DataOne.Org

PDFR114 | The data life cycle provides a high level overview of the stages involved in successful management and
preservation of data for use and reuse. Multiple versions of a data life cycle exist with differences attributable
to variations in practices across domains or communities. The DataONE data life cycle was developed by the
DataONE Leadership Team in collaboration with the broader DataONE community, and built upon the life
cycle model put forward by the National Science Foundation in the original DataNet solicitation. It serves as an
underlying framework for the development of tools, services and education materials by DataONE. | The DataONE Best Practices database provides individuals with recommendations on how to effectively work
with their data through all stages of the data lifecycle. Users can access best practices within the database by
either clicking on a stage of the lifecycle or selecting keywords under search |

Contents
1. Data Life Cycle
-- https://old.dataone.org/best-practices
-- https://old.dataone.org/investigator-toolkit
-- Data Management Education Modules https://old.dataone.org/education-modules
2. Best Practices
-- https://old.dataone.org/sites/all/documents/DataONE_BP_Primer_020212.pdf
-- https://old.dataone.org/sites/all/documents/DataONE-PPSR-DataManagementGuide.pdf
-- https://old.dataone.org/sites/all/documents/DataONE-PPSR-DataManagementGuide.pdf
3. All Best Practices
-- Describe Formats, measurement techniques, derived data products, contents of data files, organization of dataset, research project, sensor network, spatial extent and resolution of the dataset, units of measurement for each observation, quality assurance and quality control plan, document and store data using stable file formats, document steps used in data processing, document taxonomic information
4. All Best Practices
-- Advertise your data using datacasting tools https://old.dataone.org/best-practices/advertise-your-data-using-datacasting-too...
-- Assign descriptive file names https://old.dataone.org/best-practices/assign-descriptive-file-names
-- Backup your data https://old.dataone.org/best-practices/backup-your-data
--Use standard Terminology to Enable Discovery https://old.dataone.org/best-practices/choose-and-use-standard-terminology-enabl...
-- Communicate data quality https://old.dataone.org/best-practices/communicate-data-quality
-- Confirm a match between data and their description in Metadata https://old.dataone.org/best-practices/confirm-match-between-data-and-their-desc...
-- Consider the Compatibility of the Data You Are Integrating https://old.dataone.org/best-practices/consider-compatibility-data-you-are-integ...
-- Create a Data Dictionary https://old.dataone.org/best-practices/create-data-dictionary
-- Create and Document a Data Backup Policy https://old.dataone.org/best-practices/create-and-document-data-backup-policy
-- Create, Manage, and Document your Data Storage System https://old.dataone.org/best-practices/create-manage-and-document-your-data-stor...
-- Decide What Data to Preserve https://old.dataone.org/best-practices/decide-what-data-preserve
-- Define Expected Data Outcomes and Types https://old.dataone.org/best-practices/define-expected-data-outcomes-and-types
-- Define Roles and Assign Responsibilities for Data Management https://old.dataone.org/best-practices/define-roles-and-assign-responsibilities-...
-- Define the Data Model https://old.dataone.org/best-practices/define-data-model
-- Define the Parameters https://old.dataone.org/best-practices/define-parameters

SA - https://www.librarything.com/work/31507626/book/255801976 | https://www.librarything.com/work/31533223/book/256164392
RT - Archives
BT - Curation
NT - Actions in Curation
UF - Curation of Digital Objects
SN - An article describing best practices within data management services (combined pieces from DataONE). (This entry does not reference a hierarchical list)… (altro)

PDFR109 | Abby is a data librarian at the University of California, Berkeley. She studied
earth sciences as an undergraduate at Purdue University, then entered a
graduate program at Berkeley. She earned a master's degree but ended
up moving to a staff research associate position in the Berkeley
Seismological Laboratory when the funding ran out on the grant that was
supporting her. In that position, she found herself taking on more and
more responsibility for data management for various projects. After
interacting with librarians developing the campus digital repository, and
with their encouragement, she decided to pursue a masters in library and
information science at San José State University to further develop her
skills and knowledge in data management. Upon graduating, she was
hired as the University library’s first science data librarian |

Contents
Background
Reasons for Using DataONE to Share and to Reuse Data
Comparison of Current and DataONE-Engalbed Practices

SA - https://dataone.org/
RT - Services
BT - Profile
NT - Data Management Utilization
UF - To demonstrate the use of DM via DataONE
SN - This promotional article explains how a fellow scientist has utilized DM services through DataONE. (This entry does not reference a hierarchical list)… (altro)

PDFR108 | Andreas is a biogeochemical modeler at Michigan State University with a
PhD from the Max Planck Research School for Global Biogeochemical
Cycles, received 16 years ago |

Contents
Background
Reasons for Using DataONE to Share and to Reuse Data
Comparison of Current and DataONE-Engalbed Practices

SA - https://dataone.org/
RT - Services
BT - Profile
NT - Data Management Utilization
UF - To demonstrate the use of DM via DataONE
SN - This promotional article explains how a fellow scientist has utilized DM services through DataONE. (This entry does not reference a hierarchical list)… (altro)

PDFR107 | Elizabeth is a mid-to-late-career woman who is a professor of biology
and the department chair for a regional comprehensive university in
Washington State. This university historically focused on teaching. While
faculty consider research to be an important part of their work, their
research activities are generally restricted to smaller, minimally-funded
projects, and they usually have time for research activities only during
the summer. Elizabeth was recruited to this university from a researchintensive
state university in order to expand the research activities in the
biology department, both by changing existing reward structures and by
recruiting new, research-focused faculty. However, her efforts are
hampered by limited research support and facilities. She is unlikely to be
able to recruit faculty who excel according to traditional metrics for the
field, such as numbers of publications and impact factors, since those faculty will likely be able to find
positions at other institutions which will provide greater support for their research activities. Instead,
Elizabeth would like to recruit faculty who excel at new metrics that have demonstrable impact on the
field of biology. She consulted with the dean of the college, her current faculty and colleagues
elsewhere, and there was broad agreement that the department can and should evaluate the scholarly
impact of raw datasets which are contributed to the field. She would also like to perform such
evaluations on possible new hires |

Contents
Background
Reasons for Using DataONE to Share and to Reuse Data
Comparison of Current and DataONE-Engalbed Practices

SA - https://dataone.org/
RT - Services
BT - Profile
NT - Data Management Utilization
UF - To demonstrate the use of DM via DataONE
SN - This promotional article explains how a fellow scientist has utilized DM services through DataONE. (This entry does not reference a hierarchical list)… (altro)