Report: Exploring CGIAR Level Agricultural Results Interoperable System Architecture (CLARISA) 31 March 2022 Héctor Tobón Valentina De Col Margarita Ramírez Enrico Bonaiuti David Abreu Exploring CGIAR Level Agricultural Results Interoperable System Architecture (CLARISA) Report CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) Héctor Tobón Valentina De Col Margarita Ramírez Enrico Bonaiuti David Abreu To cite this report Tobón H, De Col V, Ramírez M, Bonaiuti E, Abreu D. 2022. Exploring CGIAR Level Agricultural Results Interoperable System Architecture (CLARISA). CCAFS Report. Wageningen, the Netherlands: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). About CCAFS reports Titles in this series aim to disseminate interim climate change, agriculture and food security research and practices and stimulate feedback from the scientific community. About CCAFS The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) is led by the International Center for Tropical Agriculture (CIAT), part of the Alliance of Bioversity International and CIAT, and carried out with support from the CGIAR Trust Fund and through bilateral funding agreements. For more information, please visit https://ccafs.cgiar.org/donors. Contact us CCAFS Program Management Unit, Wageningen University & Research, Lumen building, Droevendaalsesteeg 3a, 6708 PB Wageningen, the Netherlands. Email: ccafs@cgiar.org Disclaimer: This report has not been peer reviewed. Any opinions stated herein are those of the author(s) and do not necessarily reflect the policies or opinions of CCAFS, donor agencies, or partners. All images remain the sole property of their source and may not be used for any purpose without written permission of the source. This report is licensed under a Creative Commons Attribution – NonCommercial 4.0 International License. © 2022 CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Abstract CLARISA (https://clarisa.cgiar.org/) is the CGIAR Level Agricultural Results Interoperable System Architecture, a web service that helps collect and transform raw data of CGIAR research and activities into standardised and aggregated information. CLARISA is pivotal in supporting interoperability by enabling Management Information Systems (MISes) such as MARLO (Managing Agricultural Research for Learning and Outcomes), MEL (Monitoring, Evaluation and Learning), and Centre specific systems (e.g., CIAT-MARLO) to communicate with each other in the language needed for the CGIAR system-level reporting. This allows CGIAR to communicate with external partners in a clear, accountable, and transparent way. CLARISA represents an essential step of business intelligence towards enabling more effective strategic and operational decision-making. It is equipped with features to inform plans of work and budget and to appraise research progress and global goals for development. Additional enhancements and integration between program and knowledge management aspects could lead to enhanced quality and completeness of monitoring and reporting processes and harmonisation of reporting standards at the CGIAR system level. Keywords: CGIAR; MARLO; MEL; Management Information Systems; Interoperability; Controlled Lists; Results Dashboard. i About the authors Hector Tobon is the Innovations and Business Development Manager at the Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT). Valentina De Col is an Agricultural Information System Officer at the International Center for Agricultural Research in the Dry Areas (ICARDA). Margarita Ramirez is an Information Officer at the Alliance of Bioversity International and CIAT. Enrico Bonaiuti is the Research Team Leader of the Monitoring Evaluation and Learning at ICARDA and Program Management Officer at the International Potato Center (CIP). David Abreu is the Director of Technology Integration at the Alliance of Bioversity International and CIAT. ii Acknowledgements This work was implemented as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and performed in close collaboration with the Research Program on Root, Tubers and Bananas (RTB). The work was carried out with support from CGIAR Trust Fund and through bilateral funding agreements with the CGIAR Systems Office. For details please visit https://ccafs.cgiar.org/donors. The views expressed in this document cannot be taken to reflect the official opinions of these organisations. CLARISA was made possible thanks to the collaborative work of different CGIAR institutions and the valuable contribution of many people who have supported the project throughout different steps.  For conceptualising CLARISA in 2018: Bas Bouman, Claudio Proietti, Edouard Combey, Marco van den Berg, Philippe Ellul, Tania Jordan, Tonya Schuetz.  For guidance and financial support: CGIAR System Management Office (SMO).  For building a solid IT infrastructure around CLARISA: The IT Networks Infrastructure & Security team at the Alliance of Bioversity International and CIAT.  For designing the process of the internal rules that regulate the CLARISA’s institutions’ list: Amanda Wyatt, Emma Greatrix, Pascale Sabbagh.  For developing different features and aspects in CLARISA: Christian García, Andrés Valencia, Hermes Jimenez, Sebastian Amariles, Ana María Pantoja, Manuel Almanzar, Diego Perez, German Martinez, Felipe Elvira, Moayad Al-Najdawi, Anthony Shikali, Juan Sebastián Ortega, Valentina Viveros.  For the work integrating CLARISA: The MEL Team at ICARDA and CIP. The authors wish to thank Alison Rose, Science Officer at CCAFS, for the critical review of the text. CCAFS, led by the Alliance of Bioversity International and CIAT, brings together some of the world’s best researchers in agricultural science, development research, climate science and iii Earth system science, to identify and address the most important interactions, synergies and trade-offs between climate change, agriculture and food security. www.ccafs.cgiar.org iv Contents Abstract ................................................................................................................................. i About the authors ................................................................................................................. ii Acknowledgements .............................................................................................................. iii Contents ............................................................................................................................... v Acronyms .............................................................................................................................. 1 Introduction .......................................................................................................................... 2 What is CLARISA? .............................................................................................................. 2 Background ....................................................................................................................... 2 How does CLARISA work?.................................................................................................. 3 Why is CLARISA important? ............................................................................................... 4 Overview of CLARISA’s services ......................................................................................... 5 Discussion ............................................................................................................................. 7 Overview of CGIAR indicators collected in CLARISA ........................................................... 7 CLARISA’s Institutions’ List ................................................................................................ 7 Rules for including new institutions in CLARISA ................................................................. 9 CLARISA examples of use: Quality Assurance (QA), CGIAR Innovations, and Alliance Results Dashboard ...................................................................................................................... 11 Conclusion and recommendations ...................................................................................... 13 References .......................................................................................................................... 16 v Acronyms A4NH CGIAR Research Program on Agriculture for Nutrition and Health API Application programming interface Big Data CGIAR Research Program for Big Data in Agriculture CCAFS CGIAR Research Program on Climate Changes, Agriculture and Food Security CIAT International Center for Tropical Agriculture CIP International Potato Center CLARISA CGIAR Level Agricultural Results Interoperable System Architecture CRP CGIAR Research Program EiB Excellence in Agronomy EiB Excellence in breeding Fish CGIAR Research Program on Fish FTA CGIAR Research Program on Forests, Trees and Agroforestry Gender CGIAR Gender Platform Genebank CGIAR Genebank Platform GLDC CGIAR Research Program on Grain Legumes and Dryland Cereals ICARDA International Center for Agricultural Research in the Dry Areas Livestock CGIAR Research Program on Livestock Maize CGIAR Research Program on Maize MARLO Managing Agricultural Research for Learning and Outcomes MEL Monitoring, evaluation and learning MELIA Monitoring, evaluation, learning, and impact assessment MIS Management information system M-QAP Monitoring, evaluation and learning quality assurance processor PIM CGIAR Research Program on Policy, Institutions and Markets QA Quality assurance Rice CGIAR Research Program on Rice RTB CGIAR Research Program on Roots, Tubers and Bananas SDG Sustainable Development Goal SMO CGIAR System Management Organization SRF CGIAR Strategy and Results Framework Wheat CGIAR Research Program on Wheat WLE CGIAR Research Program on Water, Land and Ecosystem 1 Introduction What is CLARISA? CLARISA (https://clarisa.cgiar.org/) is the CGIAR Level Agricultural Results Interoperable System Architecture. This web service helps collect and transform the raw data of CGIAR research and activities into standardised and aggregated information. This is possible as CLARISA represents the reference of interoperability principles and coding systems for other Management Information Systems (MISes). By providing control lists with codes (e.i., unique identifiers), data on common indicators can be seamlessly gathered from the systems adopting these codes and results compiled at a system-wide level, including through dashboards. Thanks to this principle and its architecture, CLARISA unifies the language across different platforms, overcoming the common challenge of non-standardised information. Ultimately, this increases efficiency across CGIAR and allows gathering data on research performances to inform decisions and investment in agriculture. CLARISA is managed by the Innovations and Business Development team at Alliance of Bioversity International and CIAT with the support of the CGIAR System Management Organization (SMO), the International Center for Agricultural Research in the Dry Areas (ICARDA), and the International Potato Center (CIP). Background Across the CGIAR System, different methods and platforms are used to report research results and their impacts. Among them, the main MISes are MARLO (Managing Agricultural Research for Learning and Outcomes, https://marlo.cgiar.org/) and MEL (Monitoring, Evaluation and Learning, https://mel.cgiar.org/). CLARISA was conceptualised in 2018 by the Interoperability group from the MEL Community of Practice with the main idea of enabling interoperability, which means supporting the MISes to communicate and exchange data and information using the same coding standards. 2 (Fig. 1). In this way, data is harmonised from across the CGIAR and several other systems, producing standardised and aggregated information needed for CGIAR system-level reporting. Figure 1. Interoperability between CLARISA, MISes such as MARLO, MEL, and other platforms. Source: modified from CLARISA website (https://clarisa.cgiar.org/). How does CLARISA work? In programming terms, CLARISA is based on a REST-API: REST is an architectural style whose acronym stands for Representational State Transfer, whereas API is the Application Programming Interface. This configuration is a type of web service that enables computer systems to work together over the Internet. CLARISA uses control lists of standardised key terms, such as countries and regions, acronyms, institutions, budget types, Sustainable Development Goals (SDGs), and CGIAR technical language. This guarantees that data and information between MISes and other platforms are use the same language. 3 Why is CLARISA important? CLARISA represents an essential step towards business intelligence and a more effective strategic and operational decision-making. Thanks to CLARISA, CGIAR can gather all the research results at the system-wide level, monitor status and achievements, and highlight the collective impact in research for development. Since 2019, CLARISA has supported the CGIAR Quality Assurance (QA) process and collected all data and information sent from MARLO and MEL by the CGIAR Research Programs (CRPs) and Platforms during the annual reporting process. This has allowed the SMO to access the CGIAR common reporting indicators in one single place and obtain data in the same format, despite being compiled in two different systems (i.e., MARLO and MEL). The aggregated and quality-assured data collected to date can be visualised in the CGIAR Results Dashboard (https://www.cgiar.org/food-security-impact/results-dashboard/), an interactive dashboard that displays key indicators of CRPs and Platforms and shows impacts, achievements, and progress toward meeting the targets of the CGIAR Strategy and Results Framework (SRF) and the SDGs (Fig. 2). Figure 2. Data flow from MISes and CLARISA to the CGIAR Results Dashboard. Source: modified from CLARISA Factsheet (Ellul et al., 2020). 4 Overview of CLARISA’s services  Annual Report Control Lists (https://clarisa.cgiar.org/swagger/api.html): CLARISA provides standards in the form of control lists that can be used across MISes in CGIAR to enable interoperability. It also includes the indicators defined in the former Research Strategy and SRF 2016-2030 (CGIAR Consortium Office, 2015) and the Performance Results Management Framework of One CGIAR (CGIAR System Organization, 2021) currently being updated.  One CGIAR General Control Lists (https://clarisa.cgiar.org/swagger/generalListReference.html): CLARISA allows CGIAR and third-party applications to use integrated data (control lists) among centres, partners, and other entities. One CGIAR General Control Lists contain: o The General Control List identified by the MISes during the annual reporting process, which can also be used to standardise and provide interoperability across any other CGIAR platforms. o The list of Institutions related to CGIAR activities, e.g., funders, leaders, partners, contributors. The list of institutions is controlled and vetted through a systemic process to maintain updated control lists, and requests to add new institutions are validated following MARLO platform’s rules.  Additional Services (https://clarisa.cgiar.org/swagger/additionalServices.html): CLARISA shares services with strategic partners who collaborate and expose their tools for the CGIAR Community. These includes: o An internal workflow to keep reviewed and standardised list of Institutions related to CGIAR research activities, e.g., funders, leaders, partners, contributors, collaborators. The interface also has a search function so that users can search the identifier of a specific institution at any time and/or request the addition of a new institution not on the list. o The M-QAP (Monitoring, Evaluation, and Learning Quality Assurance Processor), https://clarisa.cgiar.org/swagger/additionalServices.html#section2), a 5 publications’ metadata extractor that employs APIs from Web of Science™ (https://clarivate.com/), Scopus (https://dev.elsevier.com/), Unpaywall (https://unpaywall.org/), Altmetric (https://www.altmetric.com/), and F.A.I.R (Findable, Accessible, Interoperable, and Reusable) metric from GARDIAN (https://gardian.bigdata.cgiar.org/metrics.php#!/). The tool is designed to support CGIAR results reporting, including the CGIAR Results Dashboard, and ensure that publications with a Digital Object Identifier (DOI) are validated against the databases mentioned above. Additionally, the tool matches institution names with CGIAR lists and provides a facility to request for new institutions to be added to the institution’s list using CLARISA API. o Online chat support: Users can contact and interact with the CLARISA team through live chat. o Data table visualisation and download feature in Microsoft Excel format: all control lists can be accessed online and downloaded at any time. 6 Discussion Overview of CGIAR indicators collected in CLARISA Since its inception in 2019, CLARISA has gathered data from 11 CGIAR CRPs and Platforms on CGIAR key indicators such as MELIA (Monitoring, Evaluation, Learning, and Impact Assessment) studies, policies, innovations, peer-reviewed papers, OICR (Outcome Impact Case Report). As of December 2021, CLARISA contained a list of 6,353 institutions from 167 different countries across the world (Fig. 3). Figure 3. Number of records collected in CLARISA as of December 2021, based on the information for each CGIAR Indicators reported in the 2020 Annual Reports. Source: CLARISA website (https://clarisa.cgiar.org/). CLARISA’s Institutions’ List As part of the process of harmonising the information, CLARISA’s control list of institutions represents one of the most challenging tasks both for managing the significant number of institutions recorded and for the procedure of review and approval of new entities. In 2021, CLARISA received an average of 180 requests per month from different users (Fig. 4). The process of vetting new institutions requires a team effort to apply the rules developed since CLARISA’s inception (Almanzar et al., 2021). During this process, the team must undertake a case-by-case assessment to evaluate if the suggested new institution is legally 7 constituted and if complies with the internal rules before being accepted as part of the list. As shown from the statistics presented in figure 4, half of the submitted requests from other systems were rejected. This rejection is mainly due to the high number of requests to include institutions already on the list or not legal entities (e.g., groups of people, teams or sub- departments of an institution). Therefore, reviewing new requests is a substantial effort of time and human resources. Institutions’ requests can be followed in real-time through CLARISA´s dashboard: https://app.powerbi.com/view?r=eyJrIjoiMDY4YWMyNDQtYmViMy00YTlhLWE1ODYtMTlhYjI 2MjlmYTYyIiwidCI6IjZhZmEwZTAwLWZhMTQtNDBiNy04YTJlLTIyYTdmOGMzNTdkNSIsImMiOj h9&pageName=ReportSection. A group from MARLO, composed of the CRPs on Agriculture for Nutrition and Health (A4NH), Policy, Institutions and Markets (PIM) and on Water, Land and Ecosystem (WLE) representatives closely collaborating with MARLO Development team, designed the internal rules regulating CLARISA’s Institutions’ List. The rules are presented in the following paragraph. 8 Figure 4. Dashboard showing different statistics on the requests for new institutions in CLARISA. Figures are from December 10, 2021. Source: CLARISA Institution's dashboard (https://app.powerbi.com/view?r=eyJrIjoiMDY4YWMyNDQtYmViMy00YTlhLWE1ODYtMTlhYjI2MjlmYT YyIiwidCI6IjZhZmEwZTAwLWZhMTQtNDBiNy04YTJlLTIyYTdmOGMzNTdkNSIsImMiOjh9&pageName=R eportSection). Rules for including new institutions in CLARISA Below are the rules for including new institutions in CLARISA as from Almanzar et al. (2021).  The institution should be a legal entity. For example, ‘Earth Institute’ is not a legal entity, but it could be listed as ‘Columbia University’. CCAFS is not a legal entity but could be listed as CIAT.  Government entities that comprise any Ministry/Department/Agency at the national, state, or local level, including parliamentary bodies. The institution should be added 9 to the list at its highest level so, for instance, groups within the Ministry/Department of Agriculture should not be added to the list. If a user submits a sub-department within a Ministry, the top-level Ministry should be listed instead. The institution should be added to the list with the country included in the title, e.g., ‘Ministry of Agriculture and Forests (Bhutan)’.  Institutions should be listed in their official language, provided this is English, French, German, Portuguese, Italian, or Spanish. E.g., ‘Centro Internacional de Agricultura Tropical’ and not ‘International Center for Tropical Agriculture’. All other entries should be in English, although titles in other official languages may (optional) be included in addition to English, e.g., ‘Department of Agriculture/Jabatan pertanian (Malaysia)’.  All international, regional, national, or local non-governmental organisations (NGOs) should be listed only once and by their headquarters. E.g., if a user requests ‘Oxfam- Kenya’, the organisation should be added to the list as ‘Oxfam’. When a user selects ‘Oxfam’ from the dropdown list in MARLO, she/he/they can specify the country office from the available options.  Bilateral development agencies that include aid or development agencies receiving funding from the government in their home countries should be classified as bilateral development agencies instead of government. E.g., United States Agency for International Development (USAID), Department for International Development (DFID).  Development banks (e.g., World Bank or Asian Development Bank) and multilateral financing institutions (e.g., Global Environment Facility) should be classified as international/regional financial institutions.  Any international or regional institution carrying CGIAR research regardless of its funding source (public or private, including think tanks and research consulting firms) should be classified as an international/regional research institution. CGIAR Centers or academic institutions do not belong in this category. 10  Any national or local institution carrying CGIAR research, regardless of its funding source (public or private), should be classified as a national/local research institution. Academic institutions do not belong in this category.  United Nations (UN) entities should be classified as international organisations. CLARISA examples of use: Quality Assurance (QA), CGIAR Innovations, and Alliance Results Dashboard Quality Assurance (QA) Since 2019, CLARISA has hosted the CGIAR QA process. During this time, CRPs and Platforms submit data on eight reported indicators1 through MARLO and MEL to CLARISA and quality assessors and focal points from CRPs and Platforms become active CLARISA’s service users. In 2021, CLARISA’s functionalities were further improved, including the addition of the M-QAP tool that supports the QA of peer-reviewed papers. For the 2020 QA, CLARISA received a total of 2,577 peer-reviewed publications from 16 different CRPs and Platforms and processed 97.4% of them through the M-QAP. This new functionality has allowed a reliable, accurate, and automatised validation of metadata according to CGIAR SMO guidelines. Compared to a manual check, it has saved approximately 40 days of work and provided a rapid, reproducible, time- and resource-saving solution for the CGIAR QA process of scientific publications (De Col et al., 2021a; De Col et al., 2021b). CGIAR Innovations In 2021, CLARISA provided the reference for standardised descriptor specifications for RTB’s Innovation Catalog (Sartas et al., 2021), which documents RTB innovations in an easily accessible and understandable way. Among these descriptors are institutions, countries, SDGs. 1 Contributions to System-Level Outcomes (SLOs) targets, policies, OICR, innovations, milestones, capacity development, MELIA, and peer-reviewed papers. 11 Alliance Results Dashboard Since the conception of the Alliance of Bioversity International and CIAT Strategy 2020-2025 (Alliance of Bioversity International and CIAT, 2019), a need emerged for specific mechanisms that would allow the aggregation in a centralised place of results evidence from the research units of both centers. At the same time, there was a request for a system that would allow the merging of information from the Alliance’s Enterprise Resource Planning (ERP) Agresso. At the beginning of 2021, a close collaboration between the Performance, Innovation and Strategic Analysis for Impact (PISA4Impact) unit and the Alliance Technology Integration department developed a Business Intelligence Module. This module was intended to change CLARISA's data and transform it into meaningful and usable information to enable more effective strategic and operational decision-making. The first release of the dashboard was completed for the Alliance Staff on December 6, 2021, and a public dashboard is currently showing on the Alliance’s website (Fig. 5). Figure 5. Alliance Results Dashboard. Source: Alliance website (https://alliancebioversityciat.org/impact/results-dashboard). 12 Conclusion and recommendations CLARISA web service has proved crucial for setting a common ground and a unified language for the communication and data exchange across CGIAR MISes and beyond. This aspect is essential in the context of CGIAR, in which management operation and decision-making are data- and information-driven. The core strength of CLARISA architecture of receiving, collecting, exchanging, aggregating, and disaggregating standardised data on research outputs has been proven beneficial since its inception and it can provide a solid starting point for One CGIAR. In CLARISA, the centralised lists, including a curated and managed institutions list and established rules, allow several data processes such as the controlled data submission to run smoothly, ensure efficiency in data harmonisation, and, as a result, to collate high quality cleaned data. Moreover:  CLARISA has already been adopted by different CGIAR MISes and CGIAR processes. MARLO, MEL, and CIAT-MARLO have already adopted CLARISA and used it, for instance, for the QA process, including the automated assessment of peer-reviewed papers through the M-QAP. Moreover, the process to add, review, and reject institutions is in place, and the institutions’ submission has been already tested and used by CRP users for the 2017-2022 portfolio. More tools and features are being implemented in the MISes to transition to One CGIAR.  Usability and a user-friendly interface are significant features of CLARISA. The system is simple and easy to use by web developers, data specialists, and CGIAR users who have already familiarised themselves with the process on adding institutions and carrying out data quality assurance processes.  CLARISA is a CGIAR in-house built tool, and therefore it offers flexibility, already capacitated staff, timely reaction time, efficiency, and a fully operational system. 13  CLARISA is flexible in overhauls since identifiers in the control lists can be maintained in case of changes and enhancements. Below are some of the recommendations that have emerged from this report. 1. Key data sets, such as results, plan of work and budget, grants, finance, innovation stage-gating2, could be increasingly linked through CLARISA to strengthen centralised management, collection of results, and performance assessment. 2. Enhanced interoperability between MISes, CLARISA, and knowledge management platforms and services (e.g., CGSpace, https://cgspace.cgiar.org/; MELSpace, https://repo.mel.cgiar.org/; Dataverse https://dataverse.org/; Altmetric, https://www.altmetric.com/; Food and Agriculture Organization (FAO) AGROVOC, https://www.fao.org/agrovoc/) could further lead to efficiency gains, including enhanced quality and completeness of reporting and monitoring processes and harmonisation of reporting standards at the CGIAR system-level (CGIAR Research Program on Roots, Tubers and Bananas, 2020). 3. The tool is potentially scalable within and outside CGIAR. CLARISA has been developed for a few years now and is currently being adopted mainly for performance management within CGIAR. Still, there is an excellent opportunity for research and corporate applications within and outside CGIAR (e.g., clients) to adopt and benefit from it. New functionalities and other control lists can improve the tool. These include further applications, such as integrations with Enterprise Resource Planning (ERP), Human Resources (HR) and Finance systems, Resource Mobilization Customer Relationship Management (CRMs), research applications, innovations, that could connect with CLARISA’s lists. 4. CLARISA can benefit from a more robust and improved governance mechanism and increased shared ownership by the data owners, clients, and stakeholders to minimise duplication of efforts. 2 Stage-gating is a framework that recognises that innovations go through stages, from an initial idea to the final product, technology, or service. 14 5. CLARISA can improve by formalising its stakeholders' engagement, clarifying use cases, identifying users’ needs, and agreeing on prioritisation mechanisms. 15 References  Alliance of Bioversity International and CIAT (2019). An Alliance for Accelerated Change: Food system solutions at the nexus of agriculture, environment, and nutrition - Strategy 2020–2025. Alliance of Bioversity International and CIAT. https://hdl.handle.net/10568/106098  Almanzar M., Tobón H., Perez D. (2021). CLARISA Institution request protocol. https://hdl.handle.net/10568/117370  CGIAR Consortium Office (2015). CGIAR Strategy and Results Framework 2016-2030. https://hdl.handle.net/10947/3865  CGIAR Research Program on Roots, Tubers and Bananas (2020). CGIAR Research Program on Roots, Tubers and Bananas 2019 Annual Report. https://hdl.handle.net/10568/108931  CGIAR System Organization (2021). CGIAR 2030 Research and Innovation Strategy: Transforming food, land, and water systems in a climate crisis. 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International Potato Center. https://doi.org/10.4160/9789290606079 17