W3C
HCLS-SIG
Knowledge
Ecosystem Task Force Proposal
Problem Statement
Scientific knowledge
discovery, publication and discourse
can be understood as a knowledge ecosystem containing numerous
lifecycle
processes. Currently, information in this ecosystem is produced, moves
within
and is exchanged across public, corporate, private, institutional, and
collaboration ownership spaces in the form of millions of semantically
uncharacterized digital resources.
Scientists and
health care
providers increasingly rely on these resources to an extraordinary
degree.
These digital resources
can potentially be richly
interconnected and contextualized in terms of one another. Establishing these
interconnections
is part of the process of creating, sharing, discussing, publishing and
consuming new knowledge. However, such ecosystem process activities are not currently
well-supported
by digital models, because information interconnections across
processes in the
“knowledge ecosystem” currently lack a complete machine-accesible
semantic
characterization.
For example, there is
currently no widely recognized
machine-accessible semantic differentiation between a manuscript and a
publication; or between an illustration and experimental image data; or
between
an experiment, its data, the data interpretation, and the hypothesis
the
experiment was designed to validate.
This problem exists
across multiple scientific domains. We believe that solving the
semantic characterization problem at the common
level of knowledge processes, can facilitate not only the organization
and
exchange of knowledge within domains but across them. This will be
particularly important in goal-oriented clinical research but can be
expected to
benefit the entire life science and health care community.
Mission and Scope
Our mission in this task
force is to develop a collective
understanding, and shared semantic models, of inter-related digital
knowledge
artifacts in the research process as they propagate through
laboratories,
academic communities, collaborations, research institutes, scientific
publishers, bibliographic knowledge bases, and companies.
These models will be
representations of common process
elements in the ecosystem and their transitions of evidentiary support,
accessibility, meaning, interconnectedness and ownership. They will
function as
a semantic interoperability layer between the many domain (and
personal)
ontologies in life science and health care by establishing agreed
semantics of
the knowledge processes in which the artifacts characterized by the
domain
ontologies are created, evolved and consumed.
A simple way
of visualizing
the mission of this group is to imagine the processes by which digital
resources circulate in the knowledge ecosystem as horizontal layers
connecting
information across vertical domains of health care and life science
research
and practice areas. While each separate vertical domain may require its
own
specialized ontology, the semantics of the ecosystem process model(s)
can
connect the domains and provide an important means of interoperating
across
their ontologies.
The primary
intent of
developing common semantic models of the knowledge ecosystem processes
is to
accelerate scientific discovery. We hypothesize such models will
achieve this
by facilitating:
(1)
improved personal-,
laboratory-,
and research community-level organization and characterization of
knowledge;
(2)
high-bandwidth knowledge
interoperability between
knowledge
producers and consumers, based upon the ability to publish, interchange
and
share richly contextualized resources;
(3)
creation of fluid
bridging and
interoperability across domain and personal ontologies, using shared
models;
and
(4)
vastly improved
capability of
autonomous software agents to navigate and extract meaning from a
developing
corpus of semantically characterized digital resources.
Charter Relevance
The mission of
this Task
Force supports the following goals of HCLS SIG’s charter:
(1)
define core
vocabularies that can
bridge data and ontologies developed by individual communities of
practice in
HCLS
(2)
provide … descriptive
vocabularies to better enable the integration and relationships among
people,
data, observations, software, collections of algorithms, and scholarly
publications
/ clinical trials.
Statement of Objectives
1.
Prepare a set of
general use
cases defining the application of a knowledge process ontology to key
research
and practice areas of HCLS.
2.
Prepare a draft
ontology
supporting the use cases, with accompanying white paper.
3.
Conduct a
comprehensive
discussion on the draft ontology and use cases with input from multiple
sources, resulting in revised drafts.
4.
Develop an open and
diverse set
of interoperating pilot applications to validate and refine the use
cases and
ontology.
5.
Recruit additional
members and
solicit active involvement from key players in the space, such as
academic
publishers, academic libraries, research institutes, individual
laboratories,
health care providers, and pharmaceutical companies.
6.
Task Force Final
Report: a
one-year assessment of development activities, lessons learned, etc.
with
recommendations for future activities, if any, to be undertaken by new
task
forces.
Tasks and Deliverables
1.
Initial Draft Use
Case
Document: March 30, 2006 – in consultation and collaboration with
the other
working groups.
2.
Initial Draft
Process Ontology
& Whitepaper: April 30, 2006.
3.
Revised Drafts of
Use Cases
and Process Ontology: June 30, 2006 – in consultation and
collaboration
with the other working groups.
4.
Pilot Applications:
March
2006 through December, 2007.
5.
RECRUITMENT AND
ADDITIONAL
INPUT: ongoing.
6.
Task Force Final
Report:
March 31, 2007.