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• 1 media/owl-1014942_1920.jpg 2020-09-12T22:00:29+00:00 Section 3 : Tools for Analysis - Voyant 24 image_header 2021-02-23T22:54:05+00:00

  Section 3: Tools for Analysis - Voyant

  In this section, we're going to take a look at a very popular, free, web-based text analysis tool called Voyant.
  
  Voyant is a web-based program where users input a downloaded corpus to return a word frequency cloud, word use over time graphs, word and phrase correlations, and topic models.
  
  It is capable of visualizing similarities between documents in a corpus in multiple ways.  No programming knowledge is needed which makes Voyant such a accessible tool to learn the basics of text analysis.
  
  Let's take a closer look!
  
  First, go to the Voyant website <https://voyant-tools.org/>.
  Second, watch the following brief video to learn how to access more information on all the analysis tools available through Voyant.
  
  Or
  • Click on the hyperlinked text just below the open box.
  • Then, click on tab in the top navigation bar called, "List of Tools."
  
  
  Now, that you are a little more familiar with the variety of analytic tools, let's practice.
  
  Activity - Adding Text via Link:
  1. Go to any news website of your choice (e.g., CNN, New York Times, Wall Street Journal).
  2. Click on any article of your choice.
  3. Copy the link (URL) to that article and paste it in the open box on the Voyant landing page.
  4. Then, click on the "Reveal" button.
  5. Explore and investigate your results.
  
  
  Instead of linking to an article online, let's practice with Voyant's "Open Corpus."
  
  Activity - Open Corpus:
  1. Go to the Voyant landing page.
  2. Click on the “Open” button located underneath the open box on the landing page.
  3. From the “Choose a corpus” drown-down menu, select either Shakespeare’s Plays or Austen’s Novels.
  4. Then, click the “Open” button.
  5. Explore and investigate your results.
  
  Now that you've had a little practice with analyzing a corpus, let's try uploading a corpus to Voyant.  We'll use the Folger Shakespeare Library for this activity.  The library provides downloadable text files for research purposes.
  
  Activity - Upload Corpus:
  1. Go to the Folger Shakespeare Library's download page.
  2. Click on the play that interests you the most.
  3. For example, if you selected Hamlet, then on the subsequent page, select the the play's TXT file by clicking on the corresponding "Download" button.
  4. Once you select "Download," save the file to your computer.
  5. Go back to the Voyant landing page.
  6. Click the "Upload" button.
  7. Select the TXT file that you saved to your desktop.
  8. Explore and investigate your results.
  Watch the following video which illustrates the directions above.
  
  
  
  You now have learned how to use a free, web-based text analyzing tool!
• 1 media/padlock.png 2020-11-05T20:04:50+00:00 Section 1: Assessing Your Security & Privacy Needs 21 image_header 2020-11-05T22:45:24+00:00

  Let's Begin

  In this tutorial, you'll:
  • learn the meaning of data, data privacy, and data security;
  • gain an understanding of criteria for selecting trustworthy, reliable vendors for data storage;
  • learn how to locate vendor support documentation and their privacy and security measures;
  • learn about independent security experts;
  • learn the purpose of cloud synchronization, cloud backup, and an external hard drive;
  • gain an awareness of a variety of password managers and how to assess them;
  • gain an understanding of internet browsing and searching best practices.

  Section 1: Assessing Your Security & Privacy Needs

  Before we begin to assess your data security and privacy needs, let's consider some definitions.
  
  Data are formatted pieces of information.  Data can be numbers, text, or bits & bytes.  Software is comprised of data and programs.  Programs are the instructions for manipulated the data.
  
  Data privacy refers to the authorized access of your personal data (i.e., who has access and what do they have access to). 
  
  Data security encompasses the protective measure(s) that ensure the security of your personal data against unauthorized access.

  ---

  As you begin to assess your data needs and the best place to store and save your data, you may ask yourself, "How do I know who or what to trust with my data?"
  
  First, consider taking the following steps:
  
  Step 1: Locate and read the vendor's support documentation.  A vendor should provide detailed support documentation about its own security practices.
  
  Here are some questions to think about when reviewing support documentation:
  • Does it offer easy data exports?
  • Does it encrypt data on your computers and mobile devices and also while data is in transit over the internet?
  • Does it keep sensitive data in a secure place on your own device rather than transmit it over the internet?
  • Are you the customer or are you the data?
  • Does it use standards that can be verified by independent security experts?
  • Does it regularly audit its own systems for vulnerabilities?
  
  Activity: Let's practice reviewing and assessing vendor support documentation!  First, select a vendor or use a vendor you have used to save and store data.  If you're having trouble selecting a vendor, try one of these more popular ones:
  • Google Drive
  • Dropbox 
  • Box 
  • Amazon Drive 
  • iCloud Drive
  • OneDrive 
  • Open Science Framework
  • Humanities Commons
  Then, locate their support documentation.  Once you do, can you find information about their privacy and security measures?  More specifically, try to apply the questions above.
  
  Other considerations should include:
  • How much does it cost?
  • Is there a free version?
  • What are the storage limits?
  • Are there any file size upload limits?
  • Does it enable collaboration and data sharing?
  Here's an example of where you can find privacy policy and terms for Dropbox.  Fortunately, they've included lots of helpful information on the homepage itself.  But if you scroll down to the footer, you'll see a link for more information on their "privacy & terms" under Support.
  

  ---

  
  Step 2: Consult product reviews from independent security experts.
  
  There are some well-known, trusted, and experienced security experts that you may wish to consult.  There are also non-profit organizations whose purpose is providing trustworthy information about digital privacy issues.
  
  Consider the following resources:
  • Bruce Schneier – Schneier on Security
    A public-interest technologist, working at the intersection of security, technology, and people.
  • Brian Krebs – Krebs on Security 
    A journalist and investigative reporter; author of a daily blog on computer security and cybercrime.
  • Electronic Frontier Foundation (EFF)
    A nonprofit that defends digital privacy, free speech, and innovation.
  • Electronic Privacy Information Center (EPIC)
    A public interest research center in Washington, D.C. that works to bring public attention to privacy and civil liberty issues.

  ---

  
  Step 3. Inventory your data.
  
  The last step that we'll take a look at in this section, Assessing Your Security & Privacy Needs, is how to inventory your data.
  
  Before you make decisions on the best place(s) to store and save your data, it's important to take inventory of all the data that you have.  When doing so, you should take note of the following:
  • Where you currently store your data;
  • Who has access to it;
  • What the current security measures are;
  • What might happen to your data, if security is compromised; and
  • What data is a priority
  Activity: Try to inventory your data!  You can use any kind of documentation that works best for you.  Or feel free to use this template to download and save to your computer or save to your google drive.  
   
• 1 media/Squares.png 2022-01-09T02:45:17+00:00 Section 2: Data Management Components 21 image_header 2022-01-10T20:09:32+00:00 Now that we've considered what constitutes humanities data, we'll turn our attention to effectively managing your research data.
  
  Let's breakdown data management into its basic components.

  Section 2: Data Management Components

  In the context of research and scholarship, data management refers to the storage, access, and preservation of data produced from a given investigation.​

  Data management practices cover the entire lifespan of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long term preservation of data deliverables after the research investigation has concluded.​

  *Data management plans (DMPs) describe the data management activities for a research group, researcher, or research project. They are structured documents created in advance of collecting data, and describe practices that will be followed over the course of the data lifecycle.​

  (Resource: Texas A&M University Libraries, Research Data Management)
  
  Sometimes it's helpful to think of data management components or practices as an integral part of the research lifecycle.  The graphic below illustrates the several data practices that occur through your research process.
  
  
  In this tutorial, we'll focus on metadata, file naming and organizing, storage, and sharing in the following sections.
  
  First, let's watch the video below, which is a thoughtful, funny animated attempt at explaining the importance of practicing good data management.
   
  (NYU Health Sciences Library, 2012, Data Sharing and Management Snafu in 3 Short Acts)

  Funding agency requirements for data management such as the NEH can be helpful when considering the general components of a plan whether you’re seeking funding or not.​  Below are the basic components and questions that should be considered when developing your plan.

  Data description​

  • Who will be responsible for the data and their management?​
  • What types of data will be collected or created?​
  • How will data be collected or created, and processed?​

  Standards​

  • Which file formats will be used for working data?​
  • What additional information is needed to make data meaningful, how will this be captured?​
  • What forms will additional descriptive material take?​
  • Which metadata standards will be followed?​

  Policies for access, sharing and re-use​

  • How will data be stored, backed up, and maintained during the project?​
  • How will you manage access and security?​
  • Are there any ethical, privacy, or legal issues?​
  • How will the data be shared or made available? Are there any restrictions?​
  • What are intended or anticipated future uses?​

  Long-term storage and management

  • Which data will be preserved for the long-term?​
  • Which file formats will be used for long-term accessibility?​
  • Where will data be archived and how will they be maintained to ensure preservation?​
  
  Activity: Review this data management plan template and try filling it out for your project.  You may download and save your own copy.
  
  
  Let's move on to learn about file naming best practices!
• 1 media/elephant-4367079_1280.png 2020-09-12T22:20:26+00:00 Section 4 : Tools for Analysis - HathiTrust Research Center Analytics 20 image_header 2021-02-23T22:54:56+00:00

  Section 4 : Tools for Analysis - HathiTrust Research Center Analytics

  In addition to Voyant, there are many freely-accessible text analysis tools available for researchers which accommodate a range of use from novice to expert.  One such text analysis tool that we'll take a closer look at is HathiTrust Research Center Analytics.
  
  First, let's consider the HathiTrust Digital Library (HTDL) which provides the data for the HTRC Analytics site.  The HTDL is a partnership of more than 150 member institutions.  The University of Kentucky Libraries is one of those members.  Founded in 2008, HTDL grew out of large-scale digitization initiatives at research libraries.  It's an off-shoot of the Google Books project.  Thus, most of what comprises HTDL holdings are from academic research libraries.  The content includes more than 17 million volumes (~62% in copyright or undetermined status). Volumes in the public domain can be searched and read.
  
  Now, let's consider the HathiTrust Research Center (HTRC). It is located both at Indiana University and the University of Illinois.  It facilitates large-scale computational research (text analysis) of content from the HathiTrust Digital Library (HTDL) with tools, datasets, and virtual programming environments.
  
  HathiTrust data is in the form of (primarily bibliographic) metadata and full text data.  The full text data is OCR text generated automatically during the digitization process.  And because it is OCR text, it's considered "dirty" or uncorrected (for more information on "dirty" text data see Section 2).  The bibliographic data is augmented but not corrected.
  
  Let's explore further.  There are three featured services within HTRC Analytics: Extracted Features, Text Analysis Algorithms, and Data Capsules.

  Extracted Features

  From HTRC Analytics:
  This is an unrestricted dataset of metadata and word counts for each page in the HathiTrust Digital Library. Download and explore on your own machine.  HTRC releases research datasets to facilitate text analysis using the HathiTrust Digital Library.
  
  While copyright-protected texts are not available for download from HathiTrust, fruitful research can still be performed on the basis of non-consumptive analysis of features extracted from full text. These features include volume-level metadata, page-level metadata, part-of-speech-tagged tokens, and token counts. Additionally, HTRC has partnered with advanced researchers to release a derived dataset, Word Frequencies in English-Language Literature, 1700-1922 and Geographic Locations in English-Language Literature, 1701-2011.

  Text Analysis Algorithms

  From HTRC Analytics:
  HTRC Algorithms are web-based, click-and-run tools to perform computational text analysis on volumes in the HathiTrust Digital Library. The algorithms can help you explore, analyze, and visualize public worksets or those you have created.

  Data Capsules

  From HTRC Analytics:
  These are a system of a secure computing environments for performing researcher-driven text analysis on the HathiTrust corpus. All users may access public domain items.  However, computational access to items in copyright is available only to member-affiliated researchers.
  
  This graphic further illustrates the relationship between the HathiTrust Digital Library and the HathiTrust Research Center Analytics.
  
  Synched on a nightly basis, the digitized content of the HathiTrust Digital Library is transformed into metadata and data that creates the derived datasets used in the Extracted Features service.  Additionally, that derived data feeds text analysis tools such as HathiTrust+Bookworm and other tools available in the Text Analysis Algorithms service.  And lastly, the data from the HathiTrust corpus feeds directly into the Data Capsule service for researchers to analyze and export the derived results.
  
  Now, let's explore one of the HTRC in-development, text analysis tools, HathiTrust+Bookworm.  You can find these experimental tools under "Explore" in the top navigation bar of the HTRC Analytics site.
  
  Activity:
  Learn more about this tool by first watching this short video (3:44).  A step-by-step tutorial can also be found on the HTRC wiki.
  
  Then, navigate to HathiTrust+Bookworm and explore its functionality using your own chosen terms.  What trends do you notice?
  
  You have now learned about another freely-available, web-based tool for text analysis.  If you'd like to explore additional text mining tools, check out the tools suggested under "Text Mining" on the Resources & Support for Digital Humanities research guide.
  
  References:
  • “Text Mining with HathiTrust: An Introduction for Librarians” Fall 2019 Workshop, West Virginia University, 11/4/19 by Eleanor Koehl, Associate Director for Outreach & Education, HTRC and Ryan Dubnicek, Digital Humanities Specialist, HTRC
• 1 media/Green Squares.png 2022-01-09T02:43:13+00:00 Section 1: What is Humanities Data? 10 image_header 2022-01-10T20:16:32+00:00

  Let's Begin

  In this tutorial, you'll:
  • learn what is considered data in humanities research;
  • learn about the "data journey" within in the research lifecycle;
  • define data management and discover it's many components;
  • learn how to apply file naming best practices;
  • gain an understanding of data documentation and metadata best practices; and
  • discover data storage, backup, and sharing options.

  Section 1: What is Humanities Data?

  Let's first consider how humanities data has been defined and explained by information professionals and experts in the field of digital humanities.
  
  Dr. Trevor Owens, Head of Digital Content Management, Library of Congress​ explains:

  We can choose to treat data as different kinds of things. First, as constructed things, data are a species of artifact. Second, as authored objects created for particular audiences, data can be interpreted as texts. Third, as computer-processable information, data can be computed in a whole host of ways to generate novel artifacts and texts which are then open to subsequent interpretation and analysis. Which brings us to evidence.  Each of these approaches—data as text, artifact, and processable information—allow one to produce or uncover evidence that can support particular claims and arguments. Data is not in and of itself a kind of evidence but a multifaceted object which can be mobilized as evidence in support of an argument.

  Owens, Trevor. “Defining Data for Humanists: Text, Artifact, Information or Evidence?” Journal of Digital Humanities 1, no. 1 (Winter 2011).
  
  ​Dr. Johanna Drucker, Department of Information Studies, UCLA​ considers:

  To overturn the assumptions that structure conventions acquired from other domains requires that we re-examine the intellectual foundations of digital humanities, putting techniques of graphical display on a foundation that is humanistic at its base. This requires first and foremost that we reconceive all data as capta. Differences in the etymological roots of the terms data and capta make the distinction between constructivist and realist approaches clear. Capta is “taken” actively while data is assumed to be a “given” able to be recorded and observed. From this distinction, a world of differences arises. Humanistic inquiry acknowledges the situated, partial, and constitutive character of knowledge production, the recognition that knowledge is constructed, taken, not simply given as a natural representation of pre-existing fact.

  Drucker, Johanna. “Humanities Approaches to Graphical Display.” Digital Humanities Quarterly 5, no. 1 (2011).
  
  And finally, The National Endowment for the Humanities (NEH) Office of Digital Humanities states:

  “Data” is defined as materials generated or collected during the course of conducting research.​

  Examples of humanities data could include citations, software code, algorithms, digital tools, documentation, databases, geospatial coordinates (for example, from archaeological digs), reports, and articles.

  Data Management Plans for NEH Office of Digital Humanities Proposals and Awards
  
  
  Activity: Given these definitions and examples of data, what do you think it means to manage data in the humanities?  What activities do you think would be included in managing your data?
• 1 media/Squares.png 2022-01-09T02:45:44+00:00 Section 3: File Naming Best Practices 9 image_header 2022-01-10T23:55:34+00:00

  Section 3: File Naming Best Practices

  For this section, we're going to dive into one of the data management components, Standards.
  
  When organizing your data, it's essential to name your files in a consistent and descriptive manner.

  Consider including some of the following information in your file naming format:​

  • Project name or acronym​
  • Location​
  • Initials or Name​
  • Date (e.g.,  YYYYMMDD or YYMMDD)​
  • Version number​
  Whatever you decide to include in how you name your files, two of the most important things to remember is to be consistent and descriptive.​
  
  Additional best practices include:
  • Avoid using special characters (e.g., ! # & $ %).​
  • Try not to make the name too long.​
  • Do not use spaces between words in your file name.  Instead, use underscores (e.g, file_name), dashes (e.g, file-name), no separation (e.g, filename), or camel case (e.g, FileName).​
  • Save your data files in a non-proprietary (open) format.  This will ensure long-term access and sustainability of your data.​
    • For instance, instead of saving your data in a Microsoft Word Document save it as a PDF (Portable Document Format) or RTF (Rich Text Format).​
  Here is a list of some preferred non-proprietary (open) formats:​
  • Containers: TAR, GZIP, ZIP​
  • Databases: XML, CSV​
  • Moving images: MOV, MPEG, AVI, MXF​
  • Sounds: WAVE, AIFF, MP3, MXF​
  • Still images: TIFF, JPEG 2000, PDF, PNG, GIF, BMP​
  • Text: XML, PDF, HTML, TXT​
  Save copies of each of your file versions and designating them as such (e.g., “v1,” “v2”)​

  When you make changes to a file and create a new version consider including a version number in your naming convention.  Again consistency is key.

  Consider the following questions:
  • What sort of naming & organizing structures do you currently use?​
  • What’s working in this system?​
  • What’s not working?
  (Resource: Data Best Practices and Case Studies, Naming Files – Stanford Libraries)
  
  
  Activity: Let's practice! Try this file naming and organizing activity. It will help reinforce what you've learned. You may download and save your own copy.
  
  Let's go to the next section to learn about metadata, documentation, storage, & sharing.
• 1 media/circuit board abstract.jpg 2020-11-05T20:05:22+00:00 Section 2: Security and Privacy Issues 8 image_header 2020-11-06T00:30:49+00:00

  Section 2: Security and Privacy Issues

  In this section, we'll take a look at the importance of: 
  • backing up your data;
  • safely securing and storing your passwords; and
  • browsing and searching best practices.

  Security - Backup

  Backing up your data is an important consideration and best practice.  There are a number of ways to create an effective backup system.
  
  1. Cloud Synchronization
  
  Cloud synch can be considered a backup practice in the sense that your data is saved on more than one device.  It keeps folders and documents in sync across multiple devices.  Some examples of cloud synch services include Google Drive, Dropbox, Microsoft's OneDrive, and Box. 
  
  If you choose to utilize cloud synchronization, be sure to investigate the vendors that supply these services in the same way you might investigate them for data storage as explained in Section 1: Assessing Your Security & Privacy Needs.
  
  2. Cloud Backup
  
  Cloud Backup is cloud-based software designed to auto backup all files on your computer on a regular basis to an encrypted remote location.
  Some examples of cloud backup services include Backblaze, iDrive, Carbonite, and SpiderOak One Backup.
  
  Again, if you choose to implement a cloud backup service be to sure to investigate the support documentation and consult experts before selecting a product.
  
  3. External Hard Drive
  
  Lastly, consider keeping an external hard drive.  It's a best practice to backup your data to a local hard drive(s) in addition to cloud backup services.

  Security - Passwords and Password Managers

  Password security is a serious issue.  Today, most of us have countless passwords to manage used for a variety of online accounts and services.  But all too often we don't keep those passwords safe, we repeat them, and create weak ones.
  
  Your password is only as secure as the least secure site where you use it.
  
  To safely and securely manage our passwords, security experts recommend using a password manager.  
  A password manager securely stores all your passwords in an encrypted database and you need to remember only one password.
  
  There are dozens of password managers available such as LastPass, 1Password, Dashlane, and Keeper. To find the best one to fit your needs, here are some criteria to consider before you make your selection.
  • Cost
  • Web & Mobile Compatibility
  • Platform Compatibility
  • Auto-Fill Capabilities
  • Password Suggestions & Password Strength Estimation
  • Support for Different Types of Data
  Also, consulting security experts as explained in Section 1: Assessing Your Security & Privacy Needs is another important step to take.  They will often provide in-depth product reviews.
  
  Finally, it can be helpful to consult product reviews and recommendations from well-know technology-based sources such as CNET, PCMag, PCWorld, and Wirecutter, to name a few.  These sources will often discuss product specifications and features as well as provide comparisons between the products.  Several of them also create handy comparison charts.  It's particularly useful to compare reviews and recommendations between the sources as well.
  
  Activity: Let's investigate some password managers! Use all the tools that you've learned about: review product support documentation, locate reviews from independent security experts and organizations, and consult product reviews and recommendations from well-know technology-based sources.  You can use any kind of documentation that works best for you.  Or feel free to use this template to download and save to your computer or save to your google drive. 

  Privacy - Browsing and Searching Best Practices

  In this final part of Section 2: Security and Privacy Issues, let's consider some internet browsing and searching best practices.  These are meant to better protect yourself from viruses, scams, and unwanted targeted ads.
  • Regularly update your web browser.
  • Regularly clear your browser history (toss the cookies).
  • Read the Privacy Policies and Terms of Use.
  • When connecting to the internet via a public network, use a VPN (virtual private network) or proxy server for a safer internet connection.
  • Check your browser security settings.
  • Use private web browsing or a private search engine (e.g., Firefox Focus, DuckDuckGo).
  • Use different passwords for different websites.
  But wait, there's more.
  • Install an ad blocker and anti-virus software.
  • Do not use your primary email address for online submissions.
  • Limit searching and browsing to credible sites.
  • Website certificates and encryption - look for secure sites that utilize https.  This is often indicated by a closed padlock icon in your search engine address bar.
  • When sharing your personal data on the internet, think the through the following practices.
    • FTP & SFTP: Use a file transfer protocol (FTP) service to share files online. A secure file transfer protocol service will ensure your files are being shared in a secure and private data stream. 
    • Perform regular backups (local and remote). 
    • Set access and editing privileges for the content you share with others.