SlideShare a Scribd company logo
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
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
• 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
• 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
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)
Dataverse dataset requests and approval
• Requests being managed through Google form (since last week)
Dataverse dataset requests and approval
Dataverse dataset requests and approval
• Up to three request per Google form
• Existing datasets clustered by country
• 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
Dataverse dataset requests – test google sheet
Dataverse dataset requests – test google sheet
The progress bar
indicates that the
Google sheet is loading.
Click Dismiss
• 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
• 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
• 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
Dataverse dataset requests – google sheet
• 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
Beneficiary
households
Non-beneficiary
households
Control
households
Action villages Control villages
Spillovers and village targeting
Project impact and targeting
(village and household)
Impact assessment
• Baseline surveys in all AR country except Zambia (2013/2014)
• Follow-up surveys in Malawi and Mali by summer 2019 (tentatively)
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?
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)
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
Creating a dataverse account
PART IV:
AR monitoring tools (offline)
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
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?
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
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
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
• 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
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

More Related Content

Similar to Monitoring, data management, and impact assessment in Africa RISING

Monitoring, Evaluation, and Data Management
Monitoring, Evaluation, and Data ManagementMonitoring, Evaluation, and Data Management
Monitoring, Evaluation, and Data Management
africa-rising
 
Odp rwanda-odra-rajiv
Odp rwanda-odra-rajivOdp rwanda-odra-rajiv
Odp rwanda-odra-rajiv
Rajiv Ranjan
 
Monitoring & Evaluation and ICTs4D
Monitoring & Evaluation and ICTs4DMonitoring & Evaluation and ICTs4D
Monitoring & Evaluation and ICTs4D
CIAT
 
How to access the AEDC data collections
How to access the AEDC data collectionsHow to access the AEDC data collections
How to access the AEDC data collections
Sonia Whiteley
 
Open data for development
Open data for developmentOpen data for development
Open data for development
mlepage
 
Review of Initiatives to Assemble Data on Agricultural Public Expenditures
Review of Initiatives to Assemble Data on Agricultural Public ExpendituresReview of Initiatives to Assemble Data on Agricultural Public Expenditures
Review of Initiatives to Assemble Data on Agricultural Public Expenditures
African Regional Strategic Analysis and Knowledge Support System (ReSAKSS)
 
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...
IFPRI Africa
 
OSFair2017 Workshop | OpenDataMonitor
OSFair2017 Workshop | OpenDataMonitorOSFair2017 Workshop | OpenDataMonitor
OSFair2017 Workshop | OpenDataMonitor
Open Science Fair
 
Open Sesame: Open Data, Data Liberation and Opportunities for Librarians
Open Sesame: Open Data, Data Liberation and Opportunities for LibrariansOpen Sesame: Open Data, Data Liberation and Opportunities for Librarians
Open Sesame: Open Data, Data Liberation and Opportunities for Librarians
Communication and Media Studies, Carleton University
 
The challenges of implementing generic web and mobile apps for managing and m...
The challenges of implementing generic web and mobile apps for managing and m...The challenges of implementing generic web and mobile apps for managing and m...
The challenges of implementing generic web and mobile apps for managing and m...
Rob Worthington
 
Mainstreaming e-data collection in CIAT programs in Africa
Mainstreaming e-data collection in CIAT programs in AfricaMainstreaming e-data collection in CIAT programs in Africa
Mainstreaming e-data collection in CIAT programs in Africa
CIAT
 
The Innovator’s Journey: Asset Manager Insights
The Innovator’s Journey: Asset Manager InsightsThe Innovator’s Journey: Asset Manager Insights
The Innovator’s Journey: Asset Manager Insights
State Street
 
Data Analytics-Unit 1 , this Is ppt for student help
Data Analytics-Unit 1 , this Is ppt for student helpData Analytics-Unit 1 , this Is ppt for student help
Data Analytics-Unit 1 , this Is ppt for student help
SaurabhJaiswal790114
 
Data Management Planning for Engineers
Data Management Planning for EngineersData Management Planning for Engineers
Data Management Planning for Engineers
Sherry Lake
 
Experiences with implementing the Sustainable Intensification Assessment Fram...
Experiences with implementing the Sustainable Intensification Assessment Fram...Experiences with implementing the Sustainable Intensification Assessment Fram...
Experiences with implementing the Sustainable Intensification Assessment Fram...
africa-rising
 
Data management and sharing protocol
Data management and sharing protocolData management and sharing protocol
Data management and sharing protocol
africa-rising
 
Practical Data Management Plans
Practical Data Management PlansPractical Data Management Plans
Practical Data Management Plans
IUPUI
 
Agricultural R&D indicators monitoring investments and capacity development a...
Agricultural R&D indicators monitoring investments and capacity development a...Agricultural R&D indicators monitoring investments and capacity development a...
Agricultural R&D indicators monitoring investments and capacity development a...
Hillary Hanson
 
Agriculture Public Expenditure Workshop Module 4
Agriculture Public Expenditure Workshop Module 4Agriculture Public Expenditure Workshop Module 4
Agriculture Public Expenditure Workshop Module 4
African Regional Strategic Analysis and Knowledge Support System (ReSAKSS)
 
Leveraging the dmp tool
Leveraging the dmp toolLeveraging the dmp tool
Leveraging the dmp tool
Brian Zelip
 

Similar to Monitoring, data management, and impact assessment in Africa RISING (20)

Monitoring, Evaluation, and Data Management
Monitoring, Evaluation, and Data ManagementMonitoring, Evaluation, and Data Management
Monitoring, Evaluation, and Data Management
 
Odp rwanda-odra-rajiv
Odp rwanda-odra-rajivOdp rwanda-odra-rajiv
Odp rwanda-odra-rajiv
 
Monitoring & Evaluation and ICTs4D
Monitoring & Evaluation and ICTs4DMonitoring & Evaluation and ICTs4D
Monitoring & Evaluation and ICTs4D
 
How to access the AEDC data collections
How to access the AEDC data collectionsHow to access the AEDC data collections
How to access the AEDC data collections
 
Open data for development
Open data for developmentOpen data for development
Open data for development
 
Review of Initiatives to Assemble Data on Agricultural Public Expenditures
Review of Initiatives to Assemble Data on Agricultural Public ExpendituresReview of Initiatives to Assemble Data on Agricultural Public Expenditures
Review of Initiatives to Assemble Data on Agricultural Public Expenditures
 
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...
Review of data initiatives - Presented by Tewodaj Mogues (Project Manager), I...
 
OSFair2017 Workshop | OpenDataMonitor
OSFair2017 Workshop | OpenDataMonitorOSFair2017 Workshop | OpenDataMonitor
OSFair2017 Workshop | OpenDataMonitor
 
Open Sesame: Open Data, Data Liberation and Opportunities for Librarians
Open Sesame: Open Data, Data Liberation and Opportunities for LibrariansOpen Sesame: Open Data, Data Liberation and Opportunities for Librarians
Open Sesame: Open Data, Data Liberation and Opportunities for Librarians
 
The challenges of implementing generic web and mobile apps for managing and m...
The challenges of implementing generic web and mobile apps for managing and m...The challenges of implementing generic web and mobile apps for managing and m...
The challenges of implementing generic web and mobile apps for managing and m...
 
Mainstreaming e-data collection in CIAT programs in Africa
Mainstreaming e-data collection in CIAT programs in AfricaMainstreaming e-data collection in CIAT programs in Africa
Mainstreaming e-data collection in CIAT programs in Africa
 
The Innovator’s Journey: Asset Manager Insights
The Innovator’s Journey: Asset Manager InsightsThe Innovator’s Journey: Asset Manager Insights
The Innovator’s Journey: Asset Manager Insights
 
Data Analytics-Unit 1 , this Is ppt for student help
Data Analytics-Unit 1 , this Is ppt for student helpData Analytics-Unit 1 , this Is ppt for student help
Data Analytics-Unit 1 , this Is ppt for student help
 
Data Management Planning for Engineers
Data Management Planning for EngineersData Management Planning for Engineers
Data Management Planning for Engineers
 
Experiences with implementing the Sustainable Intensification Assessment Fram...
Experiences with implementing the Sustainable Intensification Assessment Fram...Experiences with implementing the Sustainable Intensification Assessment Fram...
Experiences with implementing the Sustainable Intensification Assessment Fram...
 
Data management and sharing protocol
Data management and sharing protocolData management and sharing protocol
Data management and sharing protocol
 
Practical Data Management Plans
Practical Data Management PlansPractical Data Management Plans
Practical Data Management Plans
 
Agricultural R&D indicators monitoring investments and capacity development a...
Agricultural R&D indicators monitoring investments and capacity development a...Agricultural R&D indicators monitoring investments and capacity development a...
Agricultural R&D indicators monitoring investments and capacity development a...
 
Agriculture Public Expenditure Workshop Module 4
Agriculture Public Expenditure Workshop Module 4Agriculture Public Expenditure Workshop Module 4
Agriculture Public Expenditure Workshop Module 4
 
Leveraging the dmp tool
Leveraging the dmp toolLeveraging the dmp tool
Leveraging the dmp tool
 

More from africa-rising

AR_project_implementation-2023.pptx
AR_project_implementation-2023.pptxAR_project_implementation-2023.pptx
AR_project_implementation-2023.pptx
africa-rising
 
Photo_report_2022.pptx
Photo_report_2022.pptxPhoto_report_2022.pptx
Photo_report_2022.pptx
africa-rising
 
AR_activities_2022.pptx
AR_activities_2022.pptxAR_activities_2022.pptx
AR_activities_2022.pptx
africa-rising
 
Livestock feed_2022.pptx
Livestock feed_2022.pptxLivestock feed_2022.pptx
Livestock feed_2022.pptx
africa-rising
 
Communications_update_2022.pptx
Communications_update_2022.pptxCommunications_update_2022.pptx
Communications_update_2022.pptx
africa-rising
 
ar_SI-MFS_2022.pptx
ar_SI-MFS_2022.pptxar_SI-MFS_2022.pptx
ar_SI-MFS_2022.pptx
africa-rising
 
Technique de compostage des tiges de cotonnier au Mali-Sud
Technique de compostage des tiges de cotonnier au Mali-SudTechnique de compostage des tiges de cotonnier au Mali-Sud
Technique de compostage des tiges de cotonnier au Mali-Sud
africa-rising
 
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...Flux des nutriments (N, P, K) des resources organiques dans les exploitations...
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...
africa-rising
 
Ar briefing feb2022
Ar  briefing feb2022Ar  briefing feb2022
Ar briefing feb2022
africa-rising
 
Eliciting willingness to pay for quality maize and beans: Evidence from exper...
Eliciting willingness to pay for quality maize and beans: Evidence from exper...Eliciting willingness to pay for quality maize and beans: Evidence from exper...
Eliciting willingness to pay for quality maize and beans: Evidence from exper...
africa-rising
 
The woman has no right to sell livestock: The role of gender norms in Norther...
The woman has no right to sell livestock: The role of gender norms in Norther...The woman has no right to sell livestock: The role of gender norms in Norther...
The woman has no right to sell livestock: The role of gender norms in Norther...
africa-rising
 
Ar overview 2021
Ar overview 2021Ar overview 2021
Ar overview 2021
africa-rising
 
Potato seed multiplication 2021
Potato seed multiplication 2021Potato seed multiplication 2021
Potato seed multiplication 2021
africa-rising
 
Two assessments 2021
Two assessments 2021Two assessments 2021
Two assessments 2021
africa-rising
 
Nutrition assessment 2021
Nutrition assessment 2021Nutrition assessment 2021
Nutrition assessment 2021
africa-rising
 
Scaling assessment 2021
Scaling assessment 2021Scaling assessment 2021
Scaling assessment 2021
africa-rising
 
Aiccra supervision 2021
Aiccra supervision 2021Aiccra supervision 2021
Aiccra supervision 2021
africa-rising
 
Ar scaling 2021
Ar scaling 2021Ar scaling 2021
Ar scaling 2021
africa-rising
 
Ar training 2021
Ar training 2021Ar training 2021
Ar training 2021
africa-rising
 
Ar nutrition 2021
Ar nutrition 2021Ar nutrition 2021
Ar nutrition 2021
africa-rising
 

More from africa-rising (20)

AR_project_implementation-2023.pptx
AR_project_implementation-2023.pptxAR_project_implementation-2023.pptx
AR_project_implementation-2023.pptx
 
Photo_report_2022.pptx
Photo_report_2022.pptxPhoto_report_2022.pptx
Photo_report_2022.pptx
 
AR_activities_2022.pptx
AR_activities_2022.pptxAR_activities_2022.pptx
AR_activities_2022.pptx
 
Livestock feed_2022.pptx
Livestock feed_2022.pptxLivestock feed_2022.pptx
Livestock feed_2022.pptx
 
Communications_update_2022.pptx
Communications_update_2022.pptxCommunications_update_2022.pptx
Communications_update_2022.pptx
 
ar_SI-MFS_2022.pptx
ar_SI-MFS_2022.pptxar_SI-MFS_2022.pptx
ar_SI-MFS_2022.pptx
 
Technique de compostage des tiges de cotonnier au Mali-Sud
Technique de compostage des tiges de cotonnier au Mali-SudTechnique de compostage des tiges de cotonnier au Mali-Sud
Technique de compostage des tiges de cotonnier au Mali-Sud
 
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...Flux des nutriments (N, P, K) des resources organiques dans les exploitations...
Flux des nutriments (N, P, K) des resources organiques dans les exploitations...
 
Ar briefing feb2022
Ar  briefing feb2022Ar  briefing feb2022
Ar briefing feb2022
 
Eliciting willingness to pay for quality maize and beans: Evidence from exper...
Eliciting willingness to pay for quality maize and beans: Evidence from exper...Eliciting willingness to pay for quality maize and beans: Evidence from exper...
Eliciting willingness to pay for quality maize and beans: Evidence from exper...
 
The woman has no right to sell livestock: The role of gender norms in Norther...
The woman has no right to sell livestock: The role of gender norms in Norther...The woman has no right to sell livestock: The role of gender norms in Norther...
The woman has no right to sell livestock: The role of gender norms in Norther...
 
Ar overview 2021
Ar overview 2021Ar overview 2021
Ar overview 2021
 
Potato seed multiplication 2021
Potato seed multiplication 2021Potato seed multiplication 2021
Potato seed multiplication 2021
 
Two assessments 2021
Two assessments 2021Two assessments 2021
Two assessments 2021
 
Nutrition assessment 2021
Nutrition assessment 2021Nutrition assessment 2021
Nutrition assessment 2021
 
Scaling assessment 2021
Scaling assessment 2021Scaling assessment 2021
Scaling assessment 2021
 
Aiccra supervision 2021
Aiccra supervision 2021Aiccra supervision 2021
Aiccra supervision 2021
 
Ar scaling 2021
Ar scaling 2021Ar scaling 2021
Ar scaling 2021
 
Ar training 2021
Ar training 2021Ar training 2021
Ar training 2021
 
Ar nutrition 2021
Ar nutrition 2021Ar nutrition 2021
Ar nutrition 2021
 

Recently uploaded

Sustainable Land Management - Climate Smart Agriculture
Sustainable Land Management - Climate Smart AgricultureSustainable Land Management - Climate Smart Agriculture
Sustainable Land Management - Climate Smart Agriculture
International Food Policy Research Institute- South Asia Office
 
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptx
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptxTOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptx
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptx
shubhijain836
 
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdfGadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
PirithiRaju
 
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Sérgio Sacani
 
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
ABHISHEK SONI NIMT INSTITUTE OF MEDICAL AND PARAMEDCIAL SCIENCES , GOVT PG COLLEGE NOIDA
 
gastroretentive drug delivery system-PPT.pptx
gastroretentive drug delivery system-PPT.pptxgastroretentive drug delivery system-PPT.pptx
gastroretentive drug delivery system-PPT.pptx
Shekar Boddu
 
Clinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdfClinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdf
RAYMUNDONAVARROCORON
 
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
Sérgio Sacani
 
Direct Seeded Rice - Climate Smart Agriculture
Direct Seeded Rice - Climate Smart AgricultureDirect Seeded Rice - Climate Smart Agriculture
Direct Seeded Rice - Climate Smart Agriculture
International Food Policy Research Institute- South Asia Office
 
Male reproduction physiology by Suyash Garg .pptx
Male reproduction physiology by Suyash Garg .pptxMale reproduction physiology by Suyash Garg .pptx
Male reproduction physiology by Suyash Garg .pptx
suyashempire
 
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths ForwardImmersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
Leonel Morgado
 
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
PirithiRaju
 
Physiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptxPhysiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptx
fatima132662
 
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Creative-Biolabs
 
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
hozt8xgk
 
cathode ray oscilloscope and its applications
cathode ray oscilloscope and its applicationscathode ray oscilloscope and its applications
cathode ray oscilloscope and its applications
sandertein
 
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
vluwdy49
 
Randomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNERandomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNE
University of Maribor
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
RDhivya6
 
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Leonel Morgado
 

Recently uploaded (20)

Sustainable Land Management - Climate Smart Agriculture
Sustainable Land Management - Climate Smart AgricultureSustainable Land Management - Climate Smart Agriculture
Sustainable Land Management - Climate Smart Agriculture
 
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptx
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptxTOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptx
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptx
 
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdfGadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
 
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
Candidate young stellar objects in the S-cluster: Kinematic analysis of a sub...
 
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
 
gastroretentive drug delivery system-PPT.pptx
gastroretentive drug delivery system-PPT.pptxgastroretentive drug delivery system-PPT.pptx
gastroretentive drug delivery system-PPT.pptx
 
Clinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdfClinical periodontology and implant dentistry 2003.pdf
Clinical periodontology and implant dentistry 2003.pdf
 
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
 
Direct Seeded Rice - Climate Smart Agriculture
Direct Seeded Rice - Climate Smart AgricultureDirect Seeded Rice - Climate Smart Agriculture
Direct Seeded Rice - Climate Smart Agriculture
 
Male reproduction physiology by Suyash Garg .pptx
Male reproduction physiology by Suyash Garg .pptxMale reproduction physiology by Suyash Garg .pptx
Male reproduction physiology by Suyash Garg .pptx
 
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths ForwardImmersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
 
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
 
Physiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptxPhysiology of Nervous System presentation.pptx
Physiology of Nervous System presentation.pptx
 
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
 
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
 
cathode ray oscilloscope and its applications
cathode ray oscilloscope and its applicationscathode ray oscilloscope and its applications
cathode ray oscilloscope and its applications
 
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
 
Randomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNERandomised Optimisation Algorithms in DAPHNE
Randomised Optimisation Algorithms in DAPHNE
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
 
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
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)
  • 7. Dataverse dataset requests and approval • Requests being managed through Google form (since last week)
  • 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
  • 11. Dataverse dataset requests – test google sheet
  • 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
  • 16. 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
  • 18. Beneficiary households Non-beneficiary households Control households Action villages Control villages Spillovers and village targeting Project impact and targeting (village and household) Impact assessment • Baseline surveys in all AR country except Zambia (2013/2014) • Follow-up surveys in Malawi and Mali by summer 2019 (tentatively)
  • 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
  • 23. PART IV: AR monitoring tools (offline)
  • 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

  1. Inform the audience that this is what the Google sheet will look like the first time they open it.
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. https://dataverse.harvard.edu/dataverse.xhtml?alias=AfricaRISING