name: intro class: center, middle # Ethics and Integrity of Data Collection and Sharing ## Rencontres Mondiales du Logiciel Libre 2015, Beauvais, France • May 2015 Puneet Kishor (Plazi) Released under a [CC0 Public Domain Dedication](https://creativecommons.org/publicdomain/zero/1.0/). --- layout: true --- ## Help * Notes are hidden, but may be seen by pressing **P** on your keyboard. * Press **C** to clone a show. * Press **H** for other keyboard shortcuts. ??? notes here --- ## Approving conventional science projects Traditionally done by Institutional Review Boards (IRBs) > (In the United States) IRBs must approve proposed non-exempt research before involvement of human subjects may begin. —US Dept. of Health and Human Services --- ## But what about… # Citizen Science? --- ## Citizen Science > Citizen science… is changing the relationship between science and society, helping meet environmental challenges by fostering more collaborative, interdisciplinary research. —
How Rise of Citizen Science Is Democratizing Research
--- ## But… ## How do we evaluate, approve and monitor (some) citizen science projects? --- ## Three kinds of open projects .left-column[ ### Contributory ] .right-column[ Projects that are generally designed by scientists and for which members of the public primarily contribute data ]
Bonney, R., Ballard, H., Jordan, R., McCallie, E., Phillips, T., Shirk, J. and Wilderman, C. C.
Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education - a CAISE Inquiry Group Report
, Center for Advancement of Informal Science Education, Washington, DC, 2009.
--- ## Three kinds of open projects .left-column[ ### Contributory ### Collaborative ] .right-column[ Projects designed by scientists and for which members of the public contribute data but also may help to refine project design, analyze data, or disseminate findings ]
Bonney, R., Ballard, H., Jordan, R., McCallie, E., Phillips, T., Shirk, J. and Wilderman, C. C.
Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education - a CAISE Inquiry Group Report
, Center for Advancement of Informal Science Education, Washington, DC, 2009.
--- ## Three kinds of open projects .left-column[ ### Contributory ### Collaborative ### Co-created ] .right-column[ Projects where scientists and members of the public are working together and for which at least some of the public participants are actively involved in most or all steps of the scientific process. ]
Bonney, R., Ballard, H., Jordan, R., McCallie, E., Phillips, T., Shirk, J. and Wilderman, C. C.
Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education - a CAISE Inquiry Group Report
, Center for Advancement of Informal Science Education, Washington, DC, 2009.
--- ##
Three
Four kinds of open projects .left-column[ ### Contributory ### Collaborative ### Co-created ### Self-Organized ] .right-column[ Projects where members of the public are working on their own, either individually or in self-organized groups,
outside conventional academies
. ] --- ## How do we approve non-conventional projects - citizen science - sensors - self-measurement (quantified self) - participant led research (PLR) --- ## Substitute for IRBs # ? --- ## What about ongoing monitoring? ### Collecting data on others ### (Mis-)Reporting Data ### Damaging Irreplaceable Evidence ### Invading Privacy of Others ### Balancing Privacy and Honesty ### Giving Credit --- ## Legal tools are… ### Inadequate ### Inappropriate ### Expensive ### Complicated ### Fear-driven --- # Do no evil ## That hasn't gone down very well --- # Respect and social contract ## Can good behavior and a sense of community work? --- ## Good behavior by another name ### Code of conduct ### Social contract ### Hippocratic oath ### Honor code ### Respect --- ## Importance of data integrity ### open is good but not a substitute for good science ### what if the design is open but the data are bad? --- ## Evaluating data integrity .left-column[ ### validation dimensions ] .right-column[ .two-left-column[ - Accessibility - Amount of information - Believability - Completeness - Concise representation - Consistent representation - Ease of manipulation - Free-of-error ] .two-right-column[ - Interpretability - Objectivity - Relevancy - Reputation - Security - Timeliness - Understandability - Value-added - other? ] ]
Hunter, J., Alabri, A. and van Ingen, C. 2013.
Assessing the quality and trustworthiness of citizen science data
. Concurrency Computat.: Pract. Exper., 25: 454–466. doi: 10.1002/cpe.2923
--- ## Evaluating data integrity .left-column[ ### Validation dimensions ### Reputation ] .right-column[ ### trust across social networks ### co-calibration ]
Hunter, J., Alabri, A. and van Ingen, C. 2013.
Assessing the quality and trustworthiness of citizen science data
. Concurrency Computat.: Pract. Exper., 25: 454–466. doi: 10.1002/cpe.2923