Searching for "data"

school privacy data

http://blogs.edweek.org/edweek/DigitalEducation/2020/11/student_data_future_criminals_pasco_privacy.html

Using Student Data to Identify Future Criminals: A Privacy Debacle

Under the federal Family Educational Rights and Privacy Act (FERPA), schools can share student records with a contractor or outside party to whom the school has outsourced certain functions, if that outside party (like a designated school resource officer) meets all three of these conditions:

  1. The outside party is performing a service that would otherwise be performed by school employees.
  2. The outside party’s use of education records is under the direct control of the school.
  3. The outside party does not use the education records for anything other than the reason they were originally shared, and does not share the education record with anyone else unless it secures written consent from the parent of the student.

Privacy data ignored by Android iPhone

 

+++++Under EU law, citizen can demand a copy of all personal data that companies hold about them. However, more than one year after implementation of the new law, most Android and iPhone apps still completely ignore this right, a new study has found. from r/iphone

https://dl.acm.org/doi/epdf/10.1145/3407023.3407057

How do App Vendors Respond to Subject Access Requests? A Longitudinal Privacy Study on iOS and Android Apps
the results of a four-year undercover field study.

Besides a general lack of responsiveness, the observed problems range from malfunctioning download links and authentication mechanisms over confusing data labels and le structures to impoliteness, incomprehensible language, and even serious cases of carelessness and data leakage. It is evident from our results that there are no well-established and standardized processes for subject access requests in the mobile app industry. Moreover, we found that many vendors lack the motivation to respond adequately. Many of the responses we received were not only completely insucient, but also deceptive or misleading. Equally worrisome are cases of unsolicited dissolution of personal data, for instance, due to the

apparently widespread practice of deleting stale accounts without prior notice

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New lawsuit: Why do Android phones mysteriously exchange 260MB a month with Google via cellular data when they’re not even in use? from r/technology

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

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

students data privacy

https://www.edsurge.com/news/2020-06-26-researchers-raise-concerns-about-algorithmic-bias-in-online-course-tools

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Students fear for their data privacy after University of California invests in private equity firm

A financial link between a virtual classroom platform and the University of California system is raising eyebrows

https://www.salon.com/2020/07/28/students-fear-for-their-data-privacy-after-university-of-california-invests-in-private-equity-firm/

Instructure has made it clear through their own language that they view the student data they aggregated as one of their chief assets, although they have also insisted that they do not use that data improperly. My note: “improperly” is relative and requires defining.

Yet an article published in the Virginia Journal of Law and Technology, titled “Transparency and the Marketplace for Student Data,” pointed out that there is “an overall lack of transparency in the student information commercial marketplace and an absence of law to protect student information.” As such, some students at the University of California are concerned that — despite reassurances to the contrary — their institution’s new financial relationship with Thoma Bravo will mean their personal data can be sold or otherwise misused.

The students’ concerns over surveillance and privacy are not unwarranted. Previously, the University of California used military surveillance technology to help quell the grad student strikes at UC Santa Cruz and other campuses

Encrypted Data Act

New anti-encryption bill worse than EARN IT. Act now to stop both. from r/technology

https://tutanota.com/blog/posts/lawful-access-encrypted-data-act-backdoor/

Once surveillance laws such as an encryption backdoor for the “good guys” is available, it’s just a matter of time until the “good guys” turn bad or abuse their power.

By stressing the fact that tech companies must decrypt sensitive information only after a court issues a warrant, the three Senators believe they can swing the public opinion in favor of this encryption backdoor law.

beginners learn Python for Data Science

My company released a course for helping beginners learn Python for Data Science. This is an initial draft and we do not plan to monetize it any way. Please feel free to help us make it better with your suggestions. from r/programming

Learn Python for Data Science – Full Course

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more on Python on this IMS blog
https://blog.stcloudstate.edu/ims?s=python

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:

Bibliographical data analysis using 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

python to clean data

7 Simple Python Functions to Clean Your Data

Fábio Neves  Jan 9

python

  • Merging all files from a specific folder
  • Edit every file in the same folder and re-save them again
  • Cleaning the header of your datasets
  • Split dataframe columns into two or more columns
  • Filter specific dataframe columns based on their column names
  • Calculate the number of days between two dates
  • Calculate number of weeks/months/years between two dates

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

Big Data AI coronavirus

South Korea winning the fight against coronavirus using big-data and AI

https://www.thedailystar.net/online/news/south-korea-winning-the-fight-against-coronavirus-using-big-data-and-ai-1880737

South Korea is using the analysis, information and references provided by this integrated data — all different real-time responses and information produced by the platform are promptly conveyed to people with different AI-based applications.

Whenever someone is tested positive for COVID-19, all the people in the vicinity are provided with the infected person’s travel details, activities, and commute maps for the previous two weeks through mobile notifications sent as a push system.

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