common configuration features

  • Mandatory vs Optional
  • Condition logic (show a question only if a prior answer matches an option)
  • Add content such as text/images (speaker notes these as additional components)

Demonstrated item creation

  • Single-choice
    • set Question Name
    • set mandatory status
    • set number of options (e.g., 2 for gender)
    • enter options (“Male”, “Female”)
    • save → question created
  • Multi-choice
    • example: “Foods you cannot eat”
    • list options + Other
    • optionally enable Add Free-response to allow “Other” text
  • Matrix
    • example: “Preference for each food”
    • use a table-like structure
    • multiple food rows with a shared 5-point scale (e.g., “dislike very much” to “like very much”)

Preview + ordering

  • Use Preview to check the respondent view
  • After creation, reorder using Edit Order
  • Restriction:
    • content/order cannot be modified after respondents are registered (reliability concern)
    • therefore review before distributing

D) Run practice survey + collect results

  • Responses collected for a short window (e.g., until ~2:55 PM)
  • Distribution:
    • copied URL
    • or scan QR code
  • After responses:
    • go to the survey post → QR page area (bottom right)
    • check respondent count
    • click Analyze Statistics to view:
      • option counts/percentages
      • graphs generated automatically
  • Export options:
    • save each graph using a three-line button
    • download all graphs via Download Graph
  • Open-ended responses
    • use Check Response to view free-text responses

E) Comparison: KSTCTV Online Survey vs portal form surveys

Speaker lists three main differences:

  1. Frequency tables
    • KSTCTV provides Excel frequency tables you can view/edit online
  2. Raw data
    • portal raw data often comes uncoded (text labels)
    • KSTCTV provides coded numerical raw data, easing analysis
  3. Real-time analysis
    • KSTCTV includes Statistical Analysis 3.0
    • portal tools don’t provide a similar integrated tool

ICPSR section: what it offers + how to use it

A) What ICPSR is

  • Full name: Inter-University Consortium Political and Social Research
  • Presented as:
    • the largest international quantitative data archive
    • operated by University of Michigan (USA)
    • expanded from early political science/sociology focus to nearly all subject areas
  • Speaker notes:
    • ICPSR has existed for ~60 years (anniversary referenced as “last year marked exactly its 60th anniversary”).

B) ICPSR login/account creation (via KAIST Library)

Access through KAIST subscription

  • From KAIST Library homepage:
    • Electronic Resources → Databases
    • choose letter “i”
    • select ICPSR access URL

Off campus

  • Log into KAIST Library first, then click ICPSR URL.

Personal ICPSR account

  • Create an account after entering ICPSR:
    • click Login (top right)
    • click Create Account for New Users
    • create using Creator Account
  • Account creation steps:
    • email twice + password twice
    • name in English
    • set Organization/Affiliation
    • choose department/major area (address optional)
    • set privacy = Yes
    • submit summary
  • A verification email is sent; activate via the email link.

Post-login

  • “Login” becomes My Dashboard
  • Speaker notes full functionality requires login (not a practice-only mode for ICPSR).

C) ICPSR “Find Data” experience

Scale of content mentioned

  • ~19,000 quantitative data studies
  • ~6.2 million survey variables
  • 100,000+ publications (papers/reports) with texts/links

How to search effectively

  • Use filters on the left (subject terms, region, time period, etc.)
  • Reorder/sort results (speaker mentions a “salt rock” function—likely a sort control)

Material browsing

  • Click a bold material name in results
  • “At a glance” shows summary/citation info/related subject terms
  • Downloads:
    • questionnaires/codebooks often PDF
    • raw data in formats like Stata, R, SPSS, SAS
  • Variables view:
    • “Variables” button shows survey questions (similar to KSTC “View Questionnaire”)

D) ICPSR topic/series/online analysis facilities

  • Topics: major subject areas (urban studies, conflict/war, education, policy, healthcare, etc.)
  • Series: continuous/repeated surveys
    • organized into 300 categories
    • example: ABC News Washington Post Ball series with 500+ datasets
  • Online Analysis
    • dataset subsets enable online statistical analysis on the web
    • speaker says about 1,500 data points can be analyzed online

E) Online statistical analysis in ICPSR (example cross-analysis)

Workflow demonstrated

  1. Locate a dataset (example references 2020 US election-related materials)
  2. Click Analyze Online
  3. Use Frequency and Crosstab
  4. Agree to data usage terms
  5. Run cross-tabulation using an analysis menu option (e.g., run frequency or cross tabulation)
  6. Choose variables for:
    • Rows and Columns

Conceptual interpretation (as described)

  • Cross-analysis compares responses about COVID-19 crisis handling against election choice (variable A2 vs e6).
  • Discusses grouped response categories and a very high percentage for one group (example: 97.5%).

F) Other ICPSR tools in “Find Data”: search/compare/variables

Survey variables search

  • Searches for variables/items using keywords.
  • Example keywords:
    • “Immigrant” and (mis-transcribed) “Jwabi” (speaker implies jobs)
  • Use filter by Survey

Original video