Knowledge Workers and Associative Activity: An Examination of Knowledge Work Systems and Settings

Thesis (Ph.D.)--University of Washington, 2016-08

Software and Space: Investigating How a Cosmology Research Group Enacts Infrastructure by Producing Software

Thesis (Ph.D.)--University of Washington, 2016-08

Data, Software, and Advanced Computational Usage of University of Washington Research Leaders

Scientific research is increasingly data-intensive, relying more and more upon advanced computational resources to be able to answer the questions most pressing to our society at large. This report presents findings from a brief descriptive survey sent to a sample of 342 leading researchers at the University of Washington (UW), Seattle, Washington in 2010 and 2011 as the first stage of the larger National Science Foundation project “Interacting with Cyberinfrastructure in the Face of Changing Science.” This survey assesses these researcher’s use of advanced computational resources, data, and software in their research. We present high-level findings that describe UW researchers’: demographics, interdisciplinarity, research groups, data use, software and computational use—including software development and use, data storage and transfer activities, and collaboration tools, and computing resources. These findings offer insights into the state of computational resources in use during this time period as well as offering a look at the data intensiveness of UW researchers.

Surveying Scientists About Their Software

Software is an important infrastructural component of scientific research practice. The work of research often requires scientists to develop, use, and share software in order to address their research questions. This report presents findings from a survey of researchers at the University of Washington in three broad areas: Oceanography, Biology, and Physics. This survey is part of the National Science Foundation funded study Scientists and their Software: A Sociotechnical Investigation of Scientific Software Development and Sharing (ACI-1302272). We inquired about each respondent’s research area and data use along with their use, development, and sharing of software. Finally, we asked about challenges researchers face with and about concerns regarding software’s effect on study replicability. These findings are part of ongoing efforts to develop deeper characterizations of the role of software in twenty-first century scientific research.

Urban Design Guidelines for Human Wellbeing in Martian Settlements

Thesis (Master's)--University of Washington, 2016-06

SITE 1121 - FIELD NOTES Revealing Deep Form as a Basis for Urban Landscape Design

Thesis (Master's)--University of Washington, 2016-06

Role for cell-to-cell communication in stem cell specification toward pancreatic progenitors: relevance to the design of novel therapies for diabetes.

Thesis (Ph.D.)--University of Washington, 2016-08

Layered Information Modeling and a Knowledge Organization Paradigm: Inherent Classification and the Design of Interoperable Systems

In knowledge technology work, as expressed by the scope of this conference, there are a number of communities, each uncovering new methods, theories, and practices. The Library and Information Science (LIS) community is one such community. This community, through tradition and innovation, theories and practice, organizes knowledge and develops knowledge technologies formed by iterative research hewn to the values of equal access and discovery for all. The Information Modeling community is another contributor to knowledge technologies. It concerns itself with the construction of symbolic models that capture the meaning of information and organize it in ways that are computer-based, but human understandable. A recent paper that examines certain assumptions in information modeling builds a bridge between these two communities, offering a forum for a discussion on common aims from a common perspective. In a June 2000 article, Parsons and Wand separate classes from instances in information modeling in order to free instances from what they call the “tyranny” of classes. They attribute a number of problems in information modeling to inherent classification – or the disregard for the fact that instances can be conceptualized independent of any class assignment. By faceting instances from classes, Parsons and Wand strike a sonorous chord with classification theory as understood in LIS. In the practice community and in the publications of LIS, faceted classification has shifted the paradigm of knowledge organization theory in the twentieth century. Here, with the proposal of inherent classification and the resulting layered information modeling, a clear line joins both the LIS classification theory community and the information modeling community. Both communities have their eyes turned toward networked resource discovery, and with this conceptual conjunction a new paradigmatic conversation can take place. Parsons and Wand propose that the layered information model can facilitate schema integration, schema evolution, and interoperability. These three spheres in information modeling have their own connotation, but are not distant from the aims of classification research in LIS. In this new conceptual conjunction, established by Parsons and Ward, information modeling through the layered information model, can expand the horizons of classification theory beyond LIS, promoting a cross-fertilization of ideas on the interoperability of subject access tools like classification schemes, thesauri, taxonomies, and ontologies. This paper examines the common ground between the layered information model and faceted classification, establishing a vocabulary and outlining some common principles. It then turns to the issue of schema and the horizons of conventional classification and the differences between Information Modeling and Library and Information Science. Finally, a framework is proposed that deploys an interpretation of the layered information modeling approach in a knowledge technologies context. In order to design subject access systems that will integrate, evolve and interoperate in a networked environment, knowledge organization specialists must consider a semantic class independence like Parsons and Wand propose for information modeling.