In a project led by the University of Washington, a group of interested
educators is planning a project, for a start date of next year, to help
instructors and faculty who teach Linked Data technologies understand
the available software tools and their use in the classroom.
We are currently collecting comments to a short analysis of learning
topics and related tools posted on a Wordpress blog (below). Comments
can range from simple expressions of interest to more detailed comments
on the substance of our planned project (e.g., priorities, from your
Comments -- either posted to the blog, or sent directly to me -- would
be especially helpful by the end of June .
Please feel free to distribute the attached descriptions to anyone
who might be interested.
 http://lld.ischool.uw.edu/wp/ - Call for Comments
"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) , 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
Our activity has posted its analysis of learning topics and related
software tools for public comment through June 30th . 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
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 : "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  with definitions of
-- Searching and Querying Linked Data : 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 : 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 : 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 : 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.
Tom Baker <t...@tombaker.org>
Learning Linked Data