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The second major category of BMI theories and methods that can support and
enable CTR are focused on the “ Question Formulation ” phase of such projects,
wherein investigators and their teams need to formulate data-centric research ques-
tions for subsequent analysis. Examples of the types of tools and technologies used
to support this category of information need include: (1) database query tools; data
mining and machine learning “workbenches”; (2) data visualization engines; and
(3) knowledge-based in silico hypothesis generation systems. Underlying the design
and optimal use of such tools and technologies are theoretical and methodological
frameworks related to data modeling, information theory, artifi cial intelligence,
knowledge engineering, and data visualization.
The third major category of BMI theories and methods that can support and
enable CTR are focused on the “ Analysis and Validation ” phase of such projects,
wherein investigators and their teams need to test and validate the results of the
research questions generated in the prior phase. Examples of the types of tools and
technologies used to support this category of information need include: (1) database
query tools; (2) statistical analysis packages; (3) data-centric scripting languages;
and (4) visualization tools. Underlying the design and optimal use of such tools and
technologies are theoretical and methodological frameworks related to the quantita-
tive data sciences, as well as information theory and HCI.
A fourth and cross-cutting type of BMI theories and methods that can support
and enable CTR are focused on “ Dissemination and Exchange of Knowledge ”,
wherein intermediate and fi nal knowledge products generated via all of the preced-
ing phases are delivered to stakeholders in a variety of human and computer readable
formats. Examples of the types of tools and technologies used to support this cate-
gory of information need include: (1) database management systems, (2) electronic
data interchange and sharing infrastructures, and (3) knowledge editing environ-
ments. Underlying the design and optimal use of such tools and technologies are
theoretical and methodological frameworks related to knowledge engineering, data
standards, software architecture, and human computer interaction.
6.5
Discussion
As noted at the outset of this chapter, the design, execution, analysis, and dissemina-
tion of results generated via CTR projects are complex and information-intensive
endeavors. The ability to effi ciently and effectively conduct CTR requires the avail-
ability of comprehensive and systematic data, information, and knowledge manage-
ment tools and methods. Furthermore, the importance of such platforms and
techniques is greatly amplifi ed when project involve geographically or temporally
distributed teams, as well as when the scientifi c aims of given project involve the
collection of multi-dimensional and heterogeneous data sets (for example, when a
study involves the collection and integrative analysis of patient-derived clinical and
bio-molecular phenotypes). To this end, we have introduced not only a general set
of categories that serve to defi ne the motivating information needs incumbent to
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