Justina Elmore's List: Data--Undergraduate Data Mgmt

• Dataverse Network Project
• we tend to think of the scholarly record in terms of published works. In light of data-intensive science, Lynch said the definition must be expanded to include the datasets
• federal records management mandate
• big numbers of small datasets. Often university libraries are the point of last resort for curating and preserving “long tail” data.
• identify where data is valuable and to build a culture that facilitates the its remix and reuse.

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• mismatches exist between research data and library digital warehouses, as well as the processes and procedures librarians typically use to fill those warehouses
• small-data producers
• great numbers of individual scientists and labs producing small data, however, immensely more consultations and consultants are necessary to bring practices and the resulting data to an acceptable standard.
• long-term data viability
• digital preservation systems designed to steward only final, unchanging materials can only fail faced with real-world datasets and data-use practices
• small data,' tend to be disorganised, poorly described if described at all, and in formats poorly suited to long-term reuse
• prepared to alienate researchers whose datasets are not chosen?
• Will they truly become estimators of data quality across the breadth of data-producing disciplines in the institution? If not, will they rely solely on technical criteria such as file format, regardless of data quality or importance? Whatever criteria are chosen, will those criteria conflict with institution-wide mandates such as the preservation of theses and dissertations with their accompanying materials
• SWORD protocol
• much repository software can only manage key-value pairs. Now that many, if not most, metadata and exchange standards for research data use XML or RDF as a base, this limitation seriously vitiates repositories' ability to manage datasets.
• polished storage
• manipulation and remix tools
• APIs, much less a mod- or plugin-friendly architecture
• how can one staff member expand the repository's mission to capture research data, given the many and vexing difficulties caused by their variability and the tremendous amount of hand-holding and reformatting necessary to massage those data into acceptable form for sharing and archival?
• endor-hosted solutions such as Ex Libris's DigiTool or BePress face a special problem: they do not control the technology

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• o, find that much repository software can only manage key-value pairs. Now that many, if not most, metadata and exchange standards for research data use XML or RDF as a base, this limitation seriously vitiates repositories' ability to manage datasets.
• manipulation and remix tools
• plugin-friendly architecture
• APIs,
• Ingest, storage, and end-user interfaces should be as loosely coupled as possible
• within as many
• environments
• reuse, remix, and re-evaluation
• DSpace is a classic silo, and EPrints requires multiple software instances to accommodate differing interface needs.
• Fedora Commons
• s, though projects such as Hydra [11] and Islandora [12] are beginning to fill the gaps. The key is that a Fedora repository running Islandora need not accept and disseminate materials only through Islandora's connection to a Drupal content-management system;
• curation microservices' stack at the California Digital Library
• de-accessioning and removal
• building data and metadata with the express intent of easy sharing and remixing.

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• presenting challenges to researchers and to publishers, funding agencies, and others both within and external to the academic community
• emphasis on publishing data in ways that ease re-use and promoting accountability and integration
• Data as collections; data as services
• to support the intake, preservation and reuse of this digital content,

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• Making the Case for Research Data Management
• establishing research data policies and services that will support them
• resources that can be pooled more effectively
• from its entry to the research cycle through to the dissemination and archiving of valuable results.
• ensuring that what is handed over to a repository or publisher remains fit for secondary use
• Researchers should consider how data will be gathered, analysed and managed, and how and in what form relevant data will eventually be made available to others, at an early stage of the design of the project
• mandated Data Management Plans as a condition for funding
• evidence that making data related to an article publicly available correlates with higher citation rates,
• second use of data from the Hubble Space Telescope has now overtaken those based on the initially proposed use
• datasets gain more recognition as outputs in their own right
• data in a reusable form
• need for a shared approach across institutions to help them build research data management skills, capability and organisation
• Data Management Recommendations for Research Centres and Programmes

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