Tuesday, June 23, 2009

DH09: Christine Borgman, Scholarship in the Digital Age: blurring the boundaries between the sciences and the humanities

Digital Humanities Manifesto 2.0 illustrates the difficulty of defining the 'humanities'. Whose problem is this to organize digital information? Answer: 'Humanists must plan their digital future' which is also the title of a recent article in the Chronicle of Higher Education by Johanna Drucker.

Outline of talk:
  • scholarly information infrastructure
  • science (and, or, vs ) humanities
  • call to action

scholarly information infrastructure

Infrastructure must be convergent. Cyberinfrastructure, eScience, eSocialScience, eHumanities, eResearch, are all used to describe this phenomenon. Goal: enable new forms of scholarship that are emergent(information-intensive, data-intensive, distributed, collaborative). We must build a research agenda for digital scholarship.

science (and, or, vs ) humanities

a) Publication practices
Why do scholars publish? Legitimization, dissemination, and access, preservation, curation. Things in the humanities are out of print before they are out of date. This is the opposite to the sciences. ArXiv.org received 5000 articles for publishing; over a million hits per day.

b) Data
Data in digital scholarship is becoming scholary capital. They are no longer thrown away but keep and reused, posted and shared. Also, asking new questions with extant data, e.g. computational biology, collaborative research. This is coming to the humanities! What is data? observational, computational experimental, and records, mostly applying to science (long-lived data, NSF, 2005). Are data objective or subjective? Data can be facts, 'alleged evidence' (Buckland, 2006). Examples: Scientific data weather, ground water, etc. Examples in the social sciences include opinion polls, interviews, etc. Humanities and arts data examples would be newspapers, photographs, letters, diaries, books, articles marriage records, maps, etc. (A comment from the audience afterward mentioned that these aren't our data; it is arguments, patterns, etc.). Sources can be libraries, archives, museums, public records, corporate records, mass media, acquire from other scholars, and data repositories. (Read 'The end of theory: the data deluge makes scientific method obsolete' in Wired, 16.07). What is data in the humanities will drive what is captured and reused and curated in the future!

c) Research methods
The research labs in the future of humanities will be blended, common work places. New problem solving methods in the sciences: empirical, theory, simulation, and the current one is data (Jim Gray). y=e(x squared). E.g. Sloan Digital Sky Survey provides open access to data in astronomy. e.g. Life Under Your Feet. e.g. Rome Reborn Project

d) Collaboration
Science is mostly collaborative; humanities is not. 6-10 years working alone on a dissertation makes it difficult to work in a collaborative environment. CENS (Center for Embedded Networked Sensing). What are CENS data? e.g. Dozens of ways to measure temperature.

e) Incentives (Chapter 8 of her book)
Motivations include coercion, open science, etc. Rewards for publication, effort to document data, competition, priority of claims, intellectual property issues like control over data.

f) Learning
'Fostering Learning in the Networked World', 2008. Cyberlearning is the use of networked computing and communications. A couple of recommendations: build a cyberlearning field and instill a 'platform perspective' like Zotero; enable students to use data; promote open educational resources. Why openness matters: interoperability trumps all, add value; discoverability of tools, reusability.

Call to action

Publication practices: increase speed and scope of dissemination through online publishing and open access.
Data: define, capture, manage, share, and reuse data.
Research methods: adapt practices to ask new questions, at scale, with a deluge of data.
Collaboration: find partners whose expertise complements yours, listen closely, and learn.
Incentives: identify best practices for documentation, sharing and licensing humanities content.
Learning: build a vibrant digital humanities community starting in the primary schools.
Generally: err towards openness, reusability, and generalizability.

Future Research questions/problems:

What is data?
What are the infrastructure rwequirements?
Where are the social studies of digial humanities?
What is the humanities laboratory of the 21st century?
What is the value proposition for digital humanities in an era of declining budgets?

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