DataOne.OrgRecensioni

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)

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)

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)

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)

PDFR105 | Jean is an agricultural scientist working at the Cornell University
agricultural field station in Geneva NY. He received a PhD in horticulture
from Virginia Polytechnic Institute in 1987 | Jean is a tenured associate professor in the Department of Horticulture.
Jean’s current project uses the tomato as a model system to study
sympodial growth (a growth pattern in which the stem is a succession of
growths rather than one). He is driven by the agricultural research
station’s program of research and the need to publish and to obtain grant
funding to support his research |

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)

PDFR106 | Gretta received her PhD from University of Wisconsin Madison in Zoology six years ago at the age of 29. She did her dissertation fieldwork
on the Mosquito Coast of Honduras studying physiological and
population ecology of bats. Her research linked individual bioenergetics
to landscape level meta-population genetics.
At Wisconsin, Gretta was a Teaching Assistant for general biology
lectures and labs, and taught several different sections of a variety of
elective courses but she did not specifically study or receive more than
minimal training in teaching or education. However, during a postdoc at
the La Selva Biological Station in Costa Rica she interacted with a group
of undergraduates doing a field study. This positive experience led her to
consider a career with a greater focus on teaching than she had previously been considering.

Contents
Background
Reasons for Using DataONE to Share and To Reuse Data
Researcher Support

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)

PDFR104 | Laura is a tenured associate scientist at Woods Hole Oceanographic
Institution. She received a PhD in marine biology from the University of
Rhode Island in 1990. | Laura’s research investigates the effect of climate change on marine
food webs, for which she needs to correlate environmental and species
data. She is driven by intellectual curiosity and the need to publish and
obtain grant funding to support her research |

Contents
Background
Reasons for Using DataONE To Share and To Reuse Data
Comparison of Current and DataONE-Enabled 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)

PDFR103 | A native of Knoxville, Mr. McMillin graduated with a dual degree in
Chemistry and Education from Berea College, with coursework
supporting teaching certification in Kentucky. Family ties led him to return
to the middle-class urban/suburban neighborhood in the East Knoxville
School District near where he grew up. Upon his return to Knoxville, Mr.
McMillin sought employment as a High School Chemistry teacher, but
the district only had an opening in Middle School Earth Science.
He took the job somewhat begrudgingly but quickly grew to like it, and
has been teaching at his school for over a decade. Mr. McMillin now
chairs the Science Faculty, and new teachers, as well as his older
colleagues, at least some of them, have come to depend upon him for
new ideas, programs and innovations |

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

PDFR102 | Rick is a middle-aged male with an advanced degree in civil engineering. And in fact, Rick is a civil engineer by trade, but he has long been an enthusiastic outdoorsman, nature photographer, and gardener, and is keenly interested in local and native flora. He loves photographing what
he sees on his nature walks, which mostly take place in local reserves but occasionally on family vacations. He has supported the local chapter
of the Nature Conservancy for years both financially and as a participant in guided walks and as a volunteer for management activities at their
local preserves. In the last few years, he has participated in an effort coordinated by Nature Conservancy staff to regularly survey the
presence, abundance, and life-history characteristics of several different plant species that are resident in local reserves. He is not a computer or
data expert but is perfectly comfortable using computers and following standardized rubrics and protocols |

Contents
1. Background
2. Reasons for Using DataONE to Share And To Reuse Data
3. Comparison of Current and DataONE-Enabled Practices

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

PDFR101 | Sun is a biologist specializing in desert tortoises. She did her master's and PhD at California State University San Marcos. She has spent her career studying tortoises in their natural habitat |

Contents
Background
-- A Day In The Life
Reasons for Using DataONE to Share and to Reuse Data
-- Needs and expectations of DataONE tools:
-- Intellectual and physical skills that can be applied:
-- Technical support available:
-- Personal biases about data sharing and reuse (and data management more generally
Sun, Desert Tortoise Researcher
Comparison of Current and DataONE-Enabled Practices
-- Project Planning
-- Current Data Collection
-- DataONE enabled Data Collection
-- Current Data Assurance
-- DataONE Enabled Assurance
-- Current Data Description
-- DataONE Enabled Description
-- Current Data Preservation
-- DataONE Enabled Preservation
-- Current Data Discovery
-- DataONE Enabled Discovery
-- Current Data Intergration
-- DataONE Eneabled Integration
-- Current Data Analyses
-- DataONE Enabled Analysis: Data Visualization
Source
-- https://ask.dataone.org/questions/
-- https://old.dataone.org/sign-up
-- https://old.dataone.org/contact
-- https://old.dataone.org/personas/sitemap

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)
6. Tags

PDFR100 | This is a day-in-the-life article about DataOne users | Tina is a 42-year-old science educator who runs a citizen science project
in Portland, OR. She works for Multnomah Nature Center (MNC), a 36- year old nonprofit organization focused on natural history education and
conservation research. Private donations, development activities such as fundraising events, and an allocation from the Oregon Lottery fund MNC. Tina has a dual MS in Science Communication and Natural Resources from Oregon State University and a BS in biology from Michigan State University |

Contents
1. Name, Age and Education
2. Life or Career Goals, Fears, Hopes, and Attitudes
3. A Day in the Life
4. Reasons for Using DataONE to Share and to Reuse Data
5. Comparison of Current and DataONE-Enabled Practices
6. Source
-- https://ask.dataone.org/questions/
-- https://old.dataone.org/sign-up
-- https://old.dataone.org/contact
-- https://old.dataone.org/personas/sitemap

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 novice scientist has utilized DM services through DataONE. (This entry does not reference a hierarchical list)
7. Tags

PDFR99 | This is a day in the life article about DataOne users | William (No Last Name) University Herbarium at University of Michigan |

Contents
1. Background
-- Name, age, and education
-- Life or career goals, fears hopes, and attitudes
-- A Day In The Life
2. Reasons for Using DataONE to Share and to Reuse Data
-- Needs and Expectations of DataONE Tools
-- Intellectual and Physical Skills that Can Be Applied
-- Technical Support Available
-- Personal Biases about Data Sharing and Reuse (and Data Management More Generally)
3. Current Practice May 2012
4. Comparison of Current and DataONE - Enabled Practices
-- Current data collection
-- DataONE Enabled Data Collection
-- Current Data Assurance
-- DataONE Enabled Assurance
-- Current Data Description
-- DataONE Enabled Description
-- Current Data Preservation
-- DataONE Enabled Preservation
-- Current Data Discovery
-- DataONE Enabled Discovery
-- Current Data Integration
-- DataONE Enabled Integration
5. Source
-- https://ask.dataone.org/questions/
-- https://old.dataone.org/sign-up
-- https://old.dataone.org/contact
-- https://old.dataone.org/personas/sitemap

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

PDFR36 | The data life cycle provides a high-level overview of the stages involved in the successful management and preservation of data for use and reuse. Multiple versions of a data life cycle exist with differences attributable to practice variation 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 data life cycle has eight components:

Plan: description of the data that will be compiled, and how the data will be managed and made
accessible throughout its lifetime

Collect: observations are made either by hand or with sensors or other instruments and the data
are placed a into digital form

Assure: the quality of the data are assured through checks and inspections
Describe: data are accurately and thoroughly described using the appropriate metadata
standards

Preserve: data are submitted to an appropriate long-term archive (i.e. data center)

Discover: potentially useful data are located and obtained, along with the relevant information
about the data (metadata)

Integrate: data from disparate sources are combined to form one homogeneous set of data that
can be readily analyzed

Analyze: data are analyzed |

SA - Stages of Workflow
RT - Management of Database
BT - Library Services
NT - Digital Stewardship
UF - Workflow of addressing scholarly data.
SN - One of many representations of a workflow model. (This entry does not reference a hierarchical list)