HypER 2009: Hypotheses, Evidence & Relationships

You know that feeling that you’ve come home? I recently joined a 2-day workshop at Elsevier’s Disruptive Technology Labs, Amsterdam, where an exciting group of people shared what is clearly a harmonic convergence that’s been waiting to happen for a long time. HypER: Hypotheses, Evidence & Relationships is the name we gave ourselves. From the nascent wiki homepage:

The next step in the evolution of the digital research infrastructure is the detection, navigation and analysis of  Hypotheses, Evidence & Relationships in the literature: the building blocks of knowledge-level claims.

This community brings together researchers in argumentation, computational linguistics, sociology of science, hypermedia, semiotics, semantic and pragmatic web.

Check out the participants and presentations from Day 1, and the ensuing activity streams to take this forward… such as intersection with the W3C Scientific Discourse working group.

What makes this particularly exciting from the perspective of our Hypermedia Discourse group is that we’ve been working since 1998 on tools and theory for human-annotation of discourse relations, while meantime, the machines have been getting smarter at extracting certain forms of these from traditional scientific texts. Now, as I argued in my presentation, there’s potentially a marriage made in heaven for us to really move the knowledge infrastructure forward, out of the shadow of the printing press, into a network-native environment that takes seriously the power of the social/semantic web. Moreover, it takes seriously the pragmatic level of communication by recognising the rhetorical role that different statements play in scientific communications.

My specific argument on the human+machine annotation synergy is that no matter how smart the machines get, we will always need human annotation of hypotheses, evidence, and discourse relationships, and very high quality user interfaces (Slide 10):

Researchers read meanings into texts that are not there, and with which the author might disagree

  • so we will always require manual annotation tools
  • we need ways to make connections to connections
  • extremely complex connections may remain the province of human sensemaking (e.g. is analogous to)

Good user interfaces will be needed

  • to view, edit and navigate HypERnets, whether manually or automatically constructed

Scientific discourse is a social process

  • we take huge care in our writing about how we position ourselves in relation to our peers — will we trust unsupervised machines to extract and position our more complex claims?
KMi HypER 2009

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3 Responses to “HypER 2009: Hypotheses, Evidence & Relationships”

  1. […] events are being energised through the group that convened May’s HyPER Workshop that I reported on previously, who represent an exciting convergence in disciplines and technology for prototyping the […]

  2. […] moves. A decade on, there is a growing network of researchers focused on this challegne (see blog post on Hyp-ER), the machines have got smarter, and here we are integrating machine and human annotation within […]

  3. […] from extremely productive interactions with members of the emerging Hyp-ER community, including most recently, Ágnes Sándor’s visiting fellowship, this survey article on […]

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