<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T00:23:07Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/152771" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/152771</identifier><datestamp>2023-11-03T03:42:00Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Tsai,  Lily L.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Vibbi, Leonard Francis</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Program in Media Arts and Sciences (Massachusetts Institute of Technology)</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2023-11-02T20:15:00Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2023-11-02T20:15:00Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued">2023-09</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="submitted">2023-09-14T18:08:50.731Z</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/152771</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract">In this study, we examine data collection methods utilized in local communities during humanitarian crises, with a focus on the Sierra Leone COVID-19 scenario. We assess how widely-used data ethics principles in humanitarian data initiatives align with community values. We define these values as encompassing shared principles, virtues, and a collective understanding of what holds significance and meaning to affected communities[1].  &#xd;
&#xd;
Interviews conducted in Freetown communities allowed us to identify common themes across community principles and norms [values] toward data collection activities. Identified principles held by communities were subsequently contrasted with how data collection activities guided by established data ethics guidelines in humanitarian settings were carried out in target communities.&#xd;
&#xd;
Our findings commend the general adherence to ethical benchmarks, yet spotlight notable gaps that call for strategies more attuned to community shared principles and understanding. To address this, we present the "Human Code Exchange" (HCX) ethical data governance framework. HCX promotes participatory data collection, weaving in community values and experiences, thereby ensuring a balanced exchange between data collection activities and the community, and reducing practices that are not in tune with community values. With its core focus on the community, HCX aligns humanitarian data initiatives with the intrinsic values of communities, particularly in the regions of the global south. Our work lays the foundation for a refined data governance framework that places emphasis on ethical data collection in vulnerable communities.</dim:field>
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   <dim:field mdschema="dc" element="publisher">Massachusetts Institute of Technology</dim:field>
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   <dim:field mdschema="dc" element="title">Human Code Exchange (HCX) : A Community-Value-Driven Framework for Data Governance in Humanitarian Crises</dim:field>
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   	&lt;Title>Human Code Exchange (HCX) : A Community-Value-Driven Framework for Data Governance in Humanitarian Crises&lt;/Title>
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   	&lt;PublicationDate>2023-09&lt;/PublicationDate>
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        	&lt;DisplayName>Vibbi, Leonard Francis&lt;/DisplayName>
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   	&lt;Abstract>In this study, we examine data collection methods utilized in local communities during humanitarian crises, with a focus on the Sierra Leone COVID-19 scenario. We assess how widely-used data ethics principles in humanitarian data initiatives align with community values. We define these values as encompassing shared principles, virtues, and a collective understanding of what holds significance and meaning to affected communities[1].  &#xd;
&#xd;
Interviews conducted in Freetown communities allowed us to identify common themes across community principles and norms [values] toward data collection activities. Identified principles held by communities were subsequently contrasted with how data collection activities guided by established data ethics guidelines in humanitarian settings were carried out in target communities.&#xd;
&#xd;
Our findings commend the general adherence to ethical benchmarks, yet spotlight notable gaps that call for strategies more attuned to community shared principles and understanding. To address this, we present the &amp;quot;Human Code Exchange&amp;quot; (HCX) ethical data governance framework. HCX promotes participatory data collection, weaving in community values and experiences, thereby ensuring a balanced exchange between data collection activities and the community, and reducing practices that are not in tune with community values. With its core focus on the community, HCX aligns humanitarian data initiatives with the intrinsic values of communities, particularly in the regions of the global south. Our work lays the foundation for a refined data governance framework that places emphasis on ethical data collection in vulnerable communities.&lt;/Abstract>
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