Presented by Beliyou Haile (IFPRI), Arkadeep Bandyopadhyay (IFPRI) and Carlo Azzarri (IFPRI) at the Africa RISING Program Learning Event, Lilongwe, Malawi, 5-8 February 2019
Use of monitoring data for evidence-based decision making: A factor analysisIRC
Presentation given by Marieke Adank during the IRC Symposium All Systems Go! on 14 March 2019. This session was organised by Heather Skilling (DAI), in collaboration with Brain Banks (GETF), Nick Dickinson (WAHSNote) and Marieke Adank (IRC).
The document summarizes the development and enhancement of the CAAC program in the Inter-Agency Child Protection Information Management System and the Action Plan Information Program from January 16th to March 15th. Key tasks included discussing requirements with UNICEF, collecting and validating data, designing new database structures and forms, developing and coding the programs, and generating reports. The programs were then demonstrated to UNICEF and the systems were handed over after incorporating feedback.
This document outlines the ONS's data collection transformation programme to modernize how it collects and uses data. It plans to move more surveys online, integrate administrative and alternative data sources, modernize its IT systems, redesign some surveys, and review its field operations model. These changes aim to produce higher quality statistics at reduced cost while reducing respondent burden. Moving more collection online, combining multiple data sources, and transitioning to common platforms and services could generate cost savings while making statistics more relevant and timely. Legislation may need to change to access some key administrative datasets. The goal is a future state with most collection online unless sensible to do otherwise, supported by integrated data and systems.
Status of ICT structure, infrastructure and applications existed to manage an...RABNENA Network
Status of ICT structure, infrastructure and applications existed to manage and disseminate information and knowledge of Agricultural Biotechnology Innovations in Jordan
This document discusses data-driven storytelling and the process of finding and applying data in news reports and features. It begins by defining data-driven journalism as a process that uses analysis and filtering of large datasets to create or elevate news stories. It then outlines the typical process, which involves finding relevant data, cleaning and filtering the data, visualizing it, and then publishing the story. The document provides examples of different types and levels of data-driven storytelling. It also discusses specific sources of agricultural data and tools that can be used for data analysis, visualization and story publication. Finally, it emphasizes that effective data-driven storytelling involves humanizing the data by including real-life stories and perspectives of stakeholders.
The document summarizes the progress and plans of the UK Office for National Statistics' (ONS) Administrative Data Census Project. The project aims to replace the traditional census with population statistics derived from administrative data by 2021. So far, the project has had success producing population estimates from linked health and tax records. However, fully replacing the census will require improved access to additional administrative data, better data linkage methods, and methods to produce a wider range of statistical outputs to meet user needs. The assessment concludes that while estimates of population size and numbers of households may be feasible by 2023, fully replacing the census with administrative data alone is unlikely due to limitations in available data and methods. Continued progress will depend on new legislation, engagement with
- All the data – whether or not categorized – present in servers of a company is collectively called BIG DATA.
- For Example, customer’s shopping history, web surfing history, Likes and Comments on Facebook, Tweets etc.
This document summarizes recent federal mandates requiring open access to publications and data resulting from federally funded scientific research. It discusses a 2013 White House memo requiring federal agencies spending over $100 million annually on research to develop public access plans. It also outlines policies from agencies like NIH, NSF, and NOAA requiring data management plans and sharing of published results and supporting data. Stakeholder responses to these mandates like the CHORUS publishing initiative and the SHARE academic consortium proposal are also summarized.
Use of monitoring data for evidence-based decision making: A factor analysisIRC
Presentation given by Marieke Adank during the IRC Symposium All Systems Go! on 14 March 2019. This session was organised by Heather Skilling (DAI), in collaboration with Brain Banks (GETF), Nick Dickinson (WAHSNote) and Marieke Adank (IRC).
The document summarizes the development and enhancement of the CAAC program in the Inter-Agency Child Protection Information Management System and the Action Plan Information Program from January 16th to March 15th. Key tasks included discussing requirements with UNICEF, collecting and validating data, designing new database structures and forms, developing and coding the programs, and generating reports. The programs were then demonstrated to UNICEF and the systems were handed over after incorporating feedback.
This document outlines the ONS's data collection transformation programme to modernize how it collects and uses data. It plans to move more surveys online, integrate administrative and alternative data sources, modernize its IT systems, redesign some surveys, and review its field operations model. These changes aim to produce higher quality statistics at reduced cost while reducing respondent burden. Moving more collection online, combining multiple data sources, and transitioning to common platforms and services could generate cost savings while making statistics more relevant and timely. Legislation may need to change to access some key administrative datasets. The goal is a future state with most collection online unless sensible to do otherwise, supported by integrated data and systems.
Status of ICT structure, infrastructure and applications existed to manage an...RABNENA Network
Status of ICT structure, infrastructure and applications existed to manage and disseminate information and knowledge of Agricultural Biotechnology Innovations in Jordan
This document discusses data-driven storytelling and the process of finding and applying data in news reports and features. It begins by defining data-driven journalism as a process that uses analysis and filtering of large datasets to create or elevate news stories. It then outlines the typical process, which involves finding relevant data, cleaning and filtering the data, visualizing it, and then publishing the story. The document provides examples of different types and levels of data-driven storytelling. It also discusses specific sources of agricultural data and tools that can be used for data analysis, visualization and story publication. Finally, it emphasizes that effective data-driven storytelling involves humanizing the data by including real-life stories and perspectives of stakeholders.
The document summarizes the progress and plans of the UK Office for National Statistics' (ONS) Administrative Data Census Project. The project aims to replace the traditional census with population statistics derived from administrative data by 2021. So far, the project has had success producing population estimates from linked health and tax records. However, fully replacing the census will require improved access to additional administrative data, better data linkage methods, and methods to produce a wider range of statistical outputs to meet user needs. The assessment concludes that while estimates of population size and numbers of households may be feasible by 2023, fully replacing the census with administrative data alone is unlikely due to limitations in available data and methods. Continued progress will depend on new legislation, engagement with
- All the data – whether or not categorized – present in servers of a company is collectively called BIG DATA.
- For Example, customer’s shopping history, web surfing history, Likes and Comments on Facebook, Tweets etc.
This document summarizes recent federal mandates requiring open access to publications and data resulting from federally funded scientific research. It discusses a 2013 White House memo requiring federal agencies spending over $100 million annually on research to develop public access plans. It also outlines policies from agencies like NIH, NSF, and NOAA requiring data management plans and sharing of published results and supporting data. Stakeholder responses to these mandates like the CHORUS publishing initiative and the SHARE academic consortium proposal are also summarized.
Monitoring, Evaluation, and Data Managementafrica-rising
Presented by Beliyou Haile and Carlo Azzarri, IFPRI, at the Africa RISING Ethiopian Highlands Project Review and Planning Meeting, Addis Ababa, 21–22 May 2019. Nairobi, Kenya: ILRI.
This deck of slides outlines the key aspects of the Open Data Readiness Assessment or ODRA and was presented in the consultative workshop on Rwanda Open Data Policy organized by the Ministry of Youth & ICT (GoR) and the World Bank.
1) PABRA operates in over 29 countries with over 350 partners and works to improve bean research, production and markets.
2) They developed several tools to better manage and share data between widespread partners including a database, an indicator tracking template, and most recently an online data collection tool.
3) The tools aimed to address problems with data access, sharing results, and updating information regularly from partners in different countries. The online tools especially aimed to make data entry and validation more efficient.
The document provides an overview of how to access AEDC data collections. It discusses the publicly available reports and resources on the AEDC website, including national reports, community profiles and school profiles. It also describes how unpublished or "bespoke" AEDC data can be accessed through submitting a request, including macrodata, microdata and data linkage files. Requests for unpublished data require approval and may have associated fees depending on the type of data and level of customization required.
The document discusses open data and its benefits. It outlines 5 levels or "stars" of open data, with 5 stars being the most open. Open government data can include transportation and financial data, helping cities and giving citizens visibility. A pilot open data project is proposed, starting with one UNDP dataset to understand features and stakeholder needs before a larger launch. The pilot would test an API or open data platform over 2-3 months to inform a full open data service.
This document summarizes a review of initiatives that collect data on agricultural public expenditures (AgPE) across countries. It finds that while there are many efforts, it was unclear how they relate and what gaps remain. The objective is to provide an overview of the different initiatives to identify complementarities, challenges, and how collaboration could be improved. It analyzes initiatives by geographic scope, sectors covered, and types of data. The review finds some depths like disaggregation are more limited and proposes strategic options like strengthening coordination, collaboration, data access, and analytical capacity to better track AgPE globally. Next steps include finalizing the report and convening discussions on implementing recommendations.
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...IFPRI Africa
This document summarizes a review of initiatives that compile data on agricultural public expenditures (AgPE) across multiple countries. It finds that while there are many efforts, it was unclear how they relate and where gaps remain. The objective is to provide an overview of the initiatives to identify complementarities, challenges, and how collaboration could improve coordination. It analyzes initiatives by geographic scope, sectors covered, and typology. The review recommends strengthening individual initiatives, interaction among them through communities of practice, and linking country-level and cross-country data and analytical efforts to support agricultural policymaking. Next steps include finalizing the report based on feedback and convening a follow-up meeting to discuss implementation.
Dimitris Skoutas presents the OpenDataMonitor
Workshop title: Open Science Monitor
Workshop overview:
Which are the measurable components of Open Science? How do we build a trustworthy, global open science monitor? This workshop will discuss a potential framework to measure Open Science, including the path from the publishing of an open policy (registries of policies and how these are represented or machine read), to the use of open methodologies, and the opening up of research results, their recording and measurement.
DAY 2 - PARALLEL SESSION 5
A call to librarians to use their library powers in the community beyond the walls of their institutions as the open data folks need their knowledge!
Title:
Open Sesame: Open Data, Data Liberation and New Opportunities for Libraries
Abstract:
Cities and data producers are quickly embracing Open Data, albeit unevenly. The Data Liberation Initiative (DLI) has been a pioneer in broadening access to data for nearly two decades. This session will examine the relevance of Data Liberation in terms of Open Data and explore how librarians can step up to the plate to make Open Data/Open Government as successful as DLI.
Speakers:
- Wendy Watkins, Data Librarian, Carleton University
- Ernie Boyko, Adjunct Data Librarian, Carleton University
- Tracey P. Lauriault, Post Doctoral Fellow, Carleton University (tlauriau@gmail.com)
- Margaret Haines, University Librarian, Carleton University
The challenges of implementing generic web and mobile apps for managing and m...Rob Worthington
Is it possible to create a generic mobile app to manage and monitor community scorecard activities? This presentation summarises research based on work in Mozambique.
The Innovator’s Journey: Asset Manager InsightsState Street
On behalf of State Street, Longitude conducted a global survey of senior executives at investment
organizations during October and November 2014. We asked them to self-assess their confidence and
progress across six data capabilities, including infrastructure, insight, adaptability, compliance, talent and
governance. The 400 respondents were drawn from 11 countries and included insurance companies,
private and public pension funds, fund-of-funds, foundations, central banks, endowments, sovereign
wealth funds and supranationals. Two hundred asset managers participated in the survey.
Data can come from internal or external sources. Internal sources include company reports and records, while external sources are outside the organization, like information obtained from other companies. There are various methods for collecting primary data, like interviews, surveys, observation, and experiments. Secondary data has already been previously collected and can come from internal sources within an organization or external sources outside the organization. Data can be structured, semi-structured, or unstructured, and varies in its level of organization and ability to be stored in a relational database. Key characteristics of good data include accuracy, validity, reliability, timeliness, completeness, availability, and accessibility.
This document provides information about developing a data management plan for grant proposals. It discusses the goals of the workshop which are to learn about data management planning, available resources, develop a draft plan, and receive feedback. It then covers what good data management involves, who requires data management plans, examples of requirements from agencies like NSF, and parts of a generic data management plan. Finally, it discusses resources available for creating plans like the DMPTool.
This document outlines an agenda and activities for a workshop on practical data management planning. The workshop will discuss challenges with data management, including data loss and how poor management affects all. Activities will guide participants in inventorying their data and developing storage and backup plans. The goal is to help researchers effectively manage their data over the long-term and address funder and legal requirements.
Agricultural R&D indicators monitoring investments and capacity development a...Hillary Hanson
This document summarizes the activities of the Agricultural Science and Technology Indicators (ASTI) initiative. It discusses ASTI's three main components: collecting data and indicators on agricultural R&D spending and capacity; conducting analytical work and diagnostics on agricultural research systems; and disseminating findings through outreach and advocacy. It also describes ASTI's current datasets, collection methods, country portfolio, and tools for accessing and visualizing data online, including new interactive features under development.
The document discusses conducting a Public Expenditure Tracking Survey (PETS) to assess the effectiveness and efficiency of agricultural public spending in Sub-Saharan Africa. A PETS examines how funds budgeted for key agricultural programs are delivered to intended beneficiaries. It involves tracking spending through administrative levels using surveys. The methodology can range from simple to complex depending on country context. Key steps include preparatory work, sampling, data collection and analysis, and reporting findings and recommendations to improve service delivery and spending effectiveness. The timeline for a PETS is typically 5 months but may be longer for more complex surveys.
The DMP Tool provides a centralized location for research data management planning templates based on funder requirements. It offers a CMS-like interface for collaboratively writing, updating, and sharing data management plans. The tool supports the data management planning process through its templates, examples, and information resources. It also has an API that allows other services to integrate its data. However, the DMP Tool itself does not store, share, review, or access research data.
Africa RISING project implementation and contribution in Ethiopia. Presented at Africa RISING close-out event.
24-25 January 2023
ILRI campus- Addis Ababa, Ethiopia
The document summarizes a field visit by Africa RISING CGIAR partners to sites in Ethiopia where they are implementing their new SI-MFS initiative. It describes some innovative farmers in the Lemo and Doyogena districts who have adopted integrated crop-livestock-NRM practices promoted by Africa RISING, including using protein-rich legume fodder trees, energy-rich grasses, and soil and water conservation practices. It also highlights the challenges of water shortage and disease, and the potential for the new SI-MFS initiative to build on the success stories and learning from Africa RISING farmers.
More Related Content
Similar to Monitoring, data management, and impact assessment in Africa RISING
Monitoring, Evaluation, and Data Managementafrica-rising
Presented by Beliyou Haile and Carlo Azzarri, IFPRI, at the Africa RISING Ethiopian Highlands Project Review and Planning Meeting, Addis Ababa, 21–22 May 2019. Nairobi, Kenya: ILRI.
This deck of slides outlines the key aspects of the Open Data Readiness Assessment or ODRA and was presented in the consultative workshop on Rwanda Open Data Policy organized by the Ministry of Youth & ICT (GoR) and the World Bank.
1) PABRA operates in over 29 countries with over 350 partners and works to improve bean research, production and markets.
2) They developed several tools to better manage and share data between widespread partners including a database, an indicator tracking template, and most recently an online data collection tool.
3) The tools aimed to address problems with data access, sharing results, and updating information regularly from partners in different countries. The online tools especially aimed to make data entry and validation more efficient.
The document provides an overview of how to access AEDC data collections. It discusses the publicly available reports and resources on the AEDC website, including national reports, community profiles and school profiles. It also describes how unpublished or "bespoke" AEDC data can be accessed through submitting a request, including macrodata, microdata and data linkage files. Requests for unpublished data require approval and may have associated fees depending on the type of data and level of customization required.
The document discusses open data and its benefits. It outlines 5 levels or "stars" of open data, with 5 stars being the most open. Open government data can include transportation and financial data, helping cities and giving citizens visibility. A pilot open data project is proposed, starting with one UNDP dataset to understand features and stakeholder needs before a larger launch. The pilot would test an API or open data platform over 2-3 months to inform a full open data service.
This document summarizes a review of initiatives that collect data on agricultural public expenditures (AgPE) across countries. It finds that while there are many efforts, it was unclear how they relate and what gaps remain. The objective is to provide an overview of the different initiatives to identify complementarities, challenges, and how collaboration could be improved. It analyzes initiatives by geographic scope, sectors covered, and types of data. The review finds some depths like disaggregation are more limited and proposes strategic options like strengthening coordination, collaboration, data access, and analytical capacity to better track AgPE globally. Next steps include finalizing the report and convening discussions on implementing recommendations.
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...IFPRI Africa
This document summarizes a review of initiatives that compile data on agricultural public expenditures (AgPE) across multiple countries. It finds that while there are many efforts, it was unclear how they relate and where gaps remain. The objective is to provide an overview of the initiatives to identify complementarities, challenges, and how collaboration could improve coordination. It analyzes initiatives by geographic scope, sectors covered, and typology. The review recommends strengthening individual initiatives, interaction among them through communities of practice, and linking country-level and cross-country data and analytical efforts to support agricultural policymaking. Next steps include finalizing the report based on feedback and convening a follow-up meeting to discuss implementation.
Dimitris Skoutas presents the OpenDataMonitor
Workshop title: Open Science Monitor
Workshop overview:
Which are the measurable components of Open Science? How do we build a trustworthy, global open science monitor? This workshop will discuss a potential framework to measure Open Science, including the path from the publishing of an open policy (registries of policies and how these are represented or machine read), to the use of open methodologies, and the opening up of research results, their recording and measurement.
DAY 2 - PARALLEL SESSION 5
A call to librarians to use their library powers in the community beyond the walls of their institutions as the open data folks need their knowledge!
Title:
Open Sesame: Open Data, Data Liberation and New Opportunities for Libraries
Abstract:
Cities and data producers are quickly embracing Open Data, albeit unevenly. The Data Liberation Initiative (DLI) has been a pioneer in broadening access to data for nearly two decades. This session will examine the relevance of Data Liberation in terms of Open Data and explore how librarians can step up to the plate to make Open Data/Open Government as successful as DLI.
Speakers:
- Wendy Watkins, Data Librarian, Carleton University
- Ernie Boyko, Adjunct Data Librarian, Carleton University
- Tracey P. Lauriault, Post Doctoral Fellow, Carleton University (tlauriau@gmail.com)
- Margaret Haines, University Librarian, Carleton University
The challenges of implementing generic web and mobile apps for managing and m...Rob Worthington
Is it possible to create a generic mobile app to manage and monitor community scorecard activities? This presentation summarises research based on work in Mozambique.
The Innovator’s Journey: Asset Manager InsightsState Street
On behalf of State Street, Longitude conducted a global survey of senior executives at investment
organizations during October and November 2014. We asked them to self-assess their confidence and
progress across six data capabilities, including infrastructure, insight, adaptability, compliance, talent and
governance. The 400 respondents were drawn from 11 countries and included insurance companies,
private and public pension funds, fund-of-funds, foundations, central banks, endowments, sovereign
wealth funds and supranationals. Two hundred asset managers participated in the survey.
Data can come from internal or external sources. Internal sources include company reports and records, while external sources are outside the organization, like information obtained from other companies. There are various methods for collecting primary data, like interviews, surveys, observation, and experiments. Secondary data has already been previously collected and can come from internal sources within an organization or external sources outside the organization. Data can be structured, semi-structured, or unstructured, and varies in its level of organization and ability to be stored in a relational database. Key characteristics of good data include accuracy, validity, reliability, timeliness, completeness, availability, and accessibility.
This document provides information about developing a data management plan for grant proposals. It discusses the goals of the workshop which are to learn about data management planning, available resources, develop a draft plan, and receive feedback. It then covers what good data management involves, who requires data management plans, examples of requirements from agencies like NSF, and parts of a generic data management plan. Finally, it discusses resources available for creating plans like the DMPTool.
This document outlines an agenda and activities for a workshop on practical data management planning. The workshop will discuss challenges with data management, including data loss and how poor management affects all. Activities will guide participants in inventorying their data and developing storage and backup plans. The goal is to help researchers effectively manage their data over the long-term and address funder and legal requirements.
Agricultural R&D indicators monitoring investments and capacity development a...Hillary Hanson
This document summarizes the activities of the Agricultural Science and Technology Indicators (ASTI) initiative. It discusses ASTI's three main components: collecting data and indicators on agricultural R&D spending and capacity; conducting analytical work and diagnostics on agricultural research systems; and disseminating findings through outreach and advocacy. It also describes ASTI's current datasets, collection methods, country portfolio, and tools for accessing and visualizing data online, including new interactive features under development.
The document discusses conducting a Public Expenditure Tracking Survey (PETS) to assess the effectiveness and efficiency of agricultural public spending in Sub-Saharan Africa. A PETS examines how funds budgeted for key agricultural programs are delivered to intended beneficiaries. It involves tracking spending through administrative levels using surveys. The methodology can range from simple to complex depending on country context. Key steps include preparatory work, sampling, data collection and analysis, and reporting findings and recommendations to improve service delivery and spending effectiveness. The timeline for a PETS is typically 5 months but may be longer for more complex surveys.
The DMP Tool provides a centralized location for research data management planning templates based on funder requirements. It offers a CMS-like interface for collaboratively writing, updating, and sharing data management plans. The tool supports the data management planning process through its templates, examples, and information resources. It also has an API that allows other services to integrate its data. However, the DMP Tool itself does not store, share, review, or access research data.
Similar to Monitoring, data management, and impact assessment in Africa RISING (20)
Africa RISING project implementation and contribution in Ethiopia. Presented at Africa RISING close-out event.
24-25 January 2023
ILRI campus- Addis Ababa, Ethiopia
The document summarizes a field visit by Africa RISING CGIAR partners to sites in Ethiopia where they are implementing their new SI-MFS initiative. It describes some innovative farmers in the Lemo and Doyogena districts who have adopted integrated crop-livestock-NRM practices promoted by Africa RISING, including using protein-rich legume fodder trees, energy-rich grasses, and soil and water conservation practices. It also highlights the challenges of water shortage and disease, and the potential for the new SI-MFS initiative to build on the success stories and learning from Africa RISING farmers.
This document summarizes planned and ongoing agricultural research activities and studies in the Ethiopian highlands for 2022. It discusses field activities related to livestock feed and forage development as well as crop varietal selection. It also outlines planned, ongoing, and completed studies on topics like gender and scaling assessments. The document notes legacy products to be developed and capacity building efforts. It describes plans to broadcast livestock innovations through local radio and concludes with noting the planned closure of the Africa Research project in Ethiopia in early 2023.
Haimanot Seifu provided a communications update on the Africa RISING program in the Ethiopian Highlands. Key activities before the program ends this year include producing extension manuals, policy briefs, a special journal issue, and a photo book. Surveys are also ongoing regarding gender, monitoring impacts, spillover effects, and scaling. Africa RISING is partnering with AICCRA on workshops, surveys, training modules, and broadcasting feed and forage technologies on local radio stations. A new initiative called SI-MFS involving mixed farming systems in 6 countries was also launched in May to run initially for 3 years from 2022-2024. Support is needed from CKM for legacy products, facilitating
Technique de compostage des tiges de cotonnier au Mali-Sudafrica-rising
Poster prepared by Moumini Guindo, Bouba Traoré, Birhanu Zemadim Birhanu, and Alou Coulibaly for the 13th Symposium of the Malian Society of Applied Sciences (MSAS), 01 July – 05 August 2022.
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...africa-rising
Poster prepared by Moumini Guindo, Bouba Traoré, Birhanu Zemadim Birhanu, and Alou Coulibaly for the 13th Symposium of the Malian Society of Applied Sciences (MSAS), 01 July 1 – 05 August 2022.
The Africa RISING project in Ethiopia's highlands had the goals of improving food security, gender equality, nutrition, income, and capacity building through sustainable intensification research from 2012-2022. It worked in four regions, implementing tested interventions like improved crops, fertilizers, and mechanization. Over 360,000 households directly benefited from validated technologies in phase two, while over 30,000 people participated in training. The project supported graduate students, published research, and faced challenges like COVID-19 and funding issues before planning its exit strategies.
Eliciting willingness to pay for quality maize and beans: Evidence from exper...africa-rising
Poster prepared by Julius Manda, Adane Tufa, Christopher Mutungi, Arega Alene, Victor Manyong and Tahirou Abdoulaye for the IITA Social Science Group Virtual Meeting, 7 December 2021.
The woman has no right to sell livestock: The role of gender norms in Norther...africa-rising
Presented by Kipo Jimah and Gundula Fischer (IITA) at the virtual conference on Cultivating Equality: Advancing Gender Research in Agriculture and Food Systems, 12-15 October 2021
This document summarizes two assessments conducted by Africa RISING on sustainable intensification and return on investment from 2011-2020. It finds that:
1) The total value of direct benefits to farmers was $74.6 million, while the total project cost was $15.9 million, resulting in a return on investment of 469%.
2) An assessment of progress towards sustainable intensification analyzed households by total production per hectare and compared indicators across five domains. It found that more intensified households showed improved scores in agricultural production, economics, environment, human welfare, and social indicators.
3) A focus on assessments at the woreda (district) level provided insights into differences between communities and guidance for
The document summarizes the results of a nutrition assessment study and lessons learned from it. The study aimed to identify how Africa RISING interventions contributed to household nutrition. It used a qualitative research approach with key informant interviews and focus group discussions in Ethiopia. The results showed that the interventions helped to produce and consume a more diverse and nutritious diet, generate income, and improve knowledge of food production and preparation. However, diet diversity remained low and certain nutrient-rich foods were still limited. Key lessons were that technical nutrition support needs frequent follow-ups, and engaging community leaders and husbands is important for influencing mothers' nutrition practices.
The document discusses plans for scaling assessment of Africa RISING interventions. It notes that Africa RISING's second phase focused on scaling approaches through recruiting scaling partners, training of trainers, multi-stakeholder meetings, and research backstopping. The assessment aims to document scaling practices, identify areas for increased support, and develop an exit strategy as the program period concludes. It will use ILRI's scaling framework over six months to provide a technical report and scientific paper.
This document summarizes a presentation on conducting on-farm trials at scale using crowdsourcing. It discusses the benefits and challenges of traditional on-farm trials, and proposes a solution using digital platforms and farmer participation. Farmers would receive random combinations of varieties to test on their own farms and provide rankings. Data would be collected and analyzed to provide feedback to farmers. The approach aims to increase representation while reducing costs compared to traditional on-farm trials. It outlines 10 steps for implementation, including defining varieties, designing projects, recruiting farmers, preparing packages, data collection, analysis and discussion.
Contribution of Africa RISING validated technologies, nutrition-education interventions to household nutrition and participatory nutrition-education need assessment with seasonal food availability in Amhara, Oromia and SNNP regions of Ethiopia
PPT on Sustainable Land Management presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptxshubhijain836
Centrifugation is a powerful technique used in laboratories to separate components of a heterogeneous mixture based on their density. This process utilizes centrifugal force to rapidly spin samples, causing denser particles to migrate outward more quickly than lighter ones. As a result, distinct layers form within the sample tube, allowing for easy isolation and purification of target substances.
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...Sérgio Sacani
Context. The observation of several L-band emission sources in the S cluster has led to a rich discussion of their nature. However, a definitive answer to the classification of the dusty objects requires an explanation for the detection of compact Doppler-shifted Brγ emission. The ionized hydrogen in combination with the observation of mid-infrared L-band continuum emission suggests that most of these sources are embedded in a dusty envelope. These embedded sources are part of the S-cluster, and their relationship to the S-stars is still under debate. To date, the question of the origin of these two populations has been vague, although all explanations favor migration processes for the individual cluster members. Aims. This work revisits the S-cluster and its dusty members orbiting the supermassive black hole SgrA* on bound Keplerian orbits from a kinematic perspective. The aim is to explore the Keplerian parameters for patterns that might imply a nonrandom distribution of the sample. Additionally, various analytical aspects are considered to address the nature of the dusty sources. Methods. Based on the photometric analysis, we estimated the individual H−K and K−L colors for the source sample and compared the results to known cluster members. The classification revealed a noticeable contrast between the S-stars and the dusty sources. To fit the flux-density distribution, we utilized the radiative transfer code HYPERION and implemented a young stellar object Class I model. We obtained the position angle from the Keplerian fit results; additionally, we analyzed the distribution of the inclinations and the longitudes of the ascending node. Results. The colors of the dusty sources suggest a stellar nature consistent with the spectral energy distribution in the near and midinfrared domains. Furthermore, the evaporation timescales of dusty and gaseous clumps in the vicinity of SgrA* are much shorter ( 2yr) than the epochs covered by the observations (≈15yr). In addition to the strong evidence for the stellar classification of the D-sources, we also find a clear disk-like pattern following the arrangements of S-stars proposed in the literature. Furthermore, we find a global intrinsic inclination for all dusty sources of 60 ± 20◦, implying a common formation process. Conclusions. The pattern of the dusty sources manifested in the distribution of the position angles, inclinations, and longitudes of the ascending node strongly suggests two different scenarios: the main-sequence stars and the dusty stellar S-cluster sources share a common formation history or migrated with a similar formation channel in the vicinity of SgrA*. Alternatively, the gravitational influence of SgrA* in combination with a massive perturber, such as a putative intermediate mass black hole in the IRS 13 cluster, forces the dusty objects and S-stars to follow a particular orbital arrangement. Key words. stars: black holes– stars: formation– Galaxy: center– galaxies: star formation
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆Sérgio Sacani
Context. The early-type galaxy SDSS J133519.91+072807.4 (hereafter SDSS1335+0728), which had exhibited no prior optical variations during the preceding two decades, began showing significant nuclear variability in the Zwicky Transient Facility (ZTF) alert stream from December 2019 (as ZTF19acnskyy). This variability behaviour, coupled with the host-galaxy properties, suggests that SDSS1335+0728 hosts a ∼ 106M⊙ black hole (BH) that is currently in the process of ‘turning on’. Aims. We present a multi-wavelength photometric analysis and spectroscopic follow-up performed with the aim of better understanding the origin of the nuclear variations detected in SDSS1335+0728. Methods. We used archival photometry (from WISE, 2MASS, SDSS, GALEX, eROSITA) and spectroscopic data (from SDSS and LAMOST) to study the state of SDSS1335+0728 prior to December 2019, and new observations from Swift, SOAR/Goodman, VLT/X-shooter, and Keck/LRIS taken after its turn-on to characterise its current state. We analysed the variability of SDSS1335+0728 in the X-ray/UV/optical/mid-infrared range, modelled its spectral energy distribution prior to and after December 2019, and studied the evolution of its UV/optical spectra. Results. From our multi-wavelength photometric analysis, we find that: (a) since 2021, the UV flux (from Swift/UVOT observations) is four times brighter than the flux reported by GALEX in 2004; (b) since June 2022, the mid-infrared flux has risen more than two times, and the W1−W2 WISE colour has become redder; and (c) since February 2024, the source has begun showing X-ray emission. From our spectroscopic follow-up, we see that (i) the narrow emission line ratios are now consistent with a more energetic ionising continuum; (ii) broad emission lines are not detected; and (iii) the [OIII] line increased its flux ∼ 3.6 years after the first ZTF alert, which implies a relatively compact narrow-line-emitting region. Conclusions. We conclude that the variations observed in SDSS1335+0728 could be either explained by a ∼ 106M⊙ AGN that is just turning on or by an exotic tidal disruption event (TDE). If the former is true, SDSS1335+0728 is one of the strongest cases of an AGNobserved in the process of activating. If the latter were found to be the case, it would correspond to the longest and faintest TDE ever observed (or another class of still unknown nuclear transient). Future observations of SDSS1335+0728 are crucial to further understand its behaviour. Key words. galaxies: active– accretion, accretion discs– galaxies: individual: SDSS J133519.91+072807.4
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...Creative-Biolabs
Neutralizing antibodies, pivotal in immune defense, specifically bind and inhibit viral pathogens, thereby playing a crucial role in protecting against and mitigating infectious diseases. In this slide, we will introduce what antibodies and neutralizing antibodies are, the production and regulation of neutralizing antibodies, their mechanisms of action, classification and applications, as well as the challenges they face.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Monitoring, data management, and impact assessment in Africa RISING
1. Monitoring, data management, and
impact assessment in Africa RISING
Beliyou Haile [IFPRI], Arkadeep Bandyopadhyay [IFPRI], and
Carlo Azzarri [IFPRI]
Africa RISING Program Learning Event
05 - 08 February 2019
Lilongwe, Malawi
2. Data type Tool
Timing of data
collection
Collection/Aggregation
responsibility
1 FtF Indicators PMMT Once a year
AR researchers, Data
managers/M&E team
2
Direct beneficiaries
and technologies
BTTT.xlsx After each growing
season or as necessary
AR researchers, Data
managers/M&E team
3
Indirect beneficiaries
and technologies
Exposure.xlsx
After every incidence of
"exposure"
AR researchers, Data
managers/M&E team
4
Beneficiaries of
scaling up/out
Scaling.xlsx
Quarterly…or bi-
annualy?
AR researchers, Data managers,
development partners/M&E
team
5
Agronomic/socioeco
nomic data
Various
Per the SIAF
Per evaluation design
AR researchers
6
Scaling-up process
evaluation
TBD Yearly? Data managers
Project monitoring tools
3. • Offline (confidential) data management with encryption (Dropbox)
• Online (non-confidential) data management – Dataverse
• Why upload data on Dataverse?
• Avoid potential losses (mandatory & necessary back up of data)
• Ensure research integrity and validation of results
• Increase research efficiency and impact
• Facilitate data security and minimize risk of data loss
• Enable research continuity through secondary data use
• Ensure compliance with donor requirement
• Register datasets with USAID DDL once they become open
Data management tools
4.
5. • All de-identified data (for which AR funds have been used, even partially)
must be uploaded at least every year, whether they are part of a multiyear
experiment or not
• Datasets that are not part of a multiyear experiment shall be made open
data within 12 months of completion of the data collection (embargo
period)
• Embargo period for datasets not part of a multiyear experiment extends up
to 12 months after the completion of the experiment when complete
datasets are available
Data upload
6. 1st Step
Steps for uploading datasets on Dataverse
Researchers complete Dataverse metadata
template….crucial for proper tagging and discoverability
2nd Step Researchers submit completed metadata, de-identified data
files, documentation, and codebook to IFPRI M&E team
3rd Step M&E team and Dataverse administrator review submitted
documents and data and uploads them (interoperability)
9. Dataverse dataset requests and approval
• Up to three request per Google form
• Existing datasets clustered by country
10. • Data submitted by the requestor compiled in a Google sheet
• …where data provider will be able to search for their name or
emails
• …and grant or deny access (and the reason for the latter)
• Data providers will be sent a reminder email of pending
requests
Dataverse dataset requests and approval
12. Dataverse dataset requests – test google sheet
The progress bar
indicates that the
Google sheet is loading.
Click Dismiss
13. • It is important to let the sheet load completely.
• Kindly refrain from doing anything while the sheet is loading as it seems
slow – it is normal.
• Give it 20-30 seconds before doing anything.
• You might hear the fans on your computer starting to speed up –
again, it is normal.
• When the progress meter is completed, you can work on the form.
Dataverse dataset requests – google sheet
14. • Sheet is protected – data providers can only edit columns K and L
• Column K: Enter Yes or No to grant/deny permission
• Column L: Enter remarks (e.g., reason for denials)
Dataverse dataset requests – google sheet
• No need to save edits on a Google sheet, it auto saves
15. • Step 1: Click on this filter button after selecting column I or J.
• Step 2: Select “Create new temporary filter view”
• Step 3: Choose the desired filter element.
Dataverse dataset requests – google sheet
17. • Filter can be performed on dataset provider’s name as well.
• Filter allows you to quickly glance at all the datasets associated to you
(requested and owned).
• Filter will also allow you to find additional requests more quickly.
• Filter you create is for your individual usage only – it does not render the
default filter for other users.
Dataverse dataset requests – google sheet
19. Topics for breakout sessions
1. What are the three most important tasks you would like the M&E team to
assist you with?
2. Which M&E and data management activities and tools should be changed,
and how?
3. What are the biggest challenges you face with collection and monitoring of
data on:
• FTF indicators?
• Innovations you and your team have been testing?
• Beneficiary farmers/households directly engaged in testing
innovations?
• Monitoring of different beneficiaries of scaling up?
20. Data field Description of data field
Dataset title Full title by which the dataset is known. Please choose a concise title that
is self-explanatory. Avoid using abbreviations and long titles.
Related
Publication
Publications that use the data from this dataset. If available, please
include url to relevant publications and reports based on this data
Description A summary describing the purpose, nature, and scope of the dataset
(no word limit, although we suggest keeping it to the maximum of two
short paragraphs)
Contributor The organization/s or person/s responsible for either collecting,
managing, or otherwise contributing in some form to the development of
the resource.
Related
Datasets
Any datasets that are related to this dataset, such as previous research on
this subject
Production
Date
Date when the data collection or other materials were produced (not
distributed, published or archived)
Producer Person/s or organization/s with the financial or administrative
responsibility over the dataset
Collaborative
organizations
List organizations involved in the data production
Funding
organizations
Grant number and related acknowledgements (if available)
21. Summary of AR data in dataverse (as of 10/2/2018)
Metadata linked to
ICRAF page in Dataverse
Metadata linked
to ILRI's CKAN
Metadata only
(1) (2) (3) (4)
Ghana 14 ` ` 1
Mali 14 0
Sub-total 28 1
Tanzania 30 2
Malawi 11 0
Zambia 3 0
Sub-total 44 2
Ethiopia Ethiopia 22 4 7 3
Sub-total 22
Researchers-Total 94
IFPRI-Total 5
WUR-Total 5
All 104 4 7 9
Africa RISING datasets
in Dataverse
West Africa
East Africa
24. Offline monitoring tools/1
• Beneficiary and Technology Tracking Tool (BTTT)
• Direct beneficiary households
• With unique household identifiers
• Basic socioeconomic characteristics and location identifiers
• AR innovations mapped to direct beneficiaries
• Data managers: responsible for completing/updating the BTTT
• Researchers: responsible for providing data managers with required
details to feed into the BTTT
• IFPRI: responsible for updating/customizing the tool as necessary,
providing trainings, aggregating data, generating de-identified reports
25. Offline monitoring tools/2
• Exposure Tool
• Minimal data (number and type) about farmers exposed to AR
innovations (e.g., recent field day in Mali)
• Scaling Tool
• Minimal data about scaling beneficiaries
• Disaggregated by:
• AR innovation
• Development partner
• Period
• Other tools you are using?
26. Conclusions/1
• Compliance to program data management plan is mandatory
• We are expected/required to collect and manage different types of data to
monitor progress and validate our research
• Researchers need to actively involve your respective data managers
during the planning and implementation of your research/field activities
• Data managers should proactively support research activities by all teams
in their mega site
• Researchers shall communicate with their respective scaling partners of
expected reporting requirements and templates
• FTF indicator data must be complete, adequately disaggregated, and
consistent
27. Conclusions/2
• All de-identified data (for which AR funds have been used, even partially)
must be uploaded at least every year, whether they are part of a
multiyear experiment or not
• Datasets that are not part of a multiyear experiment shall be made open
data within 12 months of completion of the data collection (embargo
period)
• Embargo period for datasets not part of a multiyear experiment extends
up to 12 months after the completion of the experiment when complete
datasets are available
28. Data sharing among AR partners
• Partners expected to share confidential and non-confidential data within the
program
• For within-program confidential data sharing, Data User Agreement shall be
signed between owner and requestor
• Partners with IRB offices shall make within-program data sharing explicit when
submitting their protocols
• All data shall be properly cited, collaborative research encouraged
29. • Data managers responsible for compiling a list (“universe”) of datasets:
• Collected thus far
• To be collected in FY 2019 and beyond
• Along with info about experiment type and duration
• …by reviewing work plans and progress reports
• …against which the completeness of (current and future) datasets on Dataverse
can be assessed
• Chief Scientists responsible for ensuring:
• Data collection plan is clearly identified in workplans
• Data have been collected and uploaded annually or on an appropriately
regular basis
• Support to the research teams to identify the appropriate timeline for open
data
Tracking Dataverse data uploads/2
30. Africa Research in Sustainable Intensification for the Next Generation
africa-rising.net
This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
Thank You
Editor's Notes
Inform the audience that this is what the Google sheet will look like the first time they open it.
To the audience: “Once this sheet opens, it is important to let the sheet load completely. Kindly do not do anything with the sheet because it will appear laggy. Give it 20-30 seconds before doing anything. You might hear the fans on your computer starting to run
To the audience: “Once this sheet opens, it is important to let the sheet load completely. Kindly do not do anything with the sheet because it will appear laggy. Give it 20-30 seconds before doing anything. You might hear the fans on your computer starting to run
To the audience: “Once this sheet opens, it is important to let the sheet load completely. Kindly do not do anything with the sheet because it will appear laggy. Give it 20-30 seconds before doing anything. You might hear the fans on your computer starting to run
To the audience: “Once this sheet opens, it is important to let the sheet load completely. Kindly do not do anything with the sheet because it will appear laggy. Give it 20-30 seconds before doing anything. You might hear the fans on your computer starting to run
To the audience: “Once this sheet opens, it is important to let the sheet load completely. Kindly do not do anything with the sheet because it will appear laggy. Give it 20-30 seconds before doing anything. You might hear the fans on your computer starting to run