Find research datasets worth reusing

opencc-by-4.0Dec 2024View details →

Literature review of the enablers and barriers to stakeholder and citizen engagement in climate change adaptation process (as part of Adaptation AGORA project)

This dataset is the result of collaborative work for Deliverable 4.1 (WP4; T4.1) of the Adaptation AGORA project. This database was used to conduct a literature review of the enablers and barriers to stakeholder and citizen engagement in climate change adaptation process. It contains 123 papers retrived from Web of Science Databse in June 2023. We used a keyword search to identify and select articles that fell within the scope of our research, with each article containing at least one keyword related to climate change adaptation solutions, climate change, co-production, citizen and stakeholder involvement and factors (enablers and barriers).  We divided the coding framework into four main sections: <ul> <li> Section 1 collected basic information about the paper (i.e., date, journal, authors, type of study and methods for data collection). </li> <li> Section 2 sought to better understand the adaptation initiatives treated in the paper. Here, we analysed 5 variables (the adaptation solutions type, sectors, benefits, scale, and location).  </li> <li> Section 3 collected characteristics of the climate change adaptation co-production process, including the definition of co-production, the type of the co-production process, its outputs, and the methods used to engage stakeholders. </li> <li> Section 4 described the factors that enable or hinder the co-production process and their influence on different aspects of the process. After naming and defining each driver, we recorded the main type of factor, its impact, origin, and spatial and temporal scale of influence; the stakeholders who were responsible for and influenced by the factor, and the impacts on the various steps and outcomes of the co-production process. </li> </ul>

Toy Qualitative Data Project (Interview Transcripts)

Please be advised that this project is intended solely for instructional purposes and should not be used for actual research. This dataset is intended to complement the instructional material and provide a hands-on learning experience for the workshop: <a href="https://rcurty.github.io/qualdata-training">Handling and Sharing Qualitative Data Responsibly and Effectively</a>. This hypothetical research project is designed to demonstrate key concepts related to human subject qualitative data management and thematic analysis coding. It includes interview transcripts generated with ChatGPT 4.0 Mini for a fictional graduate student in Communication named Sarah, whose main research question is: How do content creators/digital influencers view their role in shaping their followers' consumer behavior, and what ethical dilemmas do they face when promoting products? <div> Given the novelty of this research topic and the limited academic literature available, Sarah hopes that the insights gained from this small-scale qualitative exploratory study will help identify key variables for a larger survey study with a representative sample of content creators/digital influencers across the U.S. Sarah has previous experience with quantitative methods but is very new to qualitative research and could use our help for better handling the data. Having already conducted six short structured interviews with subjects from top revenue niches (i.e., Home Decor and DYI, Travel & Adventure, Fashion & Style, Health & Wellness, Finance & Investment, Beauty & Skincare) and planning to conduct a dozen more, Sarah is eager to begin engaging with the data she has collected so far and deciding how to best organize and interpret it. We’ll be walking her through this process, providing the necessary guidance and support for effective and responsible data management. Interviews were conducted over Zoom and audio recorded with participants' consent. The interview included four main questions, which were consistent across all interviews: Q1. Please tell me a little about your work as a content creator/digital influencer how it started, and how you have established yourself in your current niche. Q2. In what ways do you believe content creators/digital influencers shape consumer behavior? Could you share any examples? Q3. What strategies would you say content creators/digital influencers typically use to increase sales of sponsored products and services? Which ones have you used? What worked and what did not work for you? Why? Q4. In your view, what are the essential ethical responsibilities that content creators and digital influencers should uphold? Can you share any personal experiences that illustrate these responsibilities in action? Each interview generated approximately 15 minutes of audio recording, which Sarah manually transcribed. Sarah decided to keep the transcription true to the recordings and seek assistance to mitigate any risk of identification.  </div>

Pediatric Heat Risk Index Project

The pediatric risk index project attempts to create a risk index specifically for pediatric populations using socioeconomic and health data across the United States. This new index is then overlayed with heat warming anomaly trends in this decade and future climate projections to better understand which vulnerable populations have the greatest exposure to extreme heat events and will only continue to be exposed to these events in the future. This repository contains the climate normal data, Google Earth Engine and R code for data processing, and the final data products. MODIS Land Surface Temperature Dataset and the NOAA NCEI Climate Grid Daily Temperature dataset can be accessed via Google Earth Engine with the code in this respository. This repository also has a GitHub link with the Google Earth Engine code availabile.

Data, code, and outputs for the paper "Can Place-Based Crime Prevention Impacts be Sustained Over Long Durations? 11-Year Follow-Up of a Quasi-Experimental Evaluation of a CCTV Project"

********** Can Place-Based Crime Prevention Impacts be Sustained Over Long Durations? 11-Year Follow-Up of a Quasi-Experimental Evaluation of a CCTV Project ********** The phase-specific datasets for the main and displacement analyses are contained in the “1.datasets” folder.  The scripts used to conduct the microsynthetic control matching analyses are contained in the “2.Rscripts” folder. The subfolders “3.outputs_main” and "4.outputs_displacement" contains all graphs and tables generated by the microsynth package. Please note that running the analysis will take several hours on most computer systems. The Microsoft Excel file displays the results of all models conducted for this analysis. Yellow tabs contain the WDD results presented in the text of the article.  Red tabs are the per-capita (quarter-year) microsynth results used to calculate WDD values. All other tabs contain the raw microsynth outputs used to calculate the per-capita results.

opencc-by-4.0Apr 2024View details →

New Zealand Vertical land movement and sea rise projections

UPDATE from version v3: This update corrects a missing scenario (SSP3-7.0) with no VLM from the SLR projections tables. It also includes updated 0 entries for 2005 for both the VLM and noVLM projections.   This dataset provides the estimated vertical land movement around the New Zealand coast and associated sea rise projections described by Naish et al., 2024:  Naish, T. et al. (2024) The significance of vertical land movements at convergent plate boundaries in probabilistic sea-level projections for AR6 scenarios: the New Zealand case. Earth's Future README: NZ SeaRise Data Description   This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0). Users can download two data sets for selected sites: (1) Site details and (2) Sea level projections. A brief description of these data is included below. 1. Site Details Provides location data and estimates of vertical land movement for each site. For the VLM file: id = site location Lon = longitude Lat = latitude Vertical Rate = average annual vertical velocity in mm/yr Vertical Rate BOP corrected (mm/yr) = average annual vertical velocity in mm/yr with a correction for a movement (see Hamling et al., 2016, Hamling et al., 2022) for details. NOTE: These are the vertical rates used for the sea level projections. 1-sigma uncertainty = Error estimate for vertical velocity in mm/yr Number of obs = Number of individual scatterers and/or GNSS used to estimate the vertical rate. QF = Quality factor for vertical velocity estimates of the land surface derived from InSAR data averaged for 2 km-spaced sites (1=good, 5=poor). This factor considers the number of observations available for each coastal location, the radial distance used to bin the observations and the distance to the nearest GNSS station. After selecting the optimal search radius, a distance weighted mean is calculated for of all the points with additional weight given to any available GNSS observations. Average distance between coastal point and observations =Average distance (in km) of all the points used to estimate the vertical rate from the coastal site indicated by the ID an lon, lat values. 2. Sea level projections tables Provides sea level projections data for each site. Table ‘NZSeaRise_proj_novlm.csv’ provides projections without estimates of local VLM and table ‘NZSeaRise_proj_vlm.csv’ provides projections that include estimates of local VLM. Example download table:   Confidence = identifies low or medium confidence projection siteId = site location year = Projection year (Common Era) 0.17 = 17th percentile value 0.50 = 50th percentile (mean) value 0.83 = 83rd percentile value SSP ǀ scenario = Shared Socio-economic Pathway and relevant change in forcing at 2100 in W m2

Dataset for an article "Developing best practices for conducting STEM engineering projects in higher education"

These articles are part of the dataset used in the article.  These articles are anonymized manuscript drafts that were not published in the journal with other articles. Read more from LUMAT-B: <a href="https://urn.fi/urn:nbn:fi:hulib:editori:lumatb.v9i17"> https://urn.fi/urn:nbn:fi:hulib:editori:lumatb.v9i17 </a>

opencc-by-4.0Sep 2024View details →

AWI-Gen 2 Microbiome Project MAGs September 2024

Metagenome-assembled genomes, phage genomes, and related statistics for the AWI-Gen 2 Microbiome Project.

Data for "Neglecting the coupled effect of coastal flooding and erosion can lead to spurious projections and maladaptation"

Data for the reproduction of the figures in the manuscript "Neglecting the coupled effect of coastal flooding and erosion can lead to spurious projections and maladaptation".

Selected articles from the scoping review of biomarker discovery studies for the EU project on "Personalised Medicine Trials" (PERMIT)

This dataset provides the data extracted for the scoping review of the literature on biomarker discovery studies for patient stratification using machine learning analysis of omics data, as part of the EU project on “Personalised Medicine Trials” (PERMIT). It covers the references for all articles selected as part of the scoping review, as well as information on the study type and methodology, the outcome measures, the validation type, and representative sentences extracted from each article on the main results and key findings of the corresponding biomarker study.

SNSF Spark project "Sonic Imagination" – Excerpts of recorded evaluation interviews

We aimed to investigate the hypothesis that virtual sound sources in audio augmented environments are particularly suitable for triggering and directing imaginations within human inner perception. Our hypothesis was that the binaural listening to imaginary entities at the place of recording (so to speak 'in-situ') enhances the imagination in a special way, since sound as a non-visual medium favours the creation of images in human inner perception. We narrowed down our research question especially in regards to our practical experimentations to possible applications in areas that rely on the guided creation of individual or intersubjective imaginations, such as urban planning and scenario development, certain forms of trauma therapy, as well as audiovisual art and fiction. Further information:  <a href="https://www.ludwigzeller.net/projects/sonic-imagination/">https://www.ludwigzeller.net/projects/sonic-imagination/</a> <a href="https://p3.snf.ch/project-195868">https://p3.snf.ch/project-195868</a>

Interviews to ECOBULK project partners

Interviews carried out to project partners and published openly to disseminate circular economy concepts and ECOBULK purposes.

opencc-by-4.0Aug 2018View details →

SIRIUS Project - comparative dataset on socio-cultural, political and legal indicators

This is an ad hoc dataset on socio-economic, cultural, political and legal indicators on migration covering all SIRIUS countries (Czech Republic, Denmark, Finland, Greece, Italy, Switzerland, United Kingdom), created by retrieving and systematizing a number of indicators available in the most relevant databases. The dataset has been created as part of the work package 2 of the SIRIUS Project "Skills and Integration of Migrants, Refugees and Asylum Applicants in European Labour markets". The work package, titled “Legal barriers and enablers”, examined the legal and institutional framework of migration and asylum, integrated with critical insights on the cultural and socio-economic environment of the SIRIUS countries.  Acknowledgments and disclaimers This research was conducted under the Horizon 2020 project ‘SIRIUS’ (770515). The sole responsibility of this publication lies with the author. The European Union is not responsible for any use that may be made of the information contained therein.

AZtec projects reach the data size limit

Ten Ti-6Al-4V samples were mounted on a multi-sample stage for EBSD on a Thermo Fisher Apreo SEM equipped with an Oxford Instruments' Symmetry 2 detector at the University of Manchester. In project multi-sample_1, AZtec reported a saving error when scanning the fifth sample and stopped with 5646 frames saved (.oip~4GB). It is able to montage and export the maps, but any edit on the .oip file cannot be saved. In project multi-sample_2, we restarted the scan on the rest of the samples and completed with 5601 frames. The .oip is 3.97GB, which almost reaches the size limit. No error was reported during the scanning, and the .oip file is still editable.

TGA and LOI measurements within the thermal degradation study of a SRF prepared for an aluminium scrap pre-heating system (REVaMP project)

Underlying data (related to Figure 2) for the publication Acha, E.; Lopez-Urionabarrenechea, A.;Delgado, C.; et al. Combustion of a Solid Recovered Fuel (SRF) Produced from the Polymeric Fraction of Automotive Shredder Residue (ASR). Polymers 2021, 13, 3807. <a href="https://doi.org/10.3390/polym13213807">https://doi.org/10.3390/polym13213807</a> Experimental data generated by the REVaMP project (GA 869882, Horizon 2020, European Union) along the research of the combustion of a SRF, prepared from ASR, to be used as alternative fuel in a scrap pre-heater at an aluminium refinery plant. Research pertaining to Task 1.1 (WP1), Deliverable D1.  Subject: Thermal degradation study performed in air to measure the mass loss of SRF samples with time and temperature during a continuous heating process (two TGA measurements and determination of variation of LOI with T). The results indicate the different stages in the thermal decomposition of the prepared SRF and the temperature range of its combustion. Useful information for designing the operation conditions of the SRF combustion chamber of the scrap pre-heater.

opencc-by-4.0Aug 2021View details →

REMix model input data for the THG95/GHG95 scenario analysed within the MuSeKo project

<ul> <li>This file contains data used in the REMix energy system model in a scenario assessment for the years 2020, 2030, 2040, and 2050</li> <li>The dataset comprises techno-economic data, energy demand data, renewable energy potentials, fuel as well as emission prices, and energy infrastructure capacities</li> <li>This data is considered in the THG95/GHG95 (Treibhausgas / green house gas) scenario developed within the project MuSeKo</li> <li>This scenario comprises Germany, its neighbours as well as Italy, Norway and Sweden</li> <li>Further descriptions and data is available in the project report of MuSeKo (in German), which can be downloaded from <a href="https://elib.dlr.de/135971/">https://elib.dlr.de/135971/</a></li> </ul> Version 2 provides a correction of biogas potentials in Germany

opencc-by-4.0Dec 2020View details →

SIRIUS Project - Comparative dataset on skills, qualifications and the employability of post-2014 migrants, refugees and asylum seekers

The dataset provides harmonized country data on the skills and qualifications of post-2014 migrants, refugees and asylum seekers in all SIRIUS countries (Czech Republic, Denmark, Finland, Greece, Italy, Switzerland, United Kingdom).  This dataset and the related codebook have been put together within the framework of Work package 1 of the SIRIUS Project "Skills and Integration of Migrants, Refugees and Asylum Applicants in European Labour markets". The work package, titled “Labour market barriers and enablers", aimed to  determine (1) the position of post- 2014 migrants, refugees and asylum seekers in the labour market of their host country, (2) the main features of the host countries’ labour markets focusing on the sectoral structure and the relevant skills and occupations.   Acknowledgments and disclaimers This research was conducted under the Horizon 2020 project ‘SIRIUS’ (770515). The sole responsibility of this publication lies with the author. The European Union is not responsible for any use that may be made of the information contained therein.

SANER 2022 - Industrial Track - Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange

Dataset related to the paper Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange.    Saner 2022 Industrial Track

Videos: EIT Food - SmartBreakfast project

Videos about EIT-Food SmartBreakfast project, 3D printed breakfast bar and a senior consumer test carried out at AZTI. YouTube links: <a href="http://: https://www.youtube.com/watch?v=UplSyeEv-2s&t=3s">SmartBreakfast project – EIT Food: partners, objectives and results</a> <a href="https://www.youtube.com/watch?v=G2ps2qSgN88">3D printer Breakfast Bar</a> <a href="https://www.youtube.com/watch?v=N9Uck-ImBms">Senior consumer test of a 3D printed breakfast bar</a>

opencc-by-4.0Dec 2021View details →

Citizen science at public libraries: Data on librarians and users perceptions of participating in a citizen science project in Catalunya, Spain

As libraries struggle to keep pace with the changing societal landscape, emerging practices such as citizen science (CS) initiatives are being incorporated to reinforce the idea of public libraries as gathering, meeting, and collaboration spaces within the context of shared community and shared learning resources. However, there is little empirical evidence of whether the most open and participatory ways that CS puts forward can converge with and be nurtured by the essence of public libraries. Also, the roles of librarians and users in the ‘next generation public library’ have been under-developed. As the number of CS initiatives at public libraries grows, so does the need to collect evidence on the impact and the capacity of assimilation of CS practices. The data describes librarians and users' perceptions of participating in a citizen science project. Two hands-on activities for librarians of the Barcelona Network of Public Libraries were implemented. One was a training course for 30 librarians from 24 libraries which allowed them to envisage citizen science implementation in each library. The second activity consisted in the co-creation of a citizen social science project. 40 library users, 7 librarians from 3 different cities, and professional scientists, were involved. The data on librarians and users' perception was collected through participant observation, surveys, and a focus group to identify strengths and challenges of implementing citizen science at public libraries. The data covers librarians and users attitudes towards citizen science, their motivations to participate, their perceived ability to implement a citizen science project (as for librarians) or to contribute to science (as for library users), and the participants intention to keep engaged with citizen science, drawing on the Theory of Planned Behavior. Responses to closed-ended survey questions are analyzed at a descriptive level. The qualitative feedback from the focus group and the open-ended survey question on motivations is subjected to a thematic analysis. The data offers interesting insights to identify opportunities and challenges of implementing citizen science at public libraries, contributing to the debate over the public library's mission as local community hub. The dataset is formed by 5 tables: <ol> <li>Librarians_pre.csv: data on librarians profiles, attitudes towards citizen science, expected impact of the project and self-efficacy collected at the beginning of the Citizen Science Lab.</li> <li>Librarians_post.csv: data on librarians profiles, attitudes towards citizen science, perceived impact of the project and self-efficacy collected at the end of the Citizen Science Lab.</li> <li>Users_first_phase.csv: data on users profiles, motivation, attitudes towards the library, confidence to perform scientific tasks and self-efficacy collected at the beginning of the Science and Citizen Action.</li> <li>Users_second_phase.csv: data on users profiles and motivation collected at the middle of the Science and Citizen Action.</li> <li>Users_last_phase.csv: data on users profiles, attitudes towards the library, confidence to perform scientific tasks and perceived impact of the project collected at the end of the Science and Citizen Action.</li> </ol> Citizen Science Lab Questionnaire (Librarians_pre) <table> <tbody> <tr> <td> Personal information </td> </tr> <tr> <td> 1. [rol_1] What is your role at the library? </td> <td> <ul> <li>Director</li> <li>Library technician</li> <li>Support technician</li> <li>Service support</li> </ul> </td> </tr> <tr> <td> 2. [years_1] How long have you been working at the library? </td> <td> <ul> <li>2 or less</li> <li>3 to 5 years</li> <li>6 to 10 years</li> <li>11 to 20 years</li> <li>more than 20 years</li> </ul> </td> </tr> <tr> <td> 3. [back_1] Do you have a scientific background? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 4. [know_1] Have you already heard about citizen science? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 5. [part_1] Have you already participated in a citizen science project? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> Attitudes towards users engagement </td> </tr> <tr> <td> 6. [att_lib_pre1] Do you believe that library users are able to participate in a citizen science project? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> 7. [att_lib_pre2] Do you believe that library users will commit to participating in a citizen science project? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> Expected impacts </td> </tr> <tr> <td> 8. [exp_lib_pre] To what extent do you believe that citizen science may bring positive impacts to your library?   </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> Self-efficacy </td> </tr> <tr> <td> 9. [se_lib_pre1] Right now, do you feel able to recommend any citizen science project to library users? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 10. [se_lib_pre2] Right now, do you feel able to implement yourself and lead a citizen science project? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> </tbody> </table> Citizen Science Lab Questionnaire (Librarians_post) <table> <tbody> <tr> <td> Personal information </td> </tr> <tr> <td> 1. [years_2] How long have you been working at the library? </td> <td> <ul> <li>2 or less</li> <li>3 to 5 years</li> <li>6 to 10 years</li> <li>11 to 20 years</li> <li>more than 20 years</li> </ul> </td> </tr> <tr> <td> 2. [back_2] Do you have a scientific background? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 3. [sat_1] To what extent does the project meet your initial expectations? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> Attitudes towards users engagement </td> </tr> <tr> <td> 4. [att_lib_post1] Do you believe that library users will commit to participating in a citizen science project? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> 5. [att_lib_post2] What are/could be the potential barriers to users engagement in citizen science? </td> <td> [open] </td> </tr> <tr> <td> Perceived impact </td> </tr> <tr> <td> 6. [imp_lib] What do you believe that citizen science may bring to public libraries and users? 1 [Not at all] …… 5 [Totally]   </td> <td> a. Knowledge of the scientific process b. New connections among participants                                                        c. Fun d. New knowledge of the local environment e. Scientific evidence on a common concern f. Social cohesion g. Positive attitudes towards science h. Willingness to learn i. Critical thinking and self-efficacy </td> </tr> <tr> <td> Self-efficacy </td> </tr> <tr> <td> 8. [se_lib_post1] Right now, do you feel able to recommend any citizen science project to library users? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 9. [se_lib_post2] Right now, do you feel able to implement yourself and lead a citizen science project? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> Intention to keep engaged </td> </tr> <tr> <td> 10. [eng_lib] To what extent are you motivated to keep engaged with citizen science?                                                                                                                                                                              </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> </tbody> </table>   Science and Citizens Action Focus group guide (Librarians) Opening questions 1. To start with…. Are you satisfied with the project? Probe: Yes, no, why? Was it fun/interesting/challenging/enriching…. 2. Do you feel you have learned something new? Probe: About your library’s environment, users, science and citizen science... Is there anything special that you will take with you after the project? Reflections on the cocreation process 3. At what time during the project have you felt most comfortable? Probe: For example, has it been easier to lead the activity and/or involve and retain the community? Did you find it entertaining? 4. At what time during the project have you felt less at ease? Probe: What was challenging during the cocreation process? 5. To what extent do you feel more capable of implementing and leading a citizen science project in your library right now? Probe: For example, in the case of both more crowdsourcing and of cocreated projects that actively involve the community Reflections on the perceived impact 6. To what extent does the project meet your initial expectations? Probe: in line with what you discussed at the beginning of the project, you expected it to promote participation, new connections among participants, improve the library perceptions and stimulate the participants’ critical thinking...Do you think that citizen science may meet these expectations? Reflections on citizen science at public libraries 7. To what extent can citizen science (in its most ‘extreme’ form of participation) be imagined as an activity within the library that promotes more active user participation? Probe: Through for example cocreation, experimentation, and hands-on learning activities... 8. Do you think that the activity has brought new knowledge? What new knowledge has the activity brought from your perspective? Probe: Knowledge of the scientific process, knowledge of the community or new users... 9. What could be the opportunities and barriers of introducing citizen science at public libraries? And the barriers? Probe: Like for example improving the perception of the library, actively involving certain users...What could be the ‘return’ for the community? What impact can citizen science projects have on making the environment more dynamic from libraries? 10. More generally, what could be the ‘added value’ of the introduction of citizen science within the library’s range of activities? Probe: Is it a fun activity that promotes socialization, for example? Or that allows to generate new knowledge? Or that highlights the library’s social value? Or, also, that may offer new uses and new roles to the library? Can it foster a sense of community with the library as a connector? What other impacts can be generated in your environment? Closing 11. Do you see yourselves the next year, implementing a citizen science project as part of the library’s range of activities? And adopting an existing one? Probe: Are you motivated to get more involved with citizen science projects? What kind of projects? What level of user involvement do you expect? What barriers do you see to users’ involvement? What benefits and opportunities do you think you can bring to the library? 12. We have now reached the end of the discussion. Anyone want to add anything else? Science and Citizens Action Questionnaire (Users_first_phase) <table> <tbody> <tr> <td> Personal information </td> </tr> <tr> <td> 1. [gen_1] Are you..? </td> <td> <ul> <li>Woman</li> <li>Man</li> <li>NA</li> </ul> </td> </tr> <tr> <td> 2. [years_3] How old are you? </td> <td> <ul> <li>18-25</li> <li>26-35</li> <li>36-45</li> <li>46-55</li> <li>56-65</li> <li>66+</li> </ul> </td> </tr> <tr> <td> 3. [rol_2] What is your role at the library? </td> <td> <ul> <li>Library user not associated with local associations</li> <li>Library technician</li> <li>Member of a local association</li> <li>Representative of public administrations</li> <li>Representative of the private sector</li> <li>Others:</li> </ul> </td> </tr> <tr> <td> 4. [back_3] Do you have a scientific background? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 5. [part_2] Have you already participated in a citizen science project? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> Motivations to participate </td> </tr> <tr> <td> 6. [mot_us] What did motivate you to participate in the project? </td> <td> [open] </td> </tr> <tr> <td> Attitudes towards the library </td> </tr> <tr> <td> 7. [att_us_pre1] To what extent do you believe that your library is responsive to the community needs? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> <tr> <td> 8. [att_us_pre2] To what extent to you believe your library is able to face local challenges based on users' active participation? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> Confidence to perform scientific tasks </td> </tr> <tr> <td> 9. [conf_us_pre] To what extent do you feel able to contribute to perform the following scientific tasks: 1 [Not at all] …… 4 [Totally] </td> <td> a. Formulate the research question b. Data collection c. Analysis and interpretation of the results d. Propose concrete actions based on scientific evidence </td> </tr> <tr> <td> Self-efficacy </td> </tr> <tr> <td> 10. [se_us_pre] To what extent do you feel able to positively contribute to the library and your community? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4 [Totally]</li> </ul> </td> </tr> </tbody> </table> Science and Citizens Action Questionnaire (Users_second_phase) <table> <tbody> <tr> <td> Personal information </td> </tr> <tr> <td> 1. [gen_3] Are you..? </td> <td> <ul> <li>Woman</li> <li>Man</li> <li>NA</li> </ul> </td> </tr> <tr> <td> 2. [years_5] How old are you? </td> <td> <ul> <li>18-25</li> <li>26-35</li> <li>36-45</li> <li>46-55</li> <li>56-65</li> <li>66+</li> </ul> </td> </tr> <tr> <td> 3. [rol_4] What is your role at the library? </td> <td> <ul> <li>Library user or technician not associated with local associations</li> <li>Member of a local association</li> <li>Representative of public administrations</li> <li>Representative of the private sector</li> <li>Others:</li> </ul> </td> </tr> <tr> <td> 3. [back_5] Do you have a scientific background? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 4. [mot_us2] To what extent are you motivated to carry out the experiment? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> </tbody> </table> Science and Citizens Action Questionnaire (Users_last_phase) <table> <tbody> <tr> <td> Personal information </td> </tr> <tr> <td> 1. [gen_2] Are you..? </td> <td> <ul> <li>Woman</li> <li>Man</li> <li>NA</li> </ul> </td> </tr> <tr> <td> 2. [years_4] How old are you? </td> <td> <ul> <li>18-25</li> <li>26-35</li> <li>36-45</li> <li>46-55</li> <li>56-65</li> <li>66+</li> </ul> </td> </tr> <tr> <td> 3. [rol_3] What is your role at the library? </td> <td> <ul> <li>Library user or technician not associated with local associations</li> <li>Member of a local association</li> <li>Representative of public administrations</li> <li>Representative of the private sector</li> <li>Others:</li> </ul> </td> </tr> <tr> <td> 3. [back_4] Do you have a scientific background? </td> <td> <ul> <li>Yes</li> <li>No</li> </ul> </td> </tr> <tr> <td> 4. [part_3] To how many cocreation sessions have you participated? </td> <td> <ul> <li>None</li> <li>1</li> <li>2</li> <li>3</li> </ul> </td> </tr> <tr> <td> 5. [sat_2] To what extent are you satisfied with the experiment? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> Attitudes towards the library </td> </tr> <tr> <td> 6. [att_us_post] To what extent do you believe that the project has positively changed your perception of the library? </td> <td> <ul> <li>1 [Not at all]</li> <li>2</li> <li>3</li> <li>4</li> <li>5 [Totally]</li> </ul> </td> </tr> <tr> <td> Confidence to perform scientific tasks </td> </tr> <tr> <td> 7. [conf_us_post] To what extent do you feel able to contribute to perform the following scientific tasks: 1 [Not at all] …… 5 [Totally] </td> <td> a. Formulate the research question b. Data collection c. Analysis and interpretation of the results d. Propose concrete actions based on scientific evidence </td> </tr> <tr> <td> Perceived impact </td> </tr> <tr> <td> 8. [imp_us] What do you believe that citizen science may bring to public libraries and users? 1 [Not at all] …… 5 [Totally]   </td> <td> a. Knowledge of the scientific process b. New connections among participants                                                                  c. Fun d. New knowledge of the local environment e. Scientific evidence on a common concern f. Social cohesion g. Positive attitudes towards science h. Willingness to learn i. Critical thinking and self-efficacy </td> </tr> </tbody> </table>