NeoRef
NeoRef is an archive for any digital
material including articles, research notes, books, genetic sequences, concepts,
and for derived data including indexing, reviews, claims. Areas of emphasis
include optimization of the author self contribution process (user interface,
selection and assignment of index terms from controlled vocabularies), automatic
metadata extraction from existing materials, optimization of user interfaces
for searching from very large content sets (federated universal open archives),
and extending metadata to include "claims" to capture higher level knowledge
representations about linkages between content items (in particular extending
the ScholOnto work to the domain of bioinformatics). An example
implementation is documented in our 2008 YouTube video on NeoNote.
We also study the technical
and policy issues involved with freely available archives of all scholarly
literature that allow for the storage, searching and retrieval of information
without the need for the traditional framework of publishers and review systems.
A general NeoRef presentation is NeoRef
Scholarly Communications
Digital Libraries
Dr. Hemminger helped found The Center for Research and Development of Digital
Libraries (CRADLE) in 2002, and currently serves as the organizer of the group.
This project brings together many active digital library researchers and projects
at UNC and worldwide. He is also interested in Electronic Theses and Disserations.
He has developed a ETD for SILS scholarly literature (part of NeoRef), and
leads the campus group charged with investigating and implementing ETDs for
UNC. ETDs
User Interface Design
Development of computer workstations as the display interfaces for the practice
of medicine, and in particular, radiology. Previous work includes design principles
for radiology workstation design, and specific designs and implementations
(chest CT, mammography, 3D). Current interests include (1) investigating what
choices of mental models and roam and zoom techniques are most effective when
using images larger than the display resolution, and (2) effective CHI techniques
for dynamic searching of very large sets of content items (ie. universe of
scholarly publications).
Bioinformatics
Ultrastructure: Working with Mike Giddings and Jeff Long to study
the application of Ultrastructure, a novel notational system to represent
knowledge in a flexible way using relational databases, to bioinformaticss
to represent and integrate current and future information information from
all genome sciences domains. Mouse Database: working with Terry Magnuson,
Jay Vivian and Yijing Chen to design and implement a database for their mouse
mutation project. The challenge is to track the clone (created from frozen
library, mutagenized with ENU) associated with phenotype changes. Proteomics
Database: Project with Marshall Pope and Christoph Borchers of the Proteomics
Core Facility to develop standardized interchange of proteomics experimental
data. Plant Comparative Genetics: Project with Todd Vision of Biology to investigate
database design for storage and query when doing comparative genome studies.
The long range intent to have comparative measure of the tree of life.
Virseum
I have proposed a methodology for digitally capturing both the content and
entire exhibits of museums, so that they can be visited in a virtual reality
setting. The virtual reality representation is unique in that the environments
and objects are captured and displayed in way that is both visually compelling
(photographic quality), and spatial accurate (millimenter measurements are
possible). This work is in conjunction with 3rdTech, who developed the DeltaSphere
digitizer. Virseum
Medical Informatics
Digital Imaging and Communications (DICOM) standards work. Dr. Hemminger chairs
Working Group 11 (Display), and is an active member and author in Working
Groups 15 (Digital Xray, Mammo, Computer Aided Detection), Working Group 17
(3D), AAPM Task group 18 (Electronic Display). For a listing of existing DICOM
international standards and new standards under development see the DICOM
website at NEMA.
Databases
Integating disparate databases. Handling very large databases. Primary
emphasis is on biological databases (genetics, protoemics, metabolomics).
Datamining
Knowledge discovery via data mining of large and integrated databases. Application
of statistical pattern recognition and feature analysis techniques to the
analysis of genomic and proteomic databases.