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JSON and Structured Data

Introduction to JSON and Structured Data

Dates: November 2nd through 29th, 2020
Instructor: Robert Chavez
Credits: 1.5 CEUs or 15 PDHs
Price: $175

https://libraryjuiceacademy.com/shop/course/161-introduction-json-structured-data/

JSON is a semi-structured data format for encoding data and is a popular language for data sharing and interchange – as such it is considered a good alternative to XML. This materials in this course will cover all the core JSON syntax and data structures as well as:
– structured data as a concept
– core data structuring approaches
– the differences between XML and JSON
– when to use XML, when to use JSON

JSON itself is the language of JSON Schema and JSON-LD. We will also study core JSON Schema, a language that allows annotation and validation of JSON documents, and have an introduction to JSON-LD. JSON-LD is covered in greater depth in a follow-up course, JSON-LD Fundamentals. Both courses are follow-ups to our Certificate in XML and RDF-Based Systems.
https://libraryjuiceacademy.com/shop/course/171-json-ld-fundamentals/
https://libraryjuiceacademy.com/certificate/xml-and-rdf-based-systems/

Robert Chavez holds a PhD in Classical Studies from Indiana University. From 1994-1999 he worked in the Library Electronic Text Resource Service at Indiana University Bloomington as an electronic text specialist. From 1999-2007 Robert worked at Tufts University at the Perseus Project and the Digital Collections and Archives as a programmer, digital humanist, and institutional repository program manager. He currently works for the New England Journal of Medicine as Content Applications Architect.

Course Structure
This is an online class that is taught asynchronously, meaning that participants do the work on their own time as their schedules allow. The class does not meet together at any particular times, although the instructor may set up optional synchronous chat sessions. Instruction includes readings and assignments in one-week segments. Class participation is in an online forum environment.

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more on JSON in this IMS blog
https://blog.stcloudstate.edu/ims?s=json

Assessment tools

Assessment is STEM courses (and how they integrated in LMS:

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More on assessment in this IMS blog
https://blog.stcloudstate.edu/ims?s=assessment

bibliographical data analysis nVivo

Bibliographical data analysis with Zotero and nVivo

Bibliographic Analysis for Graduate Students, EDAD 518, Fri/Sat, May 15/16, 2020

This session will not be about qualitative research (QR) only, but rather about a modern 21st century approach toward the analysis of your literature review in Chapter 2.

However, the computational approach toward qualitative research is not much different than computational approach for your quantitative research; you need to be versed in each of them, thus familiarity with nVivo for qualitative research and with SPSS for quantitative research should be pursued by any doctoral student.

Qualitative Research

Here a short presentation on the basics:

https://blog.stcloudstate.edu/ims/2019/03/25/qualitative-analysis-basics/

Further, if you wish to expand your knowledge, on qualitative research (QR) in this IMS blog:

https://blog.stcloudstate.edu/ims?s=qualitative+research

Workshop on computational practices for QR:

https://blog.stcloudstate.edu/ims/2017/04/01/qualitative-method-research/

Here is a library instruction session for your course
https://blog.stcloudstate.edu/ims/2020/01/24/digital-literacy-edad-828/

Once you complete the overview of the resources above, please make sure you have Zotero working on your computer; we will be reviewing the Zotero features before we move to nVivo.

Here materials on Zotero collected in the IMS blog:
https://blog.stcloudstate.edu/ims?s=zotero

Of those materials, you might want to cover at least:

https://youtu.be/ktLPpGeP9ic

Familiarity with Zotero is a prerequisite for successful work with nVivo, so please if you are already working with Zotero, try to expand your knowledge using the materials above.

nVivo

https://blog.stcloudstate.edu/ims/2017/01/11/nvivo-shareware/

Please use this link to install nVivo on your computer. Even if we were not in a quarantine and you would have been able to use the licensed nVivo software on campus, for convenience (working on your dissertation from home), most probably, you would have used the shareware. Shareware is fully functional on your computer for 14 days, so calculate the time you will be using it and mind the date of installation and your consequent work.

For the purpose of this workshop, please install nVivo on your computer early morning on Saturday, May 16, so we can work together on nVivo during the day and you can continue using the software for the next two weeks.

Please familiarize yourself with the two articles assigned in the EDAD 815 D2L course content “Practice Research Articles“ :

Brosky, D. (2011). Micropolitics in the School: Teacher Leaders’ Use of Political Skill and Influence Tactics. International Journal of Educational Leadership Preparation, 6(1). https://eric.ed.gov/?id=EJ972880

Tooms, A. K., Kretovics, M. A., & Smialek, C. A. (2007). Principals’ perceptions of politics. International Journal of Leadership in Education, 10(1), 89–100. https://doi.org/10.1080/13603120600950901

It is very important to be familiar with the articles when we start working with nVivo.

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How to use Zotero

https://blog.stcloudstate.edu/ims/2020/01/27/zotero-workshop/

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How to use nVivo for bibliographic analysis

The following guideline is based on this document:

https://www.projectguru.in/bibliographical-data-nvivo/

whereas the snapshots are replaced with snapshots from nVivol, version 12, which we will be using in our course and for our dissertations.

Concept of bibliographic data

Bibliographic Data is an organized collection of references to publish in literature that includes journals, magazine articles, newspaper articles, conference proceedings, reports, government and legal publications. The bibliographical data is important for writing the literature review of a research. This data is usually saved and organized in databases like Mendeley or Endnote. Nvivo provides the option to import bibliographical data from these databases directly. One can import End Note library or Mendeley library into Nvivo. Similar to interview transcripts, one can represent and analyze bibliographical data using Nvivo. To start with bibliographical data representation, this article previews the processing of literature review in Nvivo.

Importing bibliographical data

Bibliographic Data is imported using Mendeley, Endnote and other such databases or applications that are supported with Nvivo.  Bibliographical data here refers to material in the form of articles, journals or conference proceedings. Common factors among all of these data are the author’s name and year of publication. Therefore, Nvivo helps  to import and arrange these data with their titles as author’s name and year of publication. The process of importing bibliographical data is presented in the figures below.

import Zotero data in nVivo

 

 

 

 

select the appropriate data from external folder

select the appropriate data from external folder

step 1 create record in nVIvo

 

step 2 create record in nVIvo

step 3 create record in nVIvo

 

Coding strategies for literature review

Coding is a process of identifying important parts or patterns in the sources and organizing them in theme node. Sources in case of literature review include material in the form of PDF. That means literature review in Nvivo requires grouping of information from PDF files in the forms of theme nodes. Nodes directly do not create content for literature review, they present ideas simply to help in framing a literature review. Nodes can be created on the basis of theme of the study, results of the study, major findings of the study or any other important information of the study. After creating nodes, code the information of each of the articles into its respective codes.

Nvivo allows coding the articles for preparing a literature review. Articles have tremendous amount of text and information in the forms of graphs, more importantly, articles are in the format of PDF. Since Nvivo does not allow editing PDF files, apply manual coding in case of literature review.  There are two strategies of coding articles in Nvivo.

  1. Code the text of PDF files into a new Node.
  2. Code the text of PDF file into an existing Node. The procedure of manual coding in literature review is similar to interview transcripts.

Add Node to Cases

 

 

 

 

 

The Case Nodes of articles are created as per the author name or year of the publication.

For example: Create a case node with the name of that author and attach all articles in case of multiple articles of same Author in a row with different information. For instance in figure below, five articles of same author’s name, i.e., Mr. Toppings have been selected together to group in a case Node. Prepare case nodes like this then effortlessly search information based on different author’s opinion for writing empirical review in the literature.

Nvivo questions for literature review

Apart from the coding on themes, evidences, authors or opinions in different articles, run different queries based on the aim of the study. Nvivo contains different types of search tools that helps to find information in and across different articles. With the purpose of literature review, this article presents a brief overview of word frequency search, text search, and coding query in Nvivo.

Word frequency

Word frequency in Nvivo allows searching for different words in the articles. In case of literature review, use word frequency to search for a word. This will help to find what different author has stated about the word in the article. Run word frequency  on all types of sources and limit the number of words which are not useful to write the literature.

For example, run the command of word frequency with the limit of 100 most frequent words . This will help in assessing if any of these words remotely provide any new information for the literature (figure below).

Query Text Frequency

andword frequency search

and

word frequency query saved

Text search

Text search is more elaborative tool then word frequency search in Nvivo. It allows Nvivo to search for a particular phrase or expression in the articles. Also, Nvivo gives the opportunity to make a node out of text search if a particular word, phrase or expression is found useful for literature.

For example: conduct a text search query to find a word “Scaffolding” in the articles. In this case Nvivo will provide all the words, phrases and expression slightly related to this word across all the articles (Figure 8 & 9). The difference between test search and word frequency lies in generating texts, sentences and phrases in the latter related to the queried word.

Query Text Search

Coding query

Apart from text search and word frequency search Nvivo also provides the option of coding query. Coding query helps in  literature review to know the intersection between two Nodes. As mentioned previously, nodes contains the information from the articles.  Furthermore it is also possible that two nodes contain similar set of information. Therefore, coding query helps to condense this information in the form of two way table which represents the intersection between selected nodes.

For example, in below figure, researcher have search the intersection between three nodes namely, academics, psychological and social on the basis of three attributes namely qantitative, qualitative and mixed research. This coding theory is performed to know which of the selected themes nodes have all types of attributes. Like, Coding Matrix in figure below shows that academic have all three types of attributes that is research (quantitative, qualitative and mixed). Where psychological has only two types of attributes research (quantitative and mixed).

In this way, Coding query helps researchers to generate intersection between two or more theme nodes. This also simplifies the pattern of qualitative data to write literature.

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Please do not hesitate to contact me with questions, suggestions before, during or after our workshop and about ANY questions and suggestions you may have about your Chapter 2 and, particularly about your literature review:

Plamen Miltenoff, Ph.D., MLIS

Professor | 320-308-3072 | pmiltenoff@stcloudstate.edu | http://web.stcloudstate.edu/pmiltenoff/faculty/ | schedule a meeting: https://doodle.com/digitalliteracy | Zoom, Google Hangouts, Skype, FaceTalk, Whatsapp, WeChat, Facebook Messenger are only some of the platforms I can desktopshare with you; if you have your preferable platform, I can meet you also at your preference.

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more on nVIvo in this IMS blog
https://blog.stcloudstate.edu/ims?s=nvivo

more on Zotero in this IMS blog
https://blog.stcloudstate.edu/ims?s=zotero

NVivo workshop

Intro to NVivo – January 31
10:00 a.m. – 12:30 p.m.
440 Blegen Hall

NVivo is a qualitative data management, coding and markup tool, that facilitates powerful querying and exploration of source materials for both mixed methods and qualitative analysis. It integrates well with tools that assist in data collection and can handle a wide variety of source materials. This workshop introduces the basic functions of NVivo, with no prior experience necessary. The session is held in a computer lab with the software already installed. Register.

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more on qualitative research in this IMS blog
https://blog.stcloudstate.edu/ims?s=qualitative

Idolization of Technology

Narcissism and the Idolization of Technology

Marshall McLuhan , Understanding Media,

Brave New World, Aldous Huxley
one of the greatest future threats to liberal democracy was society being caught unprepared by an advancing technology that changes social conditions, so that people find themselves “in a situation which they didn’t foresee and doing all sorts of things they didn’t want to do.”

while the user of media is distracted by its content, he is more susceptible to the actual agent of its influence— the medium itself. Hence, McLuhan’s most famous aphorism, “The medium is the message.”

Viewing social media through this lens, it seems obvious that it is not the content, or what is said on these very popular platforms where the true power to influence lies, rather it is in the medium itself.

corporate surveillance

Behind the One-Way Mirror: A Deep Dive Into the Technology of Corporate Surveillance
BY BENNETT CYPHERS DECEMBER 2, 2019

https://www.eff.org/wp/behind-the-one-way-mirror

Corporations have built a hall of one-way mirrors: from the inside, you can see only apps, web pages, ads, and yourself reflected by social media. But in the shadows behind the glass, trackers quietly take notes on nearly everything you do. These trackers are not omniscient, but they are widespread and indiscriminate. The data they collect and derive is not perfect, but it is nevertheless extremely sensitive.

A data-snorting company can just make low bids to ensure it never wins while pocketing your data for nothing. This is a flaw in the implied deal where you trade data for benefits.

You can limit what you give away by blocking tracking cookies. Unfortunately, you can still be tracked by other techniques. These include web beaconsbrowser fingerprinting and behavioural data such as mouse movements, pauses and clicks, or sweeps and taps.

The EU’s GDPR (General Data Protection Regulation) was a baby step in the right direction. BOWM also mentions Vermont’s data privacy law, the Illinois Biometric Information Protection Act (BIPA) and next year’s California Consumer Privacy Act (CCPA).

Tor, the original anti-surveillance browser, is based on an old, heavily modified version of Firefox.

Most other browsers are now, like Chrome, based on Google’s open source Chromium. Once enough web developers started coding for Chrome instead of for open standards, it became arduous and expensive to sustain alternative browser engines. Chromium-based browsers now include Opera, Vivaldi, Brave, the Epic Privacy Browser and next year’s new Microsoft Edge.

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more on surveillance in this IMS blog
https://blog.stcloudstate.edu/ims?s=surveillance

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