Getting to Green - Research Progress on Environmental Health and Safety Aspects of Engineered Nanomaterials - page 58

branches of research on the EHS aspects of nanotechnology. New programs, such as NanoRelease (ILSI
2013a) and NanoCharacter (ILSI 2013b), have similar aims, and the knowledge commons would aid in
supporting government, industry, and academic participation in such programs. Such new initiatives as
the Nanotechnology Knowledge Infrastructure (NSET 2012a; NNI 2013) and the Materials Genome
Initiative (MGI) (NSTC 2011; EOP 2012; Warren and Boisvert 2012) could provide additional linkage
and informatics expertise in augmenting the knowledge commons for different users and programs.
Researchers involved in those initiatives are aware of each other's goals and progress because there is
much overlap in membership, participation in each other's workshops, occasional briefings, and
coordination through the National Nanotechnology Coordination Office (NNCO). However, discussions
on an overarching framework that would knit their separate resources, capabilities, and objectives into the
knowledge commons presented here have not yet taken place. Initiation of a series of pilots to integrate
data and knowledge generated from the several activities and other informatics efforts would provide both
a core planning group and an initial effort to set appropriate informatics requirements relevant to all
activities whether private or public.
It is important to note that many other activities could provide valuable input into establishment
of the knowledge commons and the present report is not intended to be comprehensive. Although this
report is primarily focused on integrating research data, methods, and models relevant to the properties
and effects of nanomaterials and nanomaterial-containing products in biologic and environmental
systems, other related fields such as epidemiology and nanomedicine have not been the focus. However,
the goals and structure of the knowledge commons are sufficiently broad to accommodate the integration
of data, methods, and models used by stakeholders in these related fields. First, the evaluation of both
EHS risk and product-design risk involves uncertainty propagation and the documentation and sharing of
errors, uncertainties, sensitivities, and expert opinion through the knowledge commons and the
informatics systems (see NRC 2012, pp.175-178 and Appendix B). Second, the emphasis on the need for
data, method and model validation, curation, and sharing applies to all relevant fields, and reflects similar
concerns and goals of other programs (for example, Big Data 1 and the MGI) as well as goals of the
Network and Information Technology Research and Development (NITRD) program (NITRD 2013a).
Third, as discussed in NRC 2012 (pp.175-178), existing nanoinformatics are compatible with National
Cancer Institute and National Institutes of Health biomedical systems and applications, and recent
progress, such as with the ISA-TAB-Nano data format capability extend that commonality to data
exchange nomenclature and formats, including both genomics and clinical studies. Finally, there is
evidence of convergence in vision among different informatics activities with examples, including US
NanoHUB (NanoHUB.org 2013 ) and European Union NANOhub (JRC 2013), whose focus and goals
overlap substantially, and collaborations involving EU-US CoRs and the NanoSafety Cluster (NanoSafety
Cluster 2013).
Steps to Improve Progress in Developing the Knowledge Commons
Steps that could be taken to improve progress in development of the knowledge commons have
been foreshadowed in the preceding pages and in Chapter 4 of the committee's first report (NRC 2012).
The brief summary below broadly outlines the type of coordination that is needed to initiate development
of a viable and vibrant knowledge commons that is responsive to the changing needs of the research and
translational communities. The common theme underlying model, method, and material development is
the need to provide data and knowledge to improve the reproducibility of the models, methods, and
materials.
To achieve reproducibility of models, there must be a means for publishing models with their run-
time parameters, files, sample data, baseline results, and metadata concerning the range of validity.
Virtual collaborative environments associated with each model or model type would allow focused
1 For additional details see the workshop on Data Sharing and Metadata Curation: Obstacles and Strategies
(NITRD 2013b).