Designing for User-facing Uncertainty in Everyday Sensing and Prediction

Thesis (Ph.D.)--University of Washington, 2016-07

Terminology Cross-Domain Final Report

The InterPARES 2 Terminology Cross-Domain has created three terminological instruments in service to the project, and by extension, Archival Science. Over the course of the five-year project this Cross-Domain has collected words, definition, and phrases from extant documents, research tools, models, and direct researcher submission and discussion. From these raw materials, the Cross-Domain has identified a systematic and pragmatic way establishing a coherent view on the concepts involved in dynamic, experiential, and interactive records and systems in the arts, sciences, and e-government.The three terminological instruments are the Glossary, Dictionary, and Ontologies. The first of these is an authoritative list of terms and definitions that are core to our understanding of the evolving records creation, keeping, and preservation environments. The Dictionary is a tool used to facilitate interdisciplinary communication. It contains multiple definitions for terms, from multiple disciplines. By using this tool, researchers can see how Archival Science deploys terminology compared to Computer Science, Library and Information Science, or Arts, etc. The third terminological instrument, the Ontologies, identify explicit relationships between concepts of records. This is useful for communicating the nuances of Diplomatics in the dynamic, experiential, and interactive environment.All three of these instruments were drawn from a Register of terms gathered over the course of the project. This Register served as a holding place for terms, definitions, and phrases, and allowed researchers to discuss, comment on, and modify submissions. The Register and the terminological instruments were housed in the Terminology Database. The Database provides searching, display, and file downloads – making it easy to navigate through the terminological instruments.Terminology used in InterPARES 1 and the UBC Project was carried forward to this Database. In this sense, we are building on our past knowledge, and making it relevant to the contemporary environment.

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.