ReadingRebus DATA MANAGEMENT PROPOSAL

1. What are the types of data that may be produced as part of this project?

• • How will data be collected (e.g., instrumentation, observation, survey, etc.)?
    • • High-resolution rebus images from cultural and scholarly institutions (libraries, galleries, archives, and special collections)
      • Bibliography collected from scholarly and library databases, booklist
  • Is it possible to regenerate the data? What are the implications for your research if the data are lost or became unusable later?
    • • Regeneration of research conclusions through textual citations and image credits
      • The website has its own files in its repository
  • What types of data will be produced, how much, and at what rate? Are the data types or the creation rate of data expected to change over time?
    • • Website metadata created by us
      • Descriptions and metadata of individual rebuses (between 20-30)
      • Content (essays) and analyses created by us
      • Code for website development
  • What are the tools or software you will be using to create/process/analyze/visualize the data?
    • • Microsoft Word, Google Docs, Google Sheets for word processing
      • NET and Adobe Photoshop for graphic design and in case a rebus image needs to be cropped, resized, or restored
      • Discord for group analysis and communication
      • WordPress website with plugins
  • What are your access, storage, and backup strategies?
    • • Monthly local and cloud backups of the WordPress website, images, database, and code from the web server
      • Casual local backups (informal)

2. What standards will you be using for data collection, documentation, description, and metadata?

• • How do you document data collection procedures?
    • • Audit log – (shared) document where, when data is collected, the collector or project manager will enter the date of data collection and a brief appraisal or summary of the data.
  • How will you ensure good project and data documentation? Who is responsible for implementing this data management plan?
    • • Patricia responsible for data management regarding website and code
      • Bianca responsible for data management regarding documents and process materials
  • What directory and file naming conventions will you be using?
    • • Naming will emerge from a combination of disciplinary conventions (i.e. puzzle identifying keywords; institutional cataloguing of visual and print ephemera; etc) and the categories that derive from our corpus as we amass it.
  • What project and data identifiers will be assigned?
    • • Identifiers will be assigned according to main categories/tags of rebuses that constitute our data set. These may include time period, geo location, type of rebus, theme, image/word-based, genre, medium, publisher location, language, etc.
  • Will you use disciplinary or community standards for data formatting, description, interoperability, or sharing for any of the data you collect?
    • • We expect to use disciplinary standards; at the same time, we may well develop and implement our own terms that further the understanding of rebuses as a corpus across location and time (any such terms will be shared in a data key or dictionary).

3. What steps will you take to protect your or your participant’s security, privacy/confidentiality, intellectual property, or other rights? (Check current university policies for requirements.)

• • Who controls the data (e.g., PI, student, lab, University, funder), and at what level?
    • • Project team controls data
      • Reproduction permissions will be granted by institutions
  • Any special privacy or security requirements (e.g., personal data, high-security data)?
    • • Website will have standard security measures (ssl, anti-spam, malware monitoring)
      • Personal data will not be stored on the website
  • Do you have any embargo periods to uphold?
    • • No

4. If you allow others to reuse your data, how will the data be accessed and shared?

• • What are the data sharing requirements your work is subject to (e.g., funder, journal)?
    • • Class data sharing requirements
  • Who is your possible audience? Who may use the data now, or later?
    • • Audiences may include:
        • • Etymologists and linguistic analysts.
          • Historians, anthropologists, and those interested in those fields.
          • Puzzle and rebus enthusiasts.
          • Word and Image scholars, scholars of visual culture
          • Digital Humanities students, colleagues, and the NYC DH community.
          • Wordsmiths and semioticians.
  • When will you publish the data and where?
    • • Publishing the data via the website starting march 2021
      • Also publishing data on social media starting march 2021
      • Course blog will also contain data
  • What tools/software are required to access your data?
    • • Access via Public-facing wordpress website and social media accounts

5. How will the data be archived for preservation and long-term access?

• • How long should the data be retained (e.g., 3-5 years, 10-20 years, permanently)?
    • • Website will be maintained for 3-5 years.
  • What file formats will you be using, or converting to? Are they sustainably accessible?
    • • Image file formats (jpgs, tiffs, gifs) provided by institutions
      • Website pages in html, php, and javascript
  • Who will maintain the data for the long-term?
    • • Patricia for now will maintain data
        
  • Which data archives are your data appropriate for (subject-based? institutional)?
    • • Subject-based data archives could include: word/image archives; 18th-19th century European and American visual/print culture; Communication studies; Digital Humanities archives.