How to Discover Requirements for Research Data Management Services Angus Whyte (DCC) and Suzie Allard (Dataone)
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Module 8 Wiki Guide
Best Practices for Biomedical Research Data Management Harvard Medical School, The Francis A. Countway Library of Medicine Module 8 Wiki Guide Learning Objectives and Outcomes: 1. Emphasize characteristics of long-term data curation and preservation that build on and extend active data management ● It is the purview of permanent archiving and preservation to take over stewardship and ensure that the data do not become technologically obsolete and no longer permanently accessible. ○ The selection of a repository to ensure that certain technical processes are performed routinely and reliably to maintain data integrity ○ Determining the costs and steps necessary to address preservation issues such as technological obsolescence inhibiting data access ○ Consistent, citable access to data and associated contextual records ○ Ensuring that protected data stays protected through repository-governed access control ● Data Management ○ Refers to the handling, manipulation, and retention of data generated within the context of the scientific process ○ Use of this term has become more common as funding agencies require researchers to develop and implement structured plans as part of grant-funded project activities ● Digital Stewardship ○ Contributions to the longevity and usefulness of digital content by its caretakers that may occur within, but often outside of, a formal digital preservation program ○ Encompasses all activities related to the care and management of digital objects over time, and addresses all phases of the digital object lifecycle 2. Distinguish between preservation and curation ● Digital Curation ○ The combination of data curation and digital preservation ○ There tends to be a relatively strong orientation toward authenticity, trustworthiness, and long-term preservation ○ Maintaining and adding value to a trusted body of digital information for future and current use. -
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a centre of expertise in data curation and preservation The Digital Curation Centre Hugh Corley DCC Services and Outreach Liaison Officer Funders: 1 University College London Information Day :: 16th January 2007 a centre of expertise in data curation and preservation What is an Information Day • Learn • Discuss • Action Funders: 2 University College London Information Day :: 16th January 2007 a centre of expertise in data curation and preservation Overview • Digital Curation • Aims of the DCC • Work of the DCC Funders: 3 University College London Information Day :: 16th January 2007 a centre of expertise in data curation and preservation Digital Curation • Active management of data over life- cycle of scholarly and scientific interest – reproducibility – reuse • Appreciation of differences between disciplines • Ubiquitous relationship with digital information Funders: 4 University College London Information Day :: 16th January 2007 a centre of expertise in data curation and preservation UK Digital Curation Centre • CCLRC • University of Edinburgh • HATII • UKOLN Funders: 5 University College London Information Day :: 16th January 2007 a centre of expertise in data curation and preservation UK Digital Curation Centre Support and promote continuing improvement in the quality of data curation and digital preservation activity Drivers – increasing awareness that digital assets are reusable – continuing access vital to ensure contemporary scholarship is reproducible and verifiable – digital assets are fragile Funders: 6 University College -
Front Page Title of Paper in Full: Centered
Preservation Is Not a Place 1 4th International Digital Curation Conference December 2008 Preservation Is Not a Place Stephen Abrams, Patricia Cruse, John Kunze California Digital Library, University of California December 2008 Abstract The Digital Preservation Program of the California Digital Library (CDL) is engaged in a process of reinvention involving significant transformations of its outlook, effort, and infrastructure. This includes a re-articulation of its mission in terms of digital curation, rather than preservation; encouraging a programmatic, rather than a project-oriented approach to curation activities; and a renewed emphasis on services, rather than systems. This last shift was motivated by a desire to deprecate the centrality of the repository as place. Having the repository as the locus for curation activity has resulted in the deployment of a somewhat cumbersome monolithic system that falls short of desired goals for responsiveness to rapidly changing user needs and operational and administrative sustainability. The Program is pursuing a path towards a new curation environment based on the principle of devolving curation function to a set of small, simple, loosely-coupled services. In considering this new infrastructure the Program is relying upon a highly deliberative process starting from first principles drawn from library and archival science. This is followed by a stagewise progressesion of identifying core preservable values, devising strategies promoting those values, defining abstract services embodying those strategies, and, finally, developing systems that instantiate those services. This paper presents a snapshot of the Program’s transformative efforts in its early phase. The 4th International Digital Curation Conference taking place in Edinburgh, Scotland over 1-3 December 2008 will address the theme Radical Sharing: Transforming Science?. -
Undergraduate Biocuration: Developing Tomorrow’S Researchers While Mining Today’S Data
The Journal of Undergraduate Neuroscience Education (JUNE), Fall 2015, 14(1):A56-A65 ARTICLE Undergraduate Biocuration: Developing Tomorrow’s Researchers While Mining Today’s Data Cassie S. Mitchell, Ashlyn Cates, Renaid B. Kim, & Sabrina K. Hollinger Biomedical Engineering, Georgia Institute of Technology & Emory University, Atlanta, GA 30332. Biocuration is a time-intensive process that involves managerial positions. We detail the undergraduate extraction, transcription, and organization of biological or application and training processes and give detailed job clinical data from disjointed data sets into a user-friendly descriptions for each position on the assembly line. We database. Curated data is subsequently used primarily for present case studies of neuropathology curation performed text mining or informatics analysis (bioinformatics, entirely by undergraduates, namely the construction of neuroinformatics, health informatics, etc.) and secondarily experimental databases of Amyotrophic Lateral Sclerosis as a researcher resource. Biocuration is traditionally (ALS) transgenic mouse models and clinical data from ALS considered a Ph.D. level task, but a massive shortage of patient records. Our results reveal undergraduate curators to consolidate the ever-mounting biomedical “big biocuration is scalable for a group of 8-50+ with relatively data” opens the possibility of utilizing biocuration as a minimal required resources. Moreover, with average means to mine today’s data while teaching students skill accuracy rates greater than 98.8%, undergraduate sets they can utilize in any career. By developing a biocurators are equivalently accurate to their professional biocuration assembly line of simplified and counterparts. Initial training to be completely proficient at compartmentalized tasks, we have enabled biocuration to the entry-level takes about five weeks with a minimal be effectively performed by a hierarchy of undergraduate student time commitment of four hours/week. -
A Brief Introduction to the Data Curation Profiles
Data Curation Profiles http://www.datacurationprofiles.org Access. Knowledge. Success A Brief Introduction to the Data Curation Profiles Jake Carlson Data Services Specialist Data Curation Profiles http://www.datacurationprofiles.org Access. Knowledge. Success Data Curation Profiles http://www.datacurationprofiles.org Access. Knowledge. Success Setting the stage Since 2004: Purdue Interdisciplinary Research Initiative revealed many data needs on campus What faculty said… • Not sure how or whether to share data • Lack of time to organize data sets • Need help describing data for discovery • Want to find new ways to manage data • Need help archiving data sets/collections Data Curation Profiles http://www.datacurationprofiles.org Access. Knowledge. Success “Investigating Data Curation Profiles across Research Domains” This lead to a research award from IMLS • Goals of the project: – A better understanding of the practices, attitudes and needs of researchers in managing and sharing their data. – Identify possible roles for librarians and the skill sets they will need to facilitate data sharing and curation. – Develop “data curation profiles” – a tool for librarians and others to gather information on researcher needs for their data and to inform curation services. – Purdue: Brandt—PI, Carlson—Proj Mgr, Witt—coPI; GSLIS UIUC: Palmer—co-PI, Cragin—Proj Mgr Data Curation Profiles http://www.datacurationprofiles.org Access. Knowledge. Success Data Curation Profiles Methodology • Initial interview— based on “Conducting a Data Interview” poster, then pre-profile based on model of data in a few published papers • Interviews were transcribed, reviewed • Coding, wanted more detail -> 2nd Interview • Developed and revised a template for Profile “In our experience, one of the most effective tactics for eliciting datasets for the collection is a simple librarian- researcher interview. -
Applying the ETL Process to Blockchain Data. Prospect and Findings
information Article Applying the ETL Process to Blockchain Data. Prospect and Findings Roberta Galici 1, Laura Ordile 1, Michele Marchesi 1 , Andrea Pinna 2,* and Roberto Tonelli 1 1 Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124 Cagliari, Italy; [email protected] (R.G.); [email protected] (L.O.); [email protected] (M.M.); [email protected] (R.T.) 2 Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Piazza D’Armi, 09100 Cagliari, Italy * Correspondence: [email protected] Received: 7 March 2020; Accepted: 7 April 2020; Published: 10 April 2020 Abstract: We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. -
SCONUL Focus Number 38 Summer/Autumn 2006
SCONUL Focus Number 38 Summer/Autumn 2006 Contents ISSN 1745-5782 (print) ISSN 1745-5790 (online) 3 The 3Ss 4 The Learning Grid at the University of Warwick: a library innovation to support learning in higher education Rachel Edwards 8 The Learning Gateway: opening the doors to a new generation of learners at St Martin’s College, Carlisle campus Margaret Weaver 11 Middlesex University: the impressive rejuvenation of Hendon campus Paul Beaty-Pownall 14 Poor design equals poor health questionnaire: the final results Jim Jackson 20 Human resourcing in academic libraries: the ‘lady librarian’, the call for flexible staff and the need to be counted A. D. B. MacLean, N. C. Joint 26 Taking steps that make you feel dizzy: personal reflections on module 1 of the Future Leaders programme John Cox, Annie Kilner, Dilys Young 30 Evolution: the Oxford trainee scheme Gill Powell, Katie Robertson 34 A week in the life Kim McGowan 36 Got the knowledge? Focusing on the student: Manchester Metropolitan University’s (MMU) library welcome campaign David Matthews, Emily Shields, Rosie Jones, Karen Peters 41 Ask the audience: e-voting at the University of Leeds Lisa Foggo, Susan Mottram, Sarah Taylor 44 Information literacy, the link between second and tertiary education: project origins and current developments Christine Irving 47 Review of how libraries are currently supporting the research process Ruth Stubbings, Joyce Bartlett, Sharon Reid 51 Researchers, information and libraries: the CONUL national research support survey John Cox 55 Creating a new Social Science Library at Oxford University based on reader consultation Louise Clarke 58 The use of personal scanners and digital cameras within OULS reading rooms Steve Rose, Gillian Evison 60 Copyright, digital resources and IPR at Brunel University Monique Ritchie 64 Secure electronic delivery: ‘get the world’s knowledge with less waiting’ Alison E. -
Understanding the Lifecycle of Dataset Preservation Isaiah Beard
Digital Curation of Research Data Understanding the lifecycle of dataset preservation Presented by: Isaiah Beard Digital Data Curator Rutgers University Libraries March 30 2012 • Rutgers University Libraries Wednesday, July 11, 12 • This presentation is about crystalizing concepts we’re all pretty sure we know, but haven’t really addressed formally. • Research data requires stepping out of our comfort zones: known formats and processes aren’t always going to help us in every case, and we’ll need to be ready to adapt. • This presentation will help get us into that mindset. Topics Covered Today Definitions & Concepts What IS digital curation, exactly? Understanding the digital curation lifecycle model Applying the lifecycle model to research data Wednesday, July 11, 12 • Getting our terminology straight • Finally answering the question: “what IS digital curation?” in terms of research data • Understanding the philosophy behind a fluid, adaptable process for preserving and presenting research data Definitions & Concepts What’s Digital Curation? * Source: Dilbert: October 30, 2011 Wednesday, July 11, 12 • Digital Curation is an emerging field, and will continue to be a learning process. For that reason, it’s not all that clear to everyone what digital curation is. You can get some confused or negative viewpoints about it. Definitions & Concepts Wednesday, July 11, 12 • There’s also lots of different opinions out there about what the job entails. Digital Curation: What is it? “The Curation, preservation, maintenance, collection and archiving of digital assets.”* *Source: “What is Digital Curation?” Digital Curation Centre, http://www.dcc.ac.uk/about/what/ Wednesday, July 11, 12 Fortunately, the Digital Curation Centre (a UK-based JISC-Joint Information Systems Committee-funded organization) has stepped in with a clear definition on what digital curation is, and what it entails. -
Biocuration - Mapping Resources and Needs [Version 2; Peer Review: 2 Approved]
F1000Research 2020, 9(ELIXIR):1094 Last updated: 22 JUL 2021 RESEARCH ARTICLE Biocuration - mapping resources and needs [version 2; peer review: 2 approved] Alexandra Holinski 1, Melissa L. Burke 1, Sarah L. Morgan 1, Peter McQuilton 2, Patricia M. Palagi 3 1European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, CB10 1SD, UK 2Oxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, Oxfordshire, OX1 3QG, UK 3SIB Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland v2 First published: 04 Sep 2020, 9(ELIXIR):1094 Open Peer Review https://doi.org/10.12688/f1000research.25413.1 Latest published: 02 Dec 2020, 9(ELIXIR):1094 https://doi.org/10.12688/f1000research.25413.2 Reviewer Status Invited Reviewers Abstract Background: Biocuration involves a variety of teams and individuals 1 2 across the globe. However, they may not self-identify as biocurators, as they may be unaware of biocuration as a career path or because version 2 biocuration is only part of their role. The lack of a clear, up-to-date (revision) report profile of biocuration creates challenges for organisations like ELIXIR, 02 Dec 2020 the ISB and GOBLET to systematically support biocurators and for biocurators themselves to develop their own careers. Therefore, the version 1 ELIXIR Training Platform launched an Implementation Study in order 04 Sep 2020 report report to i) identify communities of biocurators, ii) map the type of curation work being done, iii) assess biocuration training, and iv) draw a picture of biocuration career development. 1. Tanya Berardini , Phoenix Bioinformatics, Methods: To achieve the goals of the study, we carried out a global Fremont, USA survey on the nature of biocuration work, the tools and resources that are used, training that has been received and additional training 2. -
Automating Data Curation Processes Reagan W
Automating Data Curation Processes Reagan W. Moore University of North Carolina at Chapel Hill 216 Manning Hall Chapel Hill, NC 27599-3360 01 919 962 9548 [email protected] ABSTRACT • Data format (e.g. HDF5, NetCDF, FITS, …) Scientific data quality can be abstracted as assertions about the • Coordinate system (spatial and temporal locations) properties of a collection of data sets. In this paper, standard properties are defined for data sets, along with the policies and • Geometry (rectilinear, spherical, flux-based, …) procedures that are needed to enforce the properties. The assertions about the collection are verified through periodic • Physical variables (density, temperature, pressure) assessments, which are also implemented as policies and • Physical units (cgs, mks, …) procedures. Data quality curation can then be defined as the set of policies and procedures that verify the scientific data quality • Accuracy (number of significant digits) assertions. The assertions made by the creators of a collection are differentiated from the assertions about data quality needed by the • Provenance (generation steps, calibration steps) users of the data. The transformation of data into a useable form • Physical approximations (incompressible, adiabatic, …) requires well-defined procedures that need to be considered as part of the data curation process. The automated application of • Semantics (domain knowledge for term relationships) both digital curation and data transformation procedures is Additional properties can be derived from these categories. Thus essential for the management of large scientific data collections. the relevant time period may be defined in the temporal Categories and Subject Descriptors coordinate, and allowed transformations may be implicit in the type of variables and physical approximations that were made in D.4.7 [Operating Systems]: Organization and Design – creating the data collection. -
Transitioning from Data Storage to Data Curation: the Challenges Facing an Archaeological Institution Maria Sagrario R
Issues in Informing Science and Information Technology Volume 10, 2013 Transitioning from Data Storage to Data Curation: The Challenges Facing an Archaeological Institution Maria Sagrario R. Simbulan University of the Philippines, Diliman, Quezon City, Philippines [email protected] Abstract Each archaeological project generates substantial amounts of data from season to season, all of which need to be collected, analyzed, organized, and stored. After an archaeological project or season ends and all the accessioning-related and analytical activities are completed, all those arti- facts are stored away in shelves, boxes and crates, and the associated archaeological data will be stored as digital files and in file folders. There are two critical questions in a time of downsized organizations and shrinking budgets: How can the archaeological data and related scientific in- formation pertaining to each of these archaeological projects be preserved and made available to other researchers? How do we make sure that future generations are able to access these infor- mation resources? I ask these questions as a relative newcomer to archaeology. This paper is a quest to understand how archaeological institutions can transition from an individually curated, per project/per season information gathering and data storage approach to a centralized information resource manage- ment approach known as archaeological data curation. Specifically, this paper will look at the challenges that an archaeological institution would face as it attempts to shift from narrowly- focused, project-related data storage to a broader and long-term focus on the management of the archaeological information resources of the entire institution. Keywords: data curation, data repositories, archaeological data curation, digital curation Introduction Archaeological activities, whether in the field or in the laboratory, generate significant amounts of data. -
Guidance Documents for Lifecycle Management of Etds
Guidance Documents for Lifecycle Management of ETDs Authors: Daniel Alemneh, Bill Donovan, Martin Halbert, Yan Han, Geneva Henry, Patricia Hswe, Gail McMillan, Xiaocan (Lucy) Wang Editors: Matt Schultz, Nick Krabbenhoeft, and Katherine Skinner 18 March 2014 Version 1.0 Guidance Documents for Lifecycle Management of ETDs Publication Notes Title: Guidance Documents for Lifecycle Management of ETDs Editors: Matt Schultz, Nick Krabbenhoeft, and Katherine Skinner Authors: Daniel Alemneh, Bill Donovan, Martin Halbert, Yan Han, Geneva Henry, Patricia Hswe, Gail McMillan, Xiaocan (Lucy) Wang Publisher: Educopia Institute, 1230 Peachtree Street, Suite 1900, Atlanta, GA 30309. Copyright: 2014 This publication is covered by the following Creative Commons License: Attribution-NonCommercial-NoDerivs 4.0 You are free to copy, distribute, and display this work under the following conditions: Attribution – You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Specifically, you must state that the work was originally published as the Guidance Documents for Lifecycle Management of ETDs, and you must attribute the copyright holder as the Educopia Institute. Noncommercial – You may not use this work for commercial purposes. No Derivative Works – You may not alter, transform, or build upon this work. Any of these conditions can be waived if you get permission from the copyright holder. Your fair use and other rights are in no way affected by the above. The above is a human-readable summary of the full license, which is available at the following URL: http://creativecommons.org/licenses/by-nc-nd/4.0/ Guidance Documents for Lifecycle Management of ETDs Table of Contents Introduction...................................................................................................................................................