Public copy of Ethics of Data - NGO Data Driven Project Checklist
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Topic HeadingItem
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1Conceptualization and Scopingscope current state
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what are the risks and benefits
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Do you need the data? (over collection)
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what is the goal of the project
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internal NGO data - what are the guidelines for this data collection (how can the data show or change the NGO)
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what are the authorities /roles of the NGO
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what data will we omit/ consequences
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need a lexicon of best practices in collecting core data
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can the data be subject to supena/legal discovery
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id outcomes and measures you want to achieve
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is this data really important
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has the data been collected before by someone else
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what data do we collect and why
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what are top 3 mission goals of your group? If the project does not support them , then quit now.
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is this data collected for compliance or mission goals
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define problem collect data from target populations
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does this data collection help the day to day work of the collector
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is the population from whom you collect the data relevant to its use?
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accummulating risk measure throughout project
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how is the data similar or different from other data sets?
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2Fundinga deep conversation between ngo and funder - a practical data checklist
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do the benefits of data collection exceed the costs?
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there needs to be funder education on data ethics
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We need a small NGO resource center and funders review board to help inform ethical data driven projects. (This was spun into a different group discussion)
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3Data collection checklist/assessmentdecide what kind of data to collect
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which tools should you use to collect it
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collect data to monetize, only collect what is useful
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indicator selection
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figure out what data to collect and from whom
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will collecting the data matter? would something change
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who is put at risk by collecting this data
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how can collectors and subjects use and view the data later
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what data do we need to manage the project and meet the goals
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what granularity is necessary? eg. do you need birthdate or just year/age? Is the risk worth the result?
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What do risk and consent mean in this context
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Plan for the exit options at the beginning
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id data required for outcome measures
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when do you collect data and share in risk areas
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Conception , objective choice, tool choice data choice
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who collects our data, role in larger system
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what convenience data exists that is relevant
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do a risk assessment
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4Resourcingwhat resources are needed for a data driven project
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who is collecting the data and do they care
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who should collect the data?
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who are my collectors and can i reach them beforehand
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5Trainingtraining researchers/collectors
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develop communications for data collectors or online messaging
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teach risk
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6Legalnon-profits lack the funding to do risk assessment
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how to deal with complex global law for projects?
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have an IRB/volunteer review board
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volunteer ethical review board
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are we compliant with applicable law
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7Pilotwhat do you do with data if pilot fails?
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8Data Gatheringwho do we get the data from
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collection - original and derivative
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can the data subjects meaningfully consent
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what expectations are being created by collecting this data
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what about deliberate selection bias?
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deploy survey
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9Storage//Archivingwhere do you store the data
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archiving process?
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how long do you need to keep the data
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do you need to store the raw data or can you aggregate and just share results
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10data analysisdata consolidation and cleaning
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aggregate data
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analysis
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data curation?
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what do you do when you get negative results
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what if the data analyst has no context and was not part of the data collection
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how will this analysis change the decision making
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what to do with extra data> Is it public good if available
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what kind of anaylsis do we need to do
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11verificationaccuracy check?
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12communicationswho need to know and what do they need to know?
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publication plan/sharing?
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how can we avoid release of confidential personal data
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give feedback on data use to data provider
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do you trust the people who will take action eg. law enforcement
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how do we communicate the knowledge to 3rd parties
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13audit/quality controlwho and how can they verify?
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who checks the quality and how
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what are the potential flaws with this data
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what do you publish or not publish?
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how do we avoid substituting algorytihms for judgement
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deletion
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is this information retraceable?
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what if someone stole the data
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can data be reidentified
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14documentationwhat do do with data
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which decisions were made about the data. a data audit trail
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how will we share our lessons learned?
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