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209 results for “anonymization”

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zenodo48/100

Anonymous Data on Swingers in Germany Harvested on the Web

The data package consists of various files that contain different types of information, mainly focusing on anonymous swingers’ data in various regions: <h2>1. Residents Data (tabular)</h2> Focus: Demographic and socio-economic data at the county level, focusing on the swinger community. It includes median ages, population densities, and economic factors. Unique Aspects: Inclusion of demographic details like age groups, employment sectors, and divorce rates, allowing for a deeper socio-economic analysis. Format: The data are provided in both *.xlsx and *.sav formats, allowing sharing and long-term access to the data. <h2>2. Software</h2> Python scripts used for data conversion and structuring are provided for transparency reasons. <h2>3. Calculation Results Files</h2> Files related to various calculations which had led to the specific design of the data are provided for transparency reasons. They are provided in *.xlsx, *.pdf, and *md format, as is most convenient to adequately reflext the respective content. Please refer to the file readme.md for more details.

opencc-zeroJan 2024View details →

zenodo48/100

IPBES Data Management Tutorials - Session 3.5: Data management report details: Sensitive data, anonymization, and ethical considerations

The IPBES data management tutorials are short videos to help experts implement the IPBES data and knowledge management policy. They cover topics ranging from data and knowledge management policy, reports, active research data, tools, and examples. The IPBES data management reports chapter provides an overview and discussion of specific elements of IPBES data management reports. This session on data management report details: Sensitive data, anonymization, and ethical considerations captures specific considerations and processes for IPBES experts regarding sensitive data and Indigenous and local knowledge within data management reports.

opencc-by-4.0Aug 2022View details →

zenodo44/100

An Empirical Characterization of Event Sourced Systems and Their Schema Evolution - Lessons from Industry - Accompanying Anonymized Transcripts

Anonymized interviews with 25 engineers on their experience applying Event Sourcing, with accompanying classifications. These transcripts are used in our publication "An Empirical Characterization of Event Sourced Systems and Their Schema Evolution - Lessons from Industry".

opencc-by-4.0Sep 2020View details →

zenodo44/100

Anonymized Graph Data with Friend Connections of 189505 VKontakte Users

The dataset contains anonymized graph data with friend connections of 189505 VKontakte users. The dataset was used in <a href="http://github.com/filipp134/vk_bot_detection">this</a> Github project on the detection of social bots on VKontakte. The script which was used for the collection of the dataset is <a href="https://github.com/filipp134/vk_bot_detection/blob/main/Collecting%20datasets%20and%20merging%20them%20into%20one/collect_graph_data.py">here</a>. The dataset was collected in the following 2 steps by using the official <a href="https://dev.vk.com/api/getting-started">VKontakte API</a>: 1. Friend connections of 11766 VKontakte users, who had 177739 unique friends, were collected. 2. Friend connections of these 177739 users were collected.  The dataset is in JSON format and is quite heavy: 424.5 MB.

opencc-by-4.0Feb 2022View details →

zenodo44/100

FT3 Anonymous (1) 4-key fagottino: measurements, photos.

Dataset of FT3 Anonymous (1) 4-key fagottino containing (partial) external and internal measurements and photos.

opencc-by-4.0Apr 2019View details →

zenodo44/100

GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (anonymized version - third part)

<a title="GENEActiv" href="https://activinsights.com/technology/geneactiv/" target="_blank" rel="noopener">GENEActiv</a> accelerometer .csv files converted with a 1 second epoch from raw GENEActiv .bin files recorded during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"]. Devices are 60-Hz triaxial accelerometers. This dataset also contains participantCharacteristics.csv that povides basic information about participants and read_a_binFile_share.R that is a short R code aiming at converting and saving accelerometer data from .bin files in 1 second epoch .csv files (consider the Methods section). Participant characteristics: 10 to 16 years old students and some parents. Number of participants: 231 (206 adolescents + 25 adults). Year of the study: 2018 - 2019. Place of the study: New Caledonia. The accelerometer .csv files with a 1 second epoch and extracted from raw .bin files are available in open datasets: <ul> <li><a title="Open dataset - first part" href="https://doi.org/10.5281/zenodo.12615468" target="_blank" rel="noopener">anonymized version - first part</a></li> <li><a title="Open dataset - second part" href="https://doi.org/10.5281/zenodo.12638746" target="_blank" rel="noopener">anonymized version - second part</a></li> <li><a title="Open dataset - third part" href="https://doi.org/10.5281/zenodo.12682660" target="_blank" rel="noopener">anonymized version - third part</a></li> </ul> The accelerometer raw .bin files are available in restricted datasets: <ul> <li><a title="Restricted dataset - first part" href="https://doi.org/10.5281/zenodo.11594645" target="_blank" rel="noopener">non-anonymized version - first part</a></li> <li><a title="Restricted dataset - second part" href="https://doi.org/10.5281/zenodo.12638965" target="_blank" rel="noopener">non-anonymized version - second part</a></li> <li><a title="Restricted dataset - third part" href="https://doi.org/10.5281/zenodo.12661429" target="_blank" rel="noopener">non-anonymized version - third part</a></li> </ul> Other participant characteristics (age, place of living, cultural community and socio-economic status) are available in a <a title="Information associated with GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized information version)" href="https://doi.org/10.5281/zenodo.12195186" target="_blank" rel="noopener">restricted non-anonymized dataset</a>. When using this dataset, please cite the following reference: <a title="Wattelez et al. 2025" href="https://doi.org/10.1016/j.dib.2024.111228" target="_blank" rel="noopener">G. Wattelez, S. Frayon, O. Galy, Assessing physical activity/behavior of adolescents living in the Pacific with accelerometer data: 231 GENEActiv records in New Caledonia, Data in Brief 58 (2025) 111228, doi: 10.1016/j.dib.2024.111228</a>

embargoedcc-by-4.0Jun 2024View details →

zenodo44/100

GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (anonymized version - second part)

embargoedcc-by-4.0Jun 2024View details →

zenodo44/100

Value creation stories anonymized open data set (Immunization Agenda 2030 Full Learning Cycle, 7 March - 20 June 2022)

# Title Immunization Agenda 2030 (IA2030) 1st Movement Full Learning Cycle (FLC 2022) – “How are you doing?” Value Creation Stories Survey (Version 1.0) # Research audience Education researchers interested in the application of the “value creation stories” (VCS) conceptual framework elaborated by Etienne Wenger et al. in the study of communities of practice and other types of digital communities. # Credits ## Author The Geneva Learning Foundation 18 avenue Louis Casaï CH-1209 Geneva, Switzerland research@learning.foundation ### Principal Investigator and corresponding author Reda Sadki, The Geneva Learning Foundation (TGLF) reda@learning.foundation ## Project partners Bridges to Development University of South Australia Centre for Change and Complexity in Learning (C3L) ## Roles and responsibilities - Design: The Geneva Learning Foundation - Implementation (sample collection): The Geneva Learning Foundation - Processing: The Geneva Learning Foundation, Bridges for Development, Centre for Complexity and Change in Learning (C3L) - Anonymization: The Geneva Learning Foundation and Bridges for Development - Data cleaning: Bridges to Development - Submission: The Geneva Learning Foundation ## Funding sources or sponsorship that supported the data collection Wellcome, Bill & Melinda Gates Foundation (BMGF) ## Recommended citation The Geneva Learning Foundation, 2023. Value Creation Stories (VCS) weekly feedback survey, 2022 Full Learning Cycle (FLC) of the Movement for Immunization Agenda 2030 (IA2030) (Version 1.0). [Data Set]. The Geneva Learning Foundation. DOI: 10.5281/zenodo.7763922 # Description of the sample ## File list: This file is IA2030_FLC_2022_Value_Creation_Stories.README.md IA2030-EN_FLC_2022_Value_Creation_Stories-questions_mapping.csv : List of the survey’s questions and their code in English as well as their unit. (21 questions) - Version 1: Geneva Learning Foundation, 31 March 2023.  IA2030-EN_FLC_2022_Value_Creation_Stories.csv : Dataset Response of participants that replied in English. (n: 2101, obs:5601) - Version 1: Geneva Learning Foundation, 31 March 2023.  IA2030-FR_FLC_2022_Value_Creation_Stories-questions_mapping.csv: List of the survey’s questions and their code in English as well as their unit. (21 questions) - Version 1: Geneva Learning Foundation, 31 March 2023. IA2030-FR_FLC_2022_Value_Creation_Stories-Google_translation.csv: Dataset Response of participants that replied in French translated to English using “Google Translate” (n: 1585, obs:4493) - Version 1: Geneva Learning Foundation, 31 March 2023. IA2030-FR_FLC_2022_Value_Creation_Stories.csv: Dataset Response of participants that replied in French (n: 1585, obs:4493) - Version 1: Geneva Learning Foundation, 31 March 2023. Relationship between files:  The questions codes data set are the same code as the column variables and can be connected. ## Relationship between files The questions codes data set are the same code as the column variables and can be connected. ## Related data sets This is a subset of data collected by The Geneva Learning Foundation (TGLF) during the 1st IA2030 Full Learning Cycle (FLC). The complete data set is more comprehensive, and includes: demographic information (gender, country), health system information (respondent’s health system level), respondents’ analyses of challenges and priorities.  Additional data sets for the first Full Learning Cycle (FLC) of the Movement for Immunization Agenda 2030 (IA2030) are available from The Geneva Learning Foundation (TGLF) Insights Unit [insights@learning.foundation](insights@learning.foundation) ## Other publicly accessible locations of the data The Geneva Learning Foundation publishes data sets in relation to its Immunization Agenda 2030 (IA2030) Movement learning programme in the Zenodo open repository community: https://zenodo.org/communities/ia2030/ ## 1. Purpose and Objectives ### Primary goal of the survey: This survey had two goals in the context of TGLF’s IA2030 Movement Full Learning Cycle programme (2022):  1. Provide an asynchronous mechanism for support between peers (participants) and from the TGLF team; and 2. collect and measure programme participants’ value creation stories (VCS) during the programme. Martin de Laat’s “value creation stories” (VCS) has been used primarily in small-scale, qualitative studies of communities of practice, online forums, and education activities. This data set includes both quantitative (Likert) and qualitative (open text) responses to the VCS questions, collected over a period of four months (7 March – 20 June 2022) from a cohort that began with 6,185 participants on the start date. ## 2. Population and Sample The target population were participants of the Geneva Learning Foundation’s Movement for Immunization Agenda 2030 (IA2030) learning programme. The initial cohort admitted to the programme was 6,185 individuals from 99 countries. Only participants who were formally admitted to the programme received the invitation to complete the survey. Programme participants were free to choose if and when to report (self-selection), and their responses were not checked against any other measures (self-reporting). ### Languages: French and English ## 3. Survey Design and Methods Data collection period: 7 March 2022 – 20 June 2022 Between 7 March and 20 June 2023, participants in the Geneva Learning Foundation’s “Immunization Agenda 2030” (IA2030) Movement Full Learning Cycle (FLC) were asked to respond to a questionnaire titled “How are you doing?”. Participants received a personalized email with the request to share feedback about their experience during the week. The link to share feedback was also included in other reminder and information emails sent in response to participant needs. The first survey was launched on the 11 of March 2022 and the last at 17 of March 2022, totalizing 15 requests. Participants could answer the survey at any time and as many times that they wished.   The group of 6,185 participants grew over the course of the Cycle, as additional participants were able to join the initiative throughout the four-month period. ### Software- or Instrument-specific information needed to interpret the data - Automated translation of French data was performed using [Google Translate](https://translate.google.com/?sl=en&tl=fr&op=docs) - Methods used for removing or anonymizing personal identifiers or sensitive information: - Unique identifier: Unique identifiers were anonymized using MD5 Hashing via the web site [Miracle Salad](https://www.miraclesalad.com/webtools/md5.php.).Unique identifiers can be used to identify respondents who may have answered the survey more than once, at different points in time. This approach provides a method to anonymize sensitive data using MD5 hashing.*Limitation: MD5 hashing is a one-way function; it is not possible to dehash the data and recover the original information.** - Macros developed in Excel to replace Country names in qualitative responses. (No country information were collected in this survey, but some respondents referred to their specific contexts in their responses.) The macro did not account for typos, in case any country information is found please contact: [research@learning.foundation](research@learning.foundation) ### Data collection start and end dates: 7 March 2023 until 20 June 2023 #### Events or circumstances during data collection that may have influenced results: No requests for responses were sent during TGLF’s “Term break” between 16-30 April 2022. ## 4. Data Processing and Cleaning - Incomplete or inconsistent responses: Not cleaned, as respondents were able to opt out of specific sections of survey or skip questions. - Data transformations or imputations: None - Treatment of outliers or extreme values: None ## 5. Variables and Measures The survey included Likert scale questions and qualitative open texts based the conceptual framework for Value Creation Stories (VCS) developed by Wenger et. al. (2011). There are no derived or calculated variables. Items are Likert scale, multiple choice, and open text. ## 6. Data Quality and Reliability All the responses done before or after the FLC period (7 March – 20 June 2022) were excluded of the sample. ## 7. Data Privacy and Anonymization ### Methods used for removing or anonymizing personal identifiers or sensitive information: - Unique identifier: Unique identifiers were anonymized using MD5 Hashing via the web site https://www.miraclesalad.com/webtools/md5.php. Unique identifiers can be used to identify respondents who may have answered the survey more than once, at different points in time. This approach provides a method to anonymize sensitive data using MD5 hashing. - Limitation: MD5 hashing is a one-way function; it is not possible to dehash the data and recover the original information.  - Macros developed in Excel to replace Country names in qualitative responses. (No country information were collected in this survey, but some respondents referred to their specific contexts in their responses.) ## 8. Data Availability and Accessibility This data set is made available on Zenodo.org in the Zenodo community “Movement for Immunization Agenda 2030 (IA2030)” https://zenodo.org/communities/ia2030/ Requests for additional information should be addressed to research@learning.foundation. This is a subset of data collected by The Geneva Learning Foundation (TGLF) during the 1st IA2030 Full Learning Cycle (FLC). The complete data set is more comprehensive, and includes: demographic information (gender, country), health system information (respondent’s health system level), respondents’ analyses of challenges and priorities. ### Other publicly accessible locations of the data The Geneva Learning Foundation publishes data sets in relation to its Immunization Agenda 2030 (IA2030) Movement learning programme in the Zenodo open repository community: https://zenodo.org/communities/ia2030/ ### Related data sets Additional data sets for the first Full Learning Cycle (FLC) of the Movement for Immunization Agenda 2030 (IA2030) are available from The Geneva Learning Foundation (TGLF) Insights Unit insights@learning.foundation ## 10. Ethical Considerations ### Ethical guidelines followed during data collection: TGLF’s research abides by the principles of the Cantonal Commission for Research Ethics (CCER), the Federal Law on Research on Human Beings (RS 810.30), Swiss Human Research Act (HRA) and the Ordinance on Organisational Aspects of the Human Research Act (HRA Organisation Ordinance, OrgO-HRA) ### Informed consent and participant rights information: In order to join TGLF’s IA2030 Full Learning Cycle programme, participants had to confirm their agreement to use of their responses “for research, learning, evaluation, communication, and advocacy, in line with the Foundation’s mission”. Participants were able to opt out of the VCS questions by selecting “No” when asked “Could we ask you five questions about your participation?”. They were informed these questions were asked in order to “share your feedback in the next weekly Assembly”, the weekly synchronous meeting for programme participants. The rationale for sharing such feedback was also explained; “Your contribution will help everyone understand how we are doing as a group, and also help us to better support you.” Data protection and confidentiality Consent was requested during the application and submitted of action plan period for sharing data, in line with the Geneva Learning Foundation’s data protection and confidentiality policy. # Copyright and license The Geneva Learning Foundation © 2022. This data set and all associated files are licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) © The Geneva Learning Foundation 2023 Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International; https://creativecommons.org/licenses/by-nc-sa/4.0/. Under the terms of this license, you may copy, redistribute and adapt the data set for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this data set, there should be no suggestion that the Foundation endorses any specific organization, products or services. The use of the Foundation logo is not permitted. If you use the data set, then you must license your work under the same or equivalent Creative Commons license. If you create a translation of this data set, you should add the following disclaimer along with the suggested citation: “This translation was not created by the Geneva Learning Foundation. The Foundation is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition.” Any mediation relating to disputes arising under the license shall be conducted in accordance with the mediation rules of the World Intellectual Property Organization. General disclaimers. The designations employed and the presentation of the data set do not imply the expression of any opinion whatsoever on the part of the Foundation concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or recommended by the Foundation in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. All reasonable precautions have been taken by the Foundation to verify the information contained in this data set. However, the published material is being distributed without warranty of any kind, either expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall the Foundation be liable for damages arising from its use. This data set contains individual views and does not necessarily represent the decisions or the policies of the Foundation. Version 1.0 (31 March 2023): reviewed internally; reviewed externally.  # References Wenger, E., Trayner, B., de Laat, M., 2011. Promoting and assessing value creation in communities and networks: a conceptual framework (Rapport No. 18). Oitpen Universiteit, Ruud de Moor Centrum. Wenger, E., Trayner, B., de Laat, M., 2011. Promoting and assessing value creation in communities and networks: a conceptual framework (Rapport No. 18). Oitpen Universiteit, Ruud de Moor Centrum. Victoria J. Marsick, Rachel Fichter, Karen E. Watkins, 2022. From Work-based Learning to Learning-based Work: Exploring the Changing Relationship between Learning and Work, in: The SAGE Handbook of Learning and Work. SAGE Publications. Watkins, K.E., Sandmann, L.R., Dailey, C.A., Li, B., Yang, S.-E., Galen, R.S., Sadki, R., 2022. Accelerating problem-solving capacities of sub-national public health professionals: an evaluation of a digital immunization training intervention. BMC Health Serv Res 22, 736. https://doi.org/10.1186/s12913-022-08138-4 Watkins, K.E., Kim, K., 2019. Measuring the Impact of the WHO Scholar Programme Courses for Immunization (2016-2018) (Evaluation report). University of Georgia at Athens, Athens, United States. Watkins, K.E., Bhattarai, A., 2019. Analysis of the Impact Accelerator Launch Pad Individual Acceleration Reports in July 2019. University of Georgia at Athens, Athens, United States. # Questionnaire ## Hello {{fname}} {{lname}}. How are you doing in the Movement for Immunization Agenda 2030? ## Do you need help? Do you want to share your experience? We would like to know how you are doing. - I am doing fine. - I have a problem and need help. - I want to share my experience. ## Tell us more about what you want to share. Be specific and detailed so that we can understand. Share your lessons learned, successes, and challenges. ## Did you complete your action for the week? If you did it, how did it turn out? What did you learn in the process? Did anything surprise you? What will you do next? If you did not complete your action, what will you do differently next week? This is a good way to write your thoughts if you did not get to speak in the last session. You can also record an audio message in the IA2030 Movement Dialogue https://t.me/+-PwJxPpyWfQ0ZjRk or share an idea or practice https://accelerator.wazoku.com/ccc/learning in the Ideas Engine. ## What do you need help with? - I do not know what I am supposed to do - I need help with my IA2030 challenge - I want to catch up - I have poor connectivity - I have a problem with technology - Something else ## Tell us more about the problem you are facing. What have you tried to solve this problem? Where did you get stuck? The more information you provide, the better colleagues will be able to help you. ## Have you tried taking time to read and follow the instructions?  Click here https://www.learning.foundation/products/movement-for-immunization-agenda-2030-full-learning-cycle-1-march-2022 to access the video tutorials and slide decks on www.learning.foundation https://www.learning.foundation/login.  Use your email email to log in. Don’t remember your password? Click here to recover it https://www.learning.foundation/password/new.  Take the time to read the instructions – and then follow them step-by-step. Do not forget to come back to finish this questionnaire.  ## Do not suffer in silence. It sounds like you should ask for help from your Movement colleagues.  Click here to connect with colleagues https://t.me/IA2030 in the IA2030 Movement Telegram channel. - When you join Telegram, please introduce yourself and explain the problem that you are facing. Your colleagues can only help you if you describe the issue and explain what you have already done to solve it. - We encourage you to share your challenge in the next short session where we share experience and problem-solve. Click here to register https://us02web.zoom.us/j/86171141804, and then come back to finish this questionnaire. - Surely, someone will be able to help you. But you do have to register https://us02web.zoom.us/j/86171141804 and actually show up at the right time! - Poor connectivity? Click here to listen https://podcasts.google.com/feed/aHR0cHM6Ly9saXN0ZW5ib3guYXBwL2YvODRTTFI0eTY5X05h to our low-bandwidth podcast. And then come back to finish this questionnaire. - You can listen to most sessions in our podcast. This is audio-only, like listening to radio on demand. ## Could we ask you five questions about your participation? We will share your feedback in the next weekly Assembly. Your contribution will help everyone understand how we are doing as a group, and also help us to better support you. Yes No ## Participation changed me as a professional (change in skills, attitudes, identity, self-confidence, feelings, etc.). ## Can you explain how participation changed you as a professional? ## Participation affected my social connections (change in the number, quality, frequency, emotions, etc.) ## Can you explain how participation affected your social connections? ## Participation helped my professional practice (get new ideas, insights, materials, procedures, etc.) ## Can you explain how participation helped your professional practice? ## Participation changed my ability to influence my world as a professional (enhance my voice, contribution, status, recognition, etc.) ## Can you explain how participation changed your ability to influence your world as a professional? ## Participation made me see my world differently (change in perspective, new understandings of the situation, redefine success, etc.) ## Can you explain how participation made you see your world differently? ## Do you remain committed to the Movement for Immunization Agenda 2030? You remain a Member even if you are not actively participating. - Yes, and I am actively participating - Yes, but I am not actively participating - No, I wish to leave the Movement ## We are sorry to see you go. Could you let us know what went wrong? What could we have done better to support you? - (Or just hit RETURN to skip.) ## What is the email you are using? We need your email to follow up and respond to what you shared with us. Do not forget to press the SUBMIT button. ## URL redirection upon completion: https://www.learning.foundation/products/movement-for-immunization-agenda-2030-full-learning-cycle-1-march-2022 ## Thank you [fname] [lname] for sharing your feedback. We will share your feedback in the next weekly Assembly. Your contribution will help everyone understand how we are doing as a group, and also help us to better support you. Click here to check http://cal.ae/eudusmw the IA2030 Movement calendar so you do not miss upcoming event

opencc-by-4.0Mar 2023View details →

zenodo44/100

FT7 Anonymous (8) 3-key fagottino: measurements, photos, endoscopic video

Dataset of FT7 Anonymous (8) 3-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video. Note: Better quality photos will be available at a later date.

opencc-by-4.0Apr 2019View details →

zenodo44/100

Swiss Smart Meter Data - CKW 2021/2022 - anonymized individual metering points

Cleaned Swiss smart meter data based on a collection from CKW AG (see <a href="http://opendata.ckw.ch">opendata.ckw.ch</a>) <ul> <li>Duration: 2 years (1. Jan 2021 - 31. Dec 2022, CET timestamp)</li> <li>Location: Canton Lucerne, Switzerland</li> <li>Interval: 15 minutes</li> <li>Values: Active Energy (kWh) </li> <li>Meters in each year: 4959 (see filtered_IDs.csv for all IDs)</li> </ul> The original dataset has been filtered based <ul> <li>on missing data </li> </ul> This means, all 4959 meters have consumption and reported values over the full duration of 2 years. Files are available as space-saving parquet files per day in year.  Number in filename is number of day within the year. Summary.zip contains summary statistics over all 112148 (unfiltered) meters counting observations (including duplicates) , and aggregating energy data (per month, and or hourly data), see overview.csv within summary.zip

opencc-by-4.0Jan 2023View details →

zenodo40/100

Anonymized Dataset for "Do Programmers Prefer Predictable Code"

This package contains the anonymized dataset, R notebook results, and R code for processing the meaning preserving transformations and human subject study. Note that the title has been changed from the earlier version on arvix which was "Do People Prefer 'Natural' Code?". See the README file for more details.

opencc-by-4.0Mar 2020View details →

zenodo40/100

Anonymized monthly StackOverflow activity for the Python tag

CSV files containing metadata for each question, answer and comment posted on StackOverflow during 2019. Each file contains one month of activity with the body text, titles and usernames removed. User and post ids have been obscured so that they are not traceable, but are consistent throughout the dataset.

opencc-by-4.0May 2020View details →

zenodo40/100

MEDDOCAN corpus: gold standard annotations for Medical Document Anonymization on Spanish clinical case reports

Intro: Meddocan shared task dataset (divided in train, dev and test). In addition, we include here the Meddocan background set. It contains the training, development and test sets of the Meddocan shared task with Gold Standard annotations. In addition, it contains the documents of the background set, without annotations.   Annotation quality Inter-annotator agreement: 98%  For more information, see the <a href="http://ceur-ws.org/Vol-2421/MEDDOCAN_overview.pdf">paper</a>.    Format: Annotations are distributed in Brat format. See <a href="https://brat.nlplab.org/standoff.html">Brat webpage</a> for more information. In addition, annotations are also distributed in XML format (based on i2b2 XML format). In the <a href="https://temu.bsc.es/meddocan/index.php/resources/">Meddocan webpage</a>, there is a script to convert between MEDDOCAN-Brat, MEDDOCAN-XML, and i2b2 formats.   Shared task goal: In the three subtasks, the goal will be to predict the annotations given only the plain text files.    Resources: <ul> <li><a href="https://temu.bsc.es/meddocan/">Web</a></li> <li>Citation: Montserrat Marimon et al. “Automatic De-identification of Medical Texts in Spanish: the MEDDOCAN Track, Corpus, Guidelines, Methods and Evaluation of Results.” In: IberLEF@ SEPLN. 2019, pp. 618–638.</li> <li>Silver Standard corpus</li> <li><a href="https://doi.org/10.5281/zenodo.4279337">Annotation guidelines</a></li> </ul>   For further information, please visit <a href="https://temu.bsc.es/meddocan/">https://temu.bsc.es/meddocan/</a> or email us at encargo-pln-life@bsc.es Copyright (c) 2019 Secretaría de Estado para el Avance Digital (SEAD)

opencc-by-4.0Nov 2020View details →

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Brazilian Scientific Publication Records and Author Affiliations from Lattes until Feb 2017 (Anonymized)

This file contains anonymized data about researcher profiles and publication records available extracted from the Lattes Platform in in February 2017 using the LattesDataXplorer tool. Lattes is a vast repository of researchers' curriculum vitae, widely adopted in Brazil. This platform is maintained by the Brazilian National Council of Scientific and Technological Development (CNPq) and is an internationally renowned initiative. In the zipped file, there are two files: <ul> <li>anon_authors.csv contains data about researchers. It has 3 columns <ul> <li>profile: researcher anonymized id</li> <li>instituition: researcher affiliation</li> <li>zipcode: institution zip code</li> </ul> </li> </ul> <ul> <li>anon_papers.csv contains data about researchers' publications. It has 4 columns: <ul> <li>profile: researcher anonymized id</li> <li>year: publication year</li> <li>venue: publication venue</li> <li>authors: number of authors</li> </ul> </li> </ul>

opencc-by-4.0Nov 2020View details →

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Data set 2 anonymized collection of data on BRAD research participants

Database on research participants in the BRAD project. The Personal Data have been removed in order to make the identification of the research participants impossible. For Polish migrants in the UK, the database contains the information about the application to European Union Settlement Scheme.

opencc-by-4.0Dec 2020View details →

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EU HORIZON2020 CSI-COP Anonymous dataset on Citizen scientists

This dataset complements CSI-COP deliverable report D4.3: 'CSI-COP Citizen Scientists Age, Gender, Socio-Economic and Geographical (AGSEG) Distribution Report'. Researchers can review the dataset and analyse anonymous data on who the citizen scientists were in the EU Horizon2020 funded CSI-COP project with citizen scientists investigating GDPR compliance in websites and apps.

opencc-by-4.0Oct 2023View details →

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YJMob100K: City-Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories

The YJMob100K human mobility datasets (YJMob100K_dataset1.csv.gz and YJMob100K_dataset1.csv.gz) contain the movement of a total of 100,000 individuals across a 75 day period, discretized into 30-minute intervals and 500 meter grid cells. The first dataset contains the movement of 80,000 individuals across a 75-day business-as-usual period, while the second dataset contains the movement of 20,000 individuals across a 75-day period (including the last 15 days during an emergency) with unusual behavior.  While the name or location of the city is not disclosed, the participants are provided with points-of-interest (POIs; e.g., restaurants, parks) data for each grid cell (~85 dimensional vector) as supplementary information (cell_POIcat.csv.gz). The list of 85 POI categories can be found in POI_datacategories.csv.  For details of the dataset, see Data Descriptor:  <ul> <li>Yabe, T., Tsubouchi, K., Shimizu, T., Sekimoto, Y., Sezaki, K., Moro, E., & Pentland, A. (2024). YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories. Scientific Data, 11(1), 397. <a href="https://www.nature.com/articles/s41597-024-03237-9" target="_blank" rel="noopener">https://www.nature.com/articles/s41597-024-03237-9</a>  </li> </ul>     --- Details about the Human Mobility Prediction Challenge 2023 (ended November 13, 2023) ---  The challenge takes place in a mid-sized and highly populated metropolitan area, somewhere in Japan. The area is divided into 500 meters x 500 meters grid cells, resulting in a 200 x 200 grid cell space. The human mobility datasets (task1_dataset.csv.gz and task2_dataset.csv.gz) contain the movement of a total of 100,000 individuals across a 90 day period, discretized into 30-minute intervals and 500 meter grid cells. The first dataset contains the movement of a 75 day business-as-usual period, while the second dataset contains the movement of a 75 day period during an emergency with unusual behavior. There are 2 tasks in the Human Mobility Prediction Challenge. In task 1, participants are provided with the full time series data (75 days) for 80,000 individuals, and partial (only 60 days) time series movement data for the remaining 20,000 individuals (task1_dataset.csv.gz). Given the provided data, Task 1 of the challenge is to predict the movement patterns of the individuals in the 20,000 individuals during days 60-74. Task 2 is similar task but uses a smaller dataset of 25,000 individuals in total, 2,500 of which have the locations during days 60-74 masked and need to be predicted (task2_dataset.csv.gz). While the name or location of the city is not disclosed, the participants are provided with points-of-interest (POIs; e.g., restaurants, parks) data for each grid cell (~85 dimensional vector) as supplementary information (which is optional for use in the challenge) (cell_POIcat.csv.gz). For more details, see https://connection.mit.edu/humob-challenge-2023

opencc-by-4.0Nov 2023View details →

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Information and questionnaire associated with GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized information)

Questionnaire and additional restricted participant information of the following datasets: <a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - first part)" href="https://doi.org/10.5281/zenodo.14043547" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - first part)</a> <a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - second part)" href="https://doi.org/10.5281/zenodo.14089527" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - second part)</a> <a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - first part)" href="https://doi.org/10.5281/zenodo.14043331" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - first part)</a> <a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - second part)" href="https://doi.org/10.5281/zenodo.14089477" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - second part)</a> Participant characteristics: 13 to 17 years old students. Number of participants: 72. Year of the study: 2023. Place of the study: Vanuatu.

restrictedcc-by-4.0Nov 2024View details →

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Anonymized dataset for "Research themes of family and community physicians in Brazil"

This is the anonymized dataset analyzed in the manuscript “Research themes of family and community physicians in Brazil”. It was derived with the first R script in <a href="https://doi.org/10.5281/zenodo.5798092">https://doi.org/10.5281/zenodo.5798092</a> from restricted datasets in <a href="https://doi.org/10.5281/zenodo.3376310">https://doi.org/10.5281/zenodo.3376310</a> and <a href="https://doi.org/10.5281/zenodo.5797816">https://doi.org/10.5281/zenodo.5797816</a>. Both the data and the data dictionary are recorded in comma-separated values, with byte-order mark.

opencc-by-4.0Dec 2021View details →

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Anonymized GTP Tunnel Trace in Mobile IoT

Extensive dataset containing one whole month of create and delete events as well as the total, received, and transmitted volume of devices. We obtained data tunnel related events and volume values over 30 days in October 2021. In total the dataset contains a sample of 500000 unique devices that generate 155 million individual data tunnels.

opencc-by-4.0Feb 2022View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record