Monthly Archives: November 2020

How to use databases?

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Part of a librarian’s job is exploring databases (collections of articles or books). These are described in the Articles & Databases tab as an annotated bibliography.  To find the relevant databases across all collections use the search bar on the right, under Databases A-Z; type in a discipline or format.  Do not confuse it with the left-hand search bar reading “EBSCO Discovery” which looks at individual articles inside one collection only.  Read each description to find which database covers the years you are exploring, the countries or topics of your focus.  You may have to search several to thoroughly cover your idea.

For example, In this image, one link leads to articles between 1969 and 1990.  The other only opens articles after 1990 to present.

Now you have learned about how to use databases.  There are also some videos explaining different types of databases. Please share with a friend as you prepare for your final papers.

Why not just use Google?

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When you’ve searched Google for a book, has Google ever suggested, “Go to your local library”? No.

Imagining this is the book you are looking for. You typed the name in and the result is like this:

But none of these results will tell you that your Library already has it*! *

Part of that is on us, librarians: we haven’t opened our data and we are working on that. But it’s also because we (libraries) don’t pay Google to promote us. No one really knows Google’s algorithm, so it is hard to guess what sources it isn’t showing you  I hope you’ve heard about The Filter Bubble. If not, check out Eli Pariser’s TEDtalk (or print book). This Ted Talk introduces the problem of “filter bubbles”: as web companies strive to individualise their services according to our personal tastes, we will lose exposure to information that could challenge or broaden our worldview.♦

In this video, Eli Pariser argues that personalization will prove to be bad for us and bad for democracy.

Then, compare your screen of results with classmates’ in another city or country. There are many websites and data Google does not scrape or rank, often called the Deep or Invisible Web, not because it’s a secret or dangerous, but simply because it is not commercial or does not help Google make money.   Watch for the following post about a better tool to use for research than Google.     ♦ For more information, you can check this Wall Street Journal article by Grind, Kirsten, et al: “How Google Interferes with its Search Algorithms and Changes Your Results; the Internet Giant Uses Blacklists, Algorithm Tweaks and an Army of Contractors to Shape what You See”.

Online Workshop on Using RSQLite and Shiny App to Solve Business Problems

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On November 19, the Library will host an online workshop on creating a business intelligence dashboard with the help of R Shiny and RSQLite. Participants will make an application that resembles this dashboard. Using RSQLite and Shiny Applications to Solve Business Problems (Online Workshop) Thursday, 19 November 8:00 AM – 9:30 AM (China Standard Time) This workshop is designed to present a real-life business case where a one-stop-shop application bridges the gaps along the operations line from the back-end to the business sides. With R database management packages and Shiny app, this workshop will walk you through the steps to create such an interactive application.  This workshop will be held via ​Zoom, so you can attend from the comfort of your dorm or apartment. You must register in advance through the NYU Libcal page .  If you are not able to make it, we have created a step-by-step tutorial that shows how every piece of it works and the core concept of a one-stop shop behind it. We hope to see you there!

Workshops(11/9-11/15)

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Next week(11/9-11/15), join us for two lunchtime online workshops:

  • Introduction to QGIS (Online Workshop)

*        Tuesday, 10 November 12:00 PM – 1:30 PM (China Standard Time)* QGIS is an open source software package for geospatial analysis. This introductory workshop covers simple GIS analyses and visualizations within QGIS. ​This workshop will be held live via ​Zoom, so you can attend from the comfort of your dorm or apartment. You must register in advance through the NYU Libcal page  . 

  • Data Cleaning and Management Using Python (Online Workshop)

*         Thursday, 12 November 10 AM – 12 PM (China Standard Time)* This session is an intermediate level class that will examine ways to perform data cleaning, transformation, and management using Python. We will look at some efficient ways to load data and parse it into a container for ease of use in Python, to store it in helpful formats, and to perform some basic cleaning and transformations typical for mixed string-and-numeric formats. Finally, we’ll try putting it all together using a dataset from the NYC Open Data portal. Prerequisites:

  • Ability to set and understand the object type of a variable
  • Familiarity with foundational object types (lists, strings, numbers, dictionaries) in Python
  • Familiarity with common data storage file types such as JSON and CSV
  • Comfort with, or willingness to learn more about dataframe and array objects in Python
  • Comfort with using Jupyter Notebooks for writing code

​This workshop will be held live via ​Zoom, so you can attend from the comfort of your dorm or apartment. You must register in advance through the NYU Libcal page  .    I hope you’ll be able to join us!

Library Open Day at Go-Local Sites

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Come and check out the NYUSH-Library-hosted event. Meet friends, familiarize yourself with the Library, and HAVE A GOOD TIME!  Join us in the following activities:

  • Board Games
  • Soothing documentaries
  • Questions and prizes
  • Message board
  • Library Open Day (Go Local: Shinmay)

*        When:* Tuesday, 10 November 2 PM – 4 PM ​        Where: Lounge and conference room on the 33F floor

  • Library Open Day (Go Local: Fuhui)

*        When:* Wednesday, 11 November 12 PM – 1 PM *        Where: * Lounge and conference room on the 9th floor

Using COVID-19 data with caution

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Thinking about using COVID-19 data or statistics in your course and research projects? The library would like to recommend two resources we found useful. These resources are admittedly U.S. centric, but we think the skills and perspectives are widely applicable.  Evaluating Data Types: A Guide for Decision Makers using Data to Understand the Extent and Spread of COVID-19 – report produced by The National Academies of Sciences, Engineering, and Medicine (2020). Statistics such as confirmed cases, hospitalizations, emergency department visits, reported confirmed deaths, excess deaths, test outcomes, etc. are subject to further evaluation regarding their reliability, validity, availability and utility:

  • How each of them has been collected (representativeness, bias attached to reporting, small cases, measurement and sampling error, time of reporting and updates, geographical coverage)?
  • In what ways can they be useful (or not)?
  • What can each of them reveal to us?

Damned Lies and Coronavirus Statistics – workshop taught by Dr. Joel Best, professor of sociology and criminal justice at the University of Delaware. It was presented at the 2020 ICPSR Data Fair: Data In Real Life in September. Statistics are arguably socially constructed, and can be used by public health experts and politicians in dramatically different ways. If you need help with finding and using data sources and information on COVID-19, please reach out to us at the library (shanghai.library@nyu.edu). We are here to help.