Authentic Learning in the Research Data Curation Classroom

We explore the provision of authentic learning through curation of scientific research data collections as preparation for information professionals. Hands on experience with curating a research data collection is provided in a graduate level classroom. Students gain insight into work with research data through online exploration of a data repository as well as via contact with a repository information professional. Four major elements of a student data collection curation project are described: selecting a data collection, developing a draft data curation plan, keeping a data collection activity log, and summarizing via formative and summative reports. The data curation project provided an experience mix of the curation culture and its services with data generating research cultures and their emergent practices.ye

Scientific Knowledge Mobilization: Co-evolution of Data Products and Designated Communities

Digital data are accumulating rapidly, yet issues relating to data production remain unexamined. Data sharing efforts in particular are nascent, disunited and incomplete. We investigate the development of data products tailored for diverse communities with differing knowledge bases. We explore not the technical aspects of how, why, or where data are made available, but rather the socio-scientific aspects influencing what data products are created and made available for use. These products differ from compact data summaries often published in journals. We report on development by a national data center of two data collections describing the changing polar environment. One collection characterizes sea ice products derived from satellite remote sensing data and development unfolds over three decades. The second collection characterizes the Greenland Ice Sheet melt where development of an initial collection of data products over a period of several months was informed by insights gained from earlier experience. In documenting the generation of these two collections, a data product development cycle supported by a data product team is identified as key to mobilizing scientific knowledge. The collections reveal a co-evolution of data products and designated communities where community interest may be triggered by events such as environmental disturbance and new modes of communication. These examples of data product development in practice illustrate knowledge mobilization in the earth sciences; the collections create a bridge between data producers and a growing number of audiences interested in making evidence-based decisions.

A Discussion of Value Metrics for Data Repositories in Earth and Environmental Sciences

Despite growing recognition of the importance of public data to the modern economy and to scientific progress, long-term investment in the repositories that manage and disseminate scientific data in easily accessible-ways remains elusive. Repositories are asked to demonstrate that there is a net value of their data and services to justify continued funding or attract new funding sources. Here, representatives from a number of environmental and Earth science repositories evaluate approaches for assessing the costs and benefits of publishing scientific data in their repositories, identifying various metrics that repositories typically use to report on the impact and value of their data products and services, plus additional metrics that would be useful but are not typically measured. We rated each metric by (a) the difficulty of implementation by our specific repositories and (b) its importance for value determination. As managers of environmental data repositories, we find that some of the most easily obtainable data-use metrics (such as data downloads and page views) may be less indicative of value than metrics that relate to discoverability and broader use. Other intangible but equally important metrics (e.g., laws or regulations impacted, lives saved, new proposals generated), will require considerable additional research to describe and develop, plus resources to implement at scale. As value can only be determined from the point of view of a stakeholder, it is likely that multiple sets of metrics will be needed, tailored to specific stakeholder needs. Moreover, economically based analyses or the use of specialists in the field are expensive and can happen only as resources permit

Curating data collections in the classroom: lessons learned.

unpublishednot peer reviewe

Longitudinal diffusion tensor imaging shows progressive changes in white matter in Huntington’s disease

This work has been supported by the European Union — PADDINGTON project and all authors, with the exception of RS, SG and HZ receive funding from this project. RS, SG and HZ are supported by the CHDI/High Q Foundation, a not-for-profit organization dedicated to finding treatments for Huntington's disease. This work was undertaken at UCLH/UCL supported by the National Institute for Health Research [NIHR] University College London Hospitals [UCLH] Biomedical Research Centre [BRC].BACKGROUND: Huntington’s disease is marked by progressive neuroanatomical changes, assumed to underlie the development of the disease’s characteristic symptoms. Previous work has demonstrated longitudinal macrostructural white-matter atrophy, with some evidence of microstructural change focused in the corpus callosum. OBJECTIVE: To more accurately characterise longitudinal patterns, we examined white matter microstructural change using Diffusion Tensor Imaging (DTI) data from three timepoints over a 15 month period. METHODS: In 48 early-stage HD patients and 36 controls from the multi-site PADDINGTON project, diffusion tensor imaging (DTI) was employed to measure changes in fractional anisotropy (FA) and axial (AD) and radial diffusivity (RD) in 24 white matter regions-of-interest (ROIs). RESULTS: Cross-sectional analysis indicated widespread baseline group differences, with significantly decreased FA and increased AD and RD found in HD patients across multiple ROIs. Longitudinal rates of change differed between HD patients and controls in the genu and body of corpus callosum, corona radiata and anterior limb of internal capsule. Change in RD in the body of the corpus callosum was associated with baseline disease burden, but other clinical associations were not significant. CONCLUSIONS: We detected subtle longitudinal white matter changes in early HD patients. Progressive white matter abnormalities in HD may not be uniform throughout the brain, with some areas remaining static in the early symptomatic phase. Longer assessment periods across disease stages will help map this progressive trajectory.PostprintPeer reviewe

Data Conservancy Provenance, Context, and Lineage Services: Key Components for Data Preservation and Curation

Among the key services that institutional data management infrastructures must provide are provenance and lineage tracking and the ability to associate data with contextual information needed for understanding and use. These functionalities are critical for addressing a number of key issues faced by data collectors and users, including trust in data, results traceability, data transparency, and data citation support. In this paper, we describe the support for these services within the Data Conservancy Service (DCS) software. The DCS provenance, context, and lineage services cross the four layers in the DCS data curation stack model: storage, archiving, preservation, and curation