Wilderness Science Application and Delivery: Google Jamboard data from 2022 data gathering sessions

Metadata:

Identification_Information
Data_Quality_Information
Entity_and_Attribute_Information
Distribution_Information
Metadata_Reference_Information

Identification_Information:

Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:: Each virtual sticky note entered into Google Jamboards was entered verbatim into a Microsoft Excel spreadsheet organized by session and question.

Logical_Consistency_Report:

not applicable

Completeness_Report:

Participants were not required to answer every question, and in some cases, participants provided multiple responses per question. A limitation of Google Jamboards is a character limit for each sticky note. As a result, some responses are incomplete. When this is the case, the response ends with “…text cut off.”

Lineage:

Methodology:

Methodology_Type: Field
Methodology_Description:: We coordinated with agency leadership across all four federal wilderness management agencies including the Bureau of Land Management (BLM), National Park Service (NPS), U.S. Forest Service (USFS), and U.S. Fish and Wildlife Service (USFWS) across the Wilderness Preservation System to organize the data gathering sessions. Wilderness leadership invited staff to participate in the organized sessions. Additionally, we held a data gathering session at the 2022 virtual National Wilderness Leadership Skills Institute with participants representing the non-profit sector and the USFS. Combined, we held one 60-minute session with the BLM, USFS, and USFSWS, and three 30-minute sessions with the NPS in order to take advantage of existing meetings at different levels of the wilderness management. Given that not all sessions were the same length, we relied on a shortened set of questions to ensure we addressed all research objectives in each session. As a result, not all questions were asked at each session. (See \Data\session_info.csv, to determine which questions were asked at each session along with the number of participants and other session information.) In sum, these data are from a convenience sample of participants who were interested and available to engage in the research.

Potential Questions Asked at Each Session:

Warmup Q1: What is your role, or how would you describe yourself in the wilderness community?

Warmup Q2: How long have you been working in, or engaged in the wilderness community?

Q1: What are the kinds of decisions or tasks you face on a day-to-day basis?

Q2: What types of information do you call on when making these various kinds of decisions, or addressing these various tasks?

Q3: When do you use science, more specifically, in your day-to-day?

Q4: How do you use science in these decision-making contexts?

Q5: How much time do you spend learning about different topics and how useful is that knowledge?

Q6a: What successes have you had moving best available science into action?

Q6b: What challenges have you had moving best available science into action?

Q7: What makes you trust or distrust scientists?

Q8: What makes science credible?

Q9: If you have been involved or could imagine being involved in research that was developed by scientists and managers working together (“co-produced”), what made that successful or unsuccessful?

Q10: Think about someone you go to for information on or advice about wilderness-related science. Why do you go to that person?

For additional details about these data and a summary of results, see Redmore et al. (in review).
Methodology_Citation:

Process_Step:

Process_Description:: Data are provided as captured during the data gathering session. Data were converted from Excel to individual comma-separated values (CSV) files.
Process_Date: 2024

Entity_and_Attribute_Information:

Overview_Description:

Entity_and_Attribute_Overview:: Below you will find a list and description of the files included in this data publication.

VARIABLE DESCRIPTION FILE (1)

1. \Data\_variable_descriptions.csv: Comma-separated values (CSV) file containing a list and description of variables found in all data files. (A description of these variables is also provided in the metadata below.)

Columns include:

Filename = name of data file

Variable = name of variable

Description = description of variable

INFORMATIONAL DATA FILES (2)
All data files are provided as CSV files.

1. \Data\acronyms.csv: Common abbreviations used in participant responses.

Columns include:

Abbreviation = abbreviation

Meaning = description/meaning of abbreviation

2. \Data\session_info.csv: List of sessions, session dates, number of participants, etc., and whether or not the survey question was posed at that session.

Columns include:

Session date = date of session (dd-Month-yy)

Session name = name of session

Session length = time allocated to session (minutes)

Number participants = number of participants in session

Qs for Obj1 = list of questions asked related to research objective 1: better understand wilderness managers’ decision-making context

Qs for Obj2 = list of questions asked related to research objective 2: role science plays in current decision-making

Qs for Obj3 = list of questions asked related to research objective 3: identify opportunities to strengthen the use of science in wilderness management

[Q#: actual question] = 'X' if the specified question was asked in that session (blank if not)

SESSION QUESTION DATA FILES (16)
All data files are provided as CSV files. Each of the survey question data files listed below contain the results in the same format.

Columns include:

Session name = name of session

Response = participant response to question (free text response)

1. \Data\Q1_warmup_responses.csv: Results for the Q1 warmup question: What is your role, or how would you describe yourself in the wilderness community?

2. \Data\Q2_warmup_responses.csv: Results for the Q1 warmup question: How long have you been working in, or engaged in the wilderness community?

3. \Data\Q1_responses.csv: Results for Q1: What are the kinds of decisions or tasks you face on a day-to-day basis?

4. \Data\Q2_responses.csv: Results for Q2: What types of information do you call on when making these various kinds of decisions, or addressing these various tasks?

5. \Data\Q3_responses.csv: Results for Q3: When do you use science, more specifically, in your day-to-day?

6. \Data\Q4_responses.csv: Results for Q4: How do you use science in these decision-making contexts?

7. \Data\Q5a_responses.csv: Results for Q5a: How much time do you spend learning about different topics and how useful is that knowledge? List topics that you spend a lot of time learning, but don't find useful.

8. \Data\Q5b: Results for Q5b: How much time do you spend learning about different topics and how useful is that knowledge? List topics that you spend a lot of time learning and find very useful.

9. \Data\Q5c: Results for Q5c: How much time do you spend learning about different topics and how useful is that knowledge? List topics that you don't spend much time learning and don't find useful.

10. \Data\Q5d: Results for Q5d: List topics that you don't spend much time learning, but find very useful [in relation to the amount of time you spend learning about different topics].

11. \Data\Q6a_responses.csv: Results for Q6a: What successes have you had moving best available science into action (using real world examples)?

12. \Data\Q6b_responses.csv: Results for Q6b: What challenges have you had moving best available science into action (using real world examples)?

13. \Data\Q7_responses.csv: Results for Q7: What makes you trust or distrust scientists? [Label as trust or distrust]

14. \Data\Q8_responses.csv: Results for Q8: What makes science credible? [Label credible or not credible]

15. \Data\Q9_responses.csv: Results for Q9: If you have been involved or could imagine being involved in research that was developed by scientists and managers working together ("co-produced"), what made that successful or unsuccessful? [Label successful or unsuccessful]

16. \Data\Q10_responses.csv: Results for Q10: Think about someone you go to for information or advice about wilderness-related science. Why do you go to that person? (For BLM Sci Common August 22 group, this is included: Is it their expertise, their position, your relationship to them, ease of access to them, or something else?)

SUPPLEMENTAL FILES (2)

1. \Supplements\WLD_science_A&D_discussion_guide.pdf: Portable Document Format (PDF) file containing the data gathering session question guide.

2. \Supplements\WLD_science_A&D_study_plan.pdf: PDF file containing the scope of work and study plan associated with these data.
Entity_and_Attribute_Detail_Citation:: Redmore, Lauren E.; Rushing, Jaclyn F.; Armatas, Christopher A.; Wright, Vita. [In review]. Examining and strengthening the role of science in wilderness decision-making. Parks Stewardship Forum.

Distribution_Information:

Metadata_Reference_Information:

Metadata_Date: 20240718

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: USDA Forest Service, Aldo Leopold Wilderness Research Institute
Contact_Person: Jaclyn Fox Rushing

Contact_Position: Social Scientist

Contact_Address:

Address_Type: mailing and physical
Address: 790 E Beckwith Ave.
City: Missoula
State_or_Province: MT
Postal_Code: 59801
Country: USA

Contact_Voice_Telephone: 406-542-3245

Contact_Electronic_Mail_Address: jaclyn.rushing@usda.gov

Contact Instructions: This contact information was current as of original publication date. For current information see Contact Us page on: https://doi.org/10.2737/RDS.

Metadata_Standard_Name: FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001.1-1999