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"Learning Linked Data" project planned for 2013+

From: Thomas Baker <tom@tombaker.org>
Date: Mon, 11 Jun 2012 17:35:03 -0400
To: SWIG <semantic-web@w3.org>
Message-ID: <20120611213503.GE88640@alpha.dublincore.org>
The University of Washington is leading a small workshop to plan for a
more ambitious grant, starting next year, targeted at helping
instructors and faculty who need to teach Linked Data technologies
understand the available software tools and their use in the classroom.
We are currently in the phase of collecting comments on an outline
of learning topics to be targeted in the project and of software 
tools needed by teachers and learners of those topics.

We would very much appreciate comments from potential teachers of Linked
Data technologies -- comments which can range from simple expressions of
interest (e.g., "we would find this extremely useful in our work on...")
to more detailed comments on the substance of our work, such as "it
would be especially helpful to have tutorial materials on Linked Data
tools usable by non-experts..." or "it would be helpful to have better
documentation on tools that help people visualize the characteristics of
large data sets..." or "that are based on open-source software..." --
whatever you see as a priority.  Comments that describe how the topic of
Linked Data bears specifically on what you teach would be especially

If you are a programmer, developer, or simply someone skilled in the use
of tools for processing or understanding datasets in the LOD cloud, it
would be great if you could comment on our characterization of tool 
categories (and exemplar tools), and if you have specific tools to
recommend, we will add them to our growing list.

We have posted a set of six one-page-long Web pages on a Wordpress blog
(see below) and would very much like to receive your comments on the
blog by the end of June.  

Many thanks,

"Learning Linked Data" - project plans 2013+ for comment

    "Learning Linked Data," a one-year planning activity under the
    National Leadership Program of the Institute of Museum and Library
    Services (IMLS) [1], is planning a project to support professional
    education and development by promoting software tools and skills
    needed for understanding and processing Linked Data.

    A planning workshop involving information-school faculty,
    information system consultants, students, and software developers
    identified the types of software tools needed for exploring a target
    set of learning topics.

    The follow-on project will engage instructors -- iSchool faculty,
    trainers, and consultants -- in dialog with developers -- experts in
    the use of tools, perhaps even the developers of those tools -- in
    order to produce documentation, screencasts, and the like, about how
    a target set of tools may be used in teaching, and specifically how
    they may be used in combination in addressing the target set of
    learning topics.

    Our activity has posted its analysis of learning topics and related
    software tools for public comment through June 30th [2].  We are
    interested in hearing from members of the target audience of library
    and museum information professionals about how they foresee using
    software tools for instruction and learning.  We are also interested
    in advice from software developers on what tools we should target,
    or in ways our project might help document or promote the use of
    those tools.

    [1] http://www.imls.gov/news/national_leadership_grant_announcement.aspx#WA
    [2] http://lld.ischool.uw.edu/wp/


               Learning Linked Data Project

                   Call for Comments


The Learning Linked Data Project, a planning activity funded under the IMLS
National Leadership Program from October 2011 through September 2012, has taken
a first step towards developing a software platform to help instructors,
students, and independent learners interpret and create Linked Data.  The
platform is envisioned to be of use to anyone offering training and education
in Linked Data principles and practice, whether in academia or professional
settings, in online instruction or in classrooms.  

As Linked Data is based on data structures of a linguistic nature, the guiding
metaphor for the project is that of designing a "language lab" -- a software
platform for analyzing and manipulating Linked Data in support of a wide range
of pedagogical approaches and expected learning outcomes.

The project has prepared a draft "Inventory of Learning Topics", with an
analysis of software required for such a platform, and posted it for public
review through 30 June 2012 on a blog at:


The document is divided into five short blog pages:

-- Understanding Linked Data [2]: "prerequisite" topics, specific to Linked Data,
   which must be grasped before a learner can meaningfully use software tools.
   The list of topics is linked to a three-page glossary [9] with definitions of
   terminology used.

-- Searching and Querying Linked Data [3]: just as language learners learn 
   through dialog with native speakers, learners of Linked Data must learn how
   to pose queries and explore datasets.  Tools for doing so include data
   validators, reasoners, query tools, and Semantic Web search engines.

-- Creating and Manipulating RDF Data [4]: In the Linked Data cloud,
   descriptions of things and descriptions of the vocabularies used to describe
   those things are all considered "data," so many of the basic tools for
   editing, mapping, converting, and extracting data may be adapted for
   different types of data.

-- Visualization [5]: Linked Data is conceptually diagrammatic in nature, and
   graphical tools can help the learner explore the statistical, spatial, or
   temporal characteristics of datasets by visualizing webs of data at various
   levels of granularity or by plotting the data to maps or timelines.

-- Implementing a Linked Data Application [6]: Simply learning how to interpret and
   manipulate Linked Data could stop with the topics outlined above.  The extent
   to which a language-lab-like platform for learning Linked Data should encompass
   tools for building real applications poses questions of scope on which the 
   project would appreciate input.

The project envisions the platform as a basis for the development of course
modules by people involved in both formal and informal learning environments,
so comments about the usefulness of such a platform for particular scenarios
would be especially welcome.

The comments received will be incorporated into a revised document and final
report to be published in September 2012. This report will be used as the basis
for a subsequent IMLS project proposal, to be submitted in early 2013, for
implementing the platform specified.

The partners of the Learning Linked Data Project are the University of
Washington, Kent State University, the University of North Carolina, JES &
Company, and 3 Round Stones, Inc. The project lead and contact person is Mike
Crandall of the University of Washington.

[1] http://www.imls.gov/news/national_leadership_grant_announcement.aspx#WA
[2] http://lld.ischool.uw.edu/wp/learning/understanding-linked-data/ 
[3] http://lld.ischool.uw.edu/wp/learning/searching-and-querying-linked-data/
[4] http://lld.ischool.uw.edu/wp/learning/creating-and-manipulating-rdf-data/
[5] http://lld.ischool.uw.edu/wp/learning/visualization/
[6] http://lld.ischool.uw.edu/wp/learning/implementing-a-linked-data-application/ 
[7] http://lld.ischool.uw.edu/wp/glossary/

Tom Baker <tom@tombaker.org>
Learning Linked Data
    Wiki: http://wiki.dublincore.org/index.php/Learning_Linked_Data
    List: http://dublincore.org/pipermail/learninglinkeddata/
Received on Monday, 11 June 2012 21:35:52 UTC

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