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DCERC Collection

This collection contains posters and associated documents produced from 2012-2014 by students in the Data Curation Education in Research Centers (DCERC) program. DCERC was an Institute of Museum and Library Services (IMLS) funded program to provide library and information science students with internship experiences in the NCAR research & data center environment.

Curating context and use: Pulling scientific workflows into the repository
Though data curation is often discussed as a discrete process (e.g. Higgins 2008), in reality it is highly dependent on scientific workflows. Yet, a data curator's understanding of a dataset is typically limited to her experience of it within a repository: separate from its context of production, and separate from its use. Here, we explore ways data curators can collect metadata about context and use via two projects at the National Center for Atmospheric Research (NCAR).
Data curation in the long tail of science: Preparing Community Land Model validation data for reuse and preservation
Long tail science is argued to account for the majority of scientific output1. Long tail scientific research tends to be conducted by small research teams with limited budgets, affecting the team’s ability to properly curate their data for reuse and preservation. The data set that was curated in this project is a small data set of global soil properties that was processed for use with the Community Land Model (CLM). The Data Curation Profile Toolkit3 was utilized to work with the scientist in order to determine his needs with respect to curation of the data set. Through a number of formal interviews, it was established that the scientist required assistance in documenting the data workflow, updating the metadata, and eventually archiving the data with an appropriate repository.
Discovering new global climate patterns: Curating a 21-year high temporal (hourly) and spatial (40km) resolution reanalysis dataset
The National Center for Atmospheric Research (NCAR) Global Climate Four-Dimensional Data Assimilation (CFDDA) Hourly 40km Reanalysis dataset is a dynamically downscaled dataset with high temporal and spatial resolution that was created using NCAR's CFDDA system. The dataset contains three-dimensional hourly analyses in netCDF format for the global atmospheric state from 1985 to 2005 (a total of 184,080 files) on a 40km horizontal grid (0.4°grid increment) with 28 vertical levels, providing good representation of local forcing and the diurnal variation of processes in the planetary boundary layer. Making the dataset publicly available, accessible, and usable will provide a significant resource with greater diurnal cycle details to allow and promote studies of new climate characteristics.
Now you are speaking my language: Translating and facilitating between researchers and data managers
Despite the importance of data curation, data managers do not understand the needs and goals of scientists and scientists are not concerned with data. Cross-disciplinary research adds an additional challenge. Many Data Repositories do not contain cross-disciplinary data and face complications in the curation process. The goal of this project is to help both data managers and scientists to enhance communication, create a manual for best practice, and create a data management plan.
The data lifecycle flow: For me, this time
A discussion on the lifecycle data completes from research to access, use, and reuse.