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.

1. Monitoring, Evaluation, and Data
Management
Beliyou Haile and Carlo Azzarri, IFPRI
Africa RISING Ethiopian Highlands Project Review and Planning
Meeting
Addis Ababa, 21–22 May 2019

2. Data type Tool
Frequency 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 Process evaluation TBD Yearly Data managers
Monitoring tools

3. Indicator # Indicator Level of Disaggregation
EG.3.2-25 Number of hectares under
improved management
practices or technologies with
USG assistance [IM-level]
 Type of hectare:
 crop land
 cultivated pasture
 rangeland
 conservation/protected area
 freshwater or marine ecosystems
 aquaculture
 other
 Management practice or technology type
(double-counting allowed)
 Sex (no double-counting)
 Age (no double-counting)
EG.3.2-24 Number of individuals in the
agriculture system who have
applied improved management
practices or technologies with
USG assistance [IM-level]
 Value chain actor type:
 Smallholder producers
 Non-smallholder producers
 People in government
 People in private sector firms
 People in civil society
 Others
 Disaggregates Not Available
 Management practice or technology type
(double-counting allowed)

4. Indicator # Indicator Level of Disaggregation
EG.3.2-2 Number of individuals
who have received
USG-supported
degree-granting non-
nutrition-related food
security training [IM-
level]
 Sex (Male, Female, Disaggregates Not Available)
 Duration
HL.9-4 Number of individuals
receiving nutrition-
related professional
training through USG-
supported programs
[IM-level]
 Sex (Male, Female, Disaggregates Not Available)
 Type of training
 Number of non-degree seeking trainees
 Number of degree seeking trainees (New,
continuing, Disaggregates Not Available)

5. Indicator # Indicator Level of Disaggregation
EG.3.2-7 Number of
technologies,
practices, and
approaches under
various phases of
research,
development, and
uptake as a result
of USG assistance
[IM-level]
 Category of R&D (Total number of unique technologies /
practices / approaches from all categories (no double-
counting)
 Plant and animal improvement research
 Production systems research
 Social science research
 Disaggregates Not Available
 Category of R&D: Plant and animal improvement
research
 Category of R&D: Production systems research
 Category of R&D: Social science research
 Category of R&D: Disaggregates Not Available
 Phase 1: Number of technologies, practices, and
approaches under research as a result of USG assistance
 Phase 2: Number of technologies, practices, and
approaches under field testing as a result of USG
assistance
 Phase 3: Number of technologies, practices, and
approaches made available for transfer as a result of

6. Data management
• Program data repository platform - Dataverse
https://dataverse.harvard.edu/dataverse/AfricaRISING
• Why upload data?
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
• Monitoring of data access requests, including ILRI
datasets on CKAN

7. • https://cgspace.cgiar.org/bitstream/handle/10568/100536/ar_dmp
lan.pdf?sequence=1&isAllowed=y
• 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
Program data management plan

8. 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 restricted dataset access request
• Requests being managed through Google form

10. Project Mapping and Monitoring Tool (PMMT): Data Entry Application

11. PMMT Versus DATAVERSE
Project Mapping and Monitoring Tool
(PMMT)
DATAVERSE
Managed by IFPRI with support from
M&E managers
Managed by Harvard University, AR page is managed
by IFPRI’s Dataverse administrator
Compiling FtF Indicators and Custom
Indicators
Used for storing and sharing various types of data and
supporting documentation
All researchers have account here, and
can login and create FtF data reports
Users needs only to have an account to
access information on the PMMT
Data owners will need to reach out to IFPRI M&E
team following the steps discussed before
Users can browse and filter (By Region,
Country, District, Partner, and Target
Technology)
Data owners responsible for ensuring that datafiles to
be uploaded have no identifying information
For each dataset to be uploaded, a complete
metadata is needed
There is no restriction to data uploaded
on PMMT by authorized users
Data uploaded done by IFPRI’s, Dataverse
administrator can grant owners the right to access
and download their own dataset
Researchers can download their own data
reports
Users need to fill out data user agreement to access

12. Planned Activities/1
1. Fill the vacant M&E officer/data manager position
(open since Gebrehiwot H.’s departure in Nov 2017).
Consultant in the interim?
2. Build a centralized database of (different types of)
beneficiaries and innovations
3. Design of IFPRI follow-up survey (2021). Baseline
survey of 73 on-farm trial farmers and SLATE farmers
4. Follow-up survey tool: Hybrid b/n RHoMIS and IFPRI
baseline tool?
5. Update the PMMT

13. Planned Activities/2
5. Collaborative research:
- Women’s access to resources and nutrition
- Ex-ante evaluation of selected innovations

14. CGIAR Partners:

15.  Academic institutions:
 Wachemo, Mekelle, Madawolabu, Debre Berhan and Hawassa universities;
Maichew Agricultural College
 Regional research organizations:
 Amhara Regional Agricultural Research Institute, Southern Agricultural
Research Institute, Tigray Agricultural Research Institute, Oromia Agricultural
Research Institute
 Federal research organizations:
 Ethiopian Institute for Agricultural Research, Ethiopian Public Health
Institute
 Offices of Agriculture:
 Endamekoni (Tigray), Basona Worena (Amhara), Lemo (SNNRP) and Sinana
(Oromia)
 Private entrepreneurs: Fuji integrated farm
 NGOs: GRAD, Hundie, SOS Sahel, Sunarma
 Agricultural Transformation Agency (ATA)
 Innovation laboratories: SIIL, ILSSI, PHIL, LSIL
LocalPartners (Phase 1)- Ethiopia

16. Scaling Development Partners in the Different Sites/Regions
(Phase II)- Examples
InterAide France SNNPR, Lemo NGO
Send-a-Cow SNNPR, Lemo NGO
Ethiopian Catholic Church SNNPR, Lemo NGO
Hundie Addis Ababa NGO
World Vision SNNPR/Lemo NGO
Woreda, zonal and regional livestock and
fishery development offices, and
agriculture and natural resources
development offices
SNNPR, Amhara, Oromia and
Tigray/Lemo, Basona, Sinana,
Endamehoni
GOs
GRAD/REST Tigray/ Endamehoni NGO
Raya, Dashen and Habesha Breweries Tigray/ Endamehoni and Amhara/
Debre Birhan
PLC
Oromia Seed Enterprise Oromia/Sinana GO
Madda Walabu, Wachemo, Debere
Birhan, Mekele, Hawassa Universities
SNNPR, Amhara, Oromia and Tigray GOV
Saint Mary and Michew ATEVT collages Tigray/Endamehoni GOs
Regional and Federal Research centers SNNPR, Amhara, Oromia and
Tigray/Lemo, Basona, Sinnan,
Endamehoni
GOs

17. 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

18. Dataverse Dataset Requests and Approval

19. Dataverse Dataset Requests and Approval
• Up to three request per Google form
• Existing datasets clustered by country

20. • 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

21. The progress bar
indicates that the
Google sheet is loading.
Click Dismiss
Dataverse Dataset Requests – Test google sheet

22. FtF Data Requirements
FY 2019 FtF Indicators to Report Data Moving Forward
Indicator Definition
EG.3.2-25
Number of hectares under improved management practices or technologies
with USG assistance
EG.3.2-24
Number of individuals in the agriculture system who have applied improved
management practices or technologies with USG assistance
EG.3.2-2
Number of individuals who have received USG-supported degree-granting non-
nutrition-related food security training
HL.9-4
Number of individuals receiving nutrition-related professional training
through USG-supported programs
EG.3.2-7
Number of technologies, practices, and approaches under various
phases of research, development, and uptake as a result of USG
assistance

23. BTTT: Project Information
LIST OF AFRICA RISING VILLAGES, DATA ENTRY PERSONNEL
AND BENEFICIARY TYPES
LIST OF AFRICA RISING (AR) TECHNOLOGIES TESTED/ADOPTED BY DIRECT BENEFICIARIES.
NOTE: DIRECT BENEFICIARIES ARE FARMERS WHO PARTICIPATE IN THE TESTING OF AR
TECHNOLOGIES OR MANAGEMENT PRACTICES THROUGH ON-FARM TRIALS OR OTHER
APPROACHES
PLEASE LIST ALL TECHNOLOGIES/PRACTICES TESTED
Please verify that all of the below information is correct. If there
are any errors, please contact the IFPRI M&E Team BEFORE using
this workbook.
Technol
ogy ID
Technology Name/Description
Years of Africa RISING Implementation
Please select "yes" for each of the years that
the technologies were implemented. Select
"no" for the years when they were not
implemented.
Africa RISING
Villages
Data Entry
Personnel AR Beneficiary Type
201220132014 20152016201720182019 20202021
Person 1 cowpea
Person 2 cowpea + maize
Person 3 cowpea + soybean
Person 4 maize
Person 5 maize + cowpea
maize + cowpea + soybean
maize + soybean

24. GHANA Basic Household Information
Village
NAME OF THE
BENEFICIARY HOUSEHOLD
HEAD
[First name, Last name]
NAME OF
HOUSEHOLD HEAD'S
SPOUSE (if
applicable)
[First name, Last
name]
MAIN BENEFICIARY
INFORMATION HOUSEHOLD LOCATION (GPS)
OTHER VILLAGE
CONTACT
DATA
ENTRY
PERSONNEL
[First name,
Last name]
Please select the
village from the
dropdown menu
Is this
the
primary
benefici
ary?
Select
from
the
dropdo
wn
menu
Is this the
primary
beneficiary
? Select
from the
dropdown
menu
Select
from the
dropdow
n menu
Age
Select
from the
dropdow
n menu
Telepho
ne
number
Latitute (N) Longitude (W)
Name
Telephone
Number
Please
select the
data entry
personnel
from the
dropdown
menuGender
Educatio
n
Degree
s
Minute
s
Second
s
Degree
s
Minute
s Seconds
Bonia
Bonia
Bonia
Bonia
Bonia
Bonia
Bonia
BTTT: Beneficiary Information

25. Exposure Template
EXPOSURE TEMPLATE:- FOR COLLECTING DATA ON THE NUMBER OF INDIVIDUALS EXPOSED TO DIFFERENT AFRICA
RISING TREATMENTS (E.G., FIELD DAYS, VIDEO DEMOS, ETC.)
Country __________________
Number of attendees
District Village Sub-village Type of the event/intervention Date Organizing organization (s) Total Female Youth (<25 years)

26. Exposure Template (Example from Ghana)
EXPOSURE TEMPLATE:- FOR COLLECTING DATA ON THE NUMBER OF INDIVIDUALS EXPOSED TO DIFFERENT AFRICA RISING TREATMENTS
(E.G., FIELD DAYS, VIDEO DEMOS, ETC.)
Country __Ghana____
Number of attendees
District Village
Sub-
village Type of the event/interventions Date
Organizing
organization (s) Total
Femal
e
Youth (<25
years)
Nadowli Goli
Field days of MLS, CPLM and Groundnut varieties
and spacing
25 September
2018IITA 105 59 51
Wa West Zanko
Field days of MLS, CPLM and Groundnut varieties
and spacing
26 September
2018IITA 87 36 51
Kassena-Nanakan Bonia
Field days of MLS, CPLM and Groundnut varieties
and spacing 02 October 2018IITA 43 21 82
Bongo samboligo
Field days of MLS, CPLM and Groundnut varieties
and spacing 05 October 2018IITA 61 42 39
Savelugu Tibali
Field days of MLS, CPLM and Groundnut varieties
and spacing 09 October 2018IITA 47 13 68
Savelugu Duko
Field days of MLS, CPLM and Groundnut varieties
and spacing 10 October 2018IITA 47 15 68
Tolon Cheyohi No.2
Field days of MLS, CPLM and Groundnut varieties
and spacing 11 October 2018IITA 44 12
Tolon Tingoli Demonstration of maize shelling machines
13 December
2018IITA 96 27
Tolon Gbanjong Demonstration of maize shelling machines
17 December
2018IITA 120 70
Savelugu Duko
Improved feed trough demonstration/Improved feed
trough 03 January 2019ILRI/CSIR-ARI 20 5
Savelugu Tibali
Improved feed trough demonstration/Improved feed
trough 17 January 2019ILRI/CSIR-ARI 39 13 29
Kassena-Nanakan Gia
Improved feed trough demonstration/Improved feed
trough 16 April 2019ILRI/CSIR-ARI 18 10
Kasena Nakana
West Nyangua Vegetable Production Training 20 February 2019WorldVeg 30 16 14
Kasena Nankana
East Bonia Vegetable Production Training 20 February 2019WorldVeg 30 15 17

27. SCALING TEMPLATE:- FOR COLLECTING DATA ON THE NUMBER OF HOUSEHOLDS BENEFITING FROM AFRICA RISING
TECHNOLOGIES AS PART OF THE SCALING UP AND IN COLLABORATION WITH DEVELOPMENT PARTNERS
Country __________________
Jan - March, 2019 April- June, 2019 July - Sep., 2019 Oct- Dec, 2019
Male Female Male Female Male Female Male Female
Region District Village Technology
Development
partner(s)
Scaling Template

28. 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.