<codeBook xmlns="ddi:codebook:2_5" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="ddi:codebook:2_5 https://ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/codebook.xsd" version="2.5"><docDscr><citation><titlStmt><titl>Global digital tool review for agroecological transitions</titl><IDNo agency="DOI">doi:10.7910/DVN/HNBKJG</IDNo></titlStmt><distStmt><distrbtr source="archive">Harvard Dataverse</distrbtr><distDate>2022-11-10</distDate></distStmt><verStmt source="archive"><version date="2023-03-09" type="RELEASED">2</version></verStmt><biblCit>Kyle M. Dittmer; Sadie Shelton; Sessie Burns; Eva (Lini) Wollenberg, 2022, "Global digital tool review for agroecological transitions", https://doi.org/10.7910/DVN/HNBKJG, Harvard Dataverse, V2</biblCit></citation></docDscr><stdyDscr><citation><titlStmt><titl>Global digital tool review for agroecological transitions</titl><IDNo agency="DOI">doi:10.7910/DVN/HNBKJG</IDNo></titlStmt><rspStmt><AuthEnty affiliation="International Center for Tropical Agriculture - CIAT">Kyle M. Dittmer</AuthEnty><AuthEnty affiliation="International Center for Tropical Agriculture - CIAT">Sadie Shelton</AuthEnty><AuthEnty affiliation="International Center for Tropical Agriculture - CIAT">Sessie Burns</AuthEnty><AuthEnty affiliation="International Center for Tropical Agriculture - CIAT">Eva (Lini) Wollenberg</AuthEnty></rspStmt><prodStmt><producer affiliation="The Alliance of Bioversity International and CIAT">Alliance of Bioversity International and CIAT</producer><prodDate>2022</prodDate><grantNo agency="European Commission (funded), IFAD (managed by)">2000003773</grantNo></prodStmt><distStmt><distrbtr source="archive">Harvard Dataverse</distrbtr><distrbtr affiliation="The Alliance of Bioversity International and CIAT" URI="https://alliancebioversityciat.org/">Alliance of Bioversity International and CIAT</distrbtr><contact affiliation="Alliance of Bioversity International and CIAT" email="alliance-dm@cgiar.org">Alliance Data Management</contact><depositr>Alliance Data Management</depositr><depDate>2022-11-04</depDate></distStmt><holdings URI="https://doi.org/10.7910/DVN/HNBKJG"/></citation><stdyInfo><subject><keyword xml:lang="en">Agricultural Sciences</keyword><keyword xml:lang="en">Earth and Environmental Sciences</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_1666">climate change</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_95276007">digital extension tools</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_203">agriculture</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_92381">agroecology</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_2805">farmers</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_d820537f">social inclusion</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_1374571087594">climate change mitigation</keyword><keyword vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_b2862a74">performance assessment</keyword><keyword vocab="Research Region">Asia</keyword><keyword vocab="Research Region">Latin America and the Caribbean</keyword><keyword vocab="Research Lever">Multifunctional Landscapes</keyword><topcClas vocab="AGROVOC" vocabURI="http://aims.fao.org/aos/agrovoc/c_1374567058134">climate change adaptation</topcClas></subject><abstract date="2022-11">This document contains a review of global digital resources relevant to climate-informed agroecological transitions. The purpose of the review was to catalog relevant digital resources and assess their role in inclusive knowledge development, with special attention to farmers’ co-creation of knowledge for on-the-ground practices. To this end, we identified existing digital tools relevant to technical advisory and performance assessment and reviewed their functions (i.e., the purpose of using a tool) against indicators for exemplary features (i.e., the channels in which a user can engage with the tool) that could support socially inclusive, climate-informed agroecological transitions.&lt;br>&lt;br> Metodology:To evaluate exemplary features of agricultural digital tools – defined here as an app, online resource (not platforms), or other software available on a digital device (e.g., phone, smartphone, computer, etc.), including those that are language, audio, and visually based – we developed 87 indicators (see Indicators Explained) relating to seven categories: (i) performance assessment,  (ii) technological specifications,  (iii) social inclusion and co-creation,  (iv) scaling,  (v) climate change adaptation, mitigation and whether the tool calculates greenhouse gas emissions, and  (vi) agroecological principles   Exemplariness was defined in this review as best fitting the requirements of the target users and best addressing agroecological and climate change mitigation and/or adaption outcomes. All indicators for categories i-v were developed and validated via several rounds of internal reviews and expert consultations. The 12 agroecological indicators (i.e., principles) were adopted and refined from the FAO 10 Elements of Agroecology (FAO, 2018), HLPE (HLPE, 2019) and TAPE (FAO, 2019) reports.    Sixty (60) tools were selected for a full review against the 87 indicators based on their applicability to provide technical advisory and/or performance assessment on climate-informed agroecological transitions. Tools were classified as technical advisory resources if they delivered any recommendations regarding farming practices and as performance assessment resources if they included review of farm status or operations. Tools were mostly identified via Google searches, expert interviews, and platforms such as the CGIAR Evidence Clearing House and Digital Agri Hub. Each tool was reviewed by one analyst by accessing the tool, when available, or by reviewing materials online. A second analyst validated individual indicator responses when subjectivity in responses was an issue. Indicators were marked as ‘unknown’ when subjectivity in responses persisted or when information was not available.</abstract><sumDscr><timePrd cycle="P1" event="start" date="2022-02">2022-02</timePrd><timePrd cycle="P1" event="end" date="2022-10">2022-10</timePrd><collDate cycle="P1" event="start" date="2022-02">2022-02</collDate><collDate cycle="P1" event="end" date="2022-10">2022-10</collDate><dataKind>Qualitative Data</dataKind><dataKind>Survey Data</dataKind><dataKind>Climate Data</dataKind></sumDscr></stdyInfo><method><dataColl><sources/></dataColl><anlyInfo/></method><dataAccs><setAvail/><useStmt/><notes type="DVN:TOU" level="dv">&lt;a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank">&lt;img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" />&lt;/a>&lt;br /></notes></dataAccs><othrStdyMat/></stdyDscr><otherMat ID="f6801194" URI="https://dataverse.harvard.edu/api/access/datafile/6801194" level="datafile"><labl>01. 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