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Transcript of Accessing and using data Donor needs 1 Palace Street, London SW1E 5HE Abercrombie House, Eaglesham...
Accessing and using data
Donor needs
1 Palace Street, London SW1E 5HEAbercrombie House, Eaglesham Road, East Kilbride, Glasgow G75 8EA
Siobhan CareyChief StatisticianDFID
Page 5
Context
• DFID budget is increasing 12% pa • Consensus around the Managing for Development
Results Agenda • Creates expectations • So how can we help policy colleagues be more
evidenced based?• The stupid things that test us -
• Updates - not adequately referenced• Lack of metadata• Short lead in times • country dialogue with centre - who’s data to use
• What would make us more effective ?
Page 6
Context
• Programmes in almost 70 countries• Over 500 advisory staff – 10 disciplines• Posting – 2 to 4 years• Managing knowledge is difficult in general• Managing knowledge about data
• Got to be a better way
better use of better statistics
Page 8
“Looking for” at expense of “looking at”
Access• All the data in a single space
(WDI, UN, Country, DAC…)• Metadata –means to hold/capture• Ideally up to the minute - available on day produced• Other stuff - capturing the knowledge - referencing
Communication• Tools to make the messages easy and quick to absorb • Automating routine reports properly cited
Page 9
Portal for Development Indicators
Prototype• How feasible is it to have different data in the
same space?• Is it useful?• Approached from two fronts
• content - tested using indicators from different sources - not comprehensive
• function - capturing the knowledge, additional graph and map features
• Used DevInfo for convenience
Page 10
If this was easy it would have been done already
• Issues around standards, definitions, classifications
• Content management• getting stuff in• handling revisions• ownership / stewardship
• Ideally not just indicators - distributions, microdata, project data, expenditure data, outputs……
Page 12
Expected benefits
• Better and more timely data analysis for policy and country offices
• More comprehensive analyses, using international data in conjunction with e.g. DFID expenditure;
• Time saving in data extraction and presentation;• Easy and appropriate use by less-informed users
including an enhanced awareness of the quality of the data for the end-user.
• Help resolve discrepancies between data sources;• Coherence of the data used across DFID• Information about the data known to selected
individuals is not lost. • Autotmation of routine processes and reports
Page 13
An example of why it might be useful - education
Page 14
MDG 2 - Progress towards universal primary education, Africa PSA countries
0
20
40
60
80
100
Eth
iop
ia
Mo
zam
biq
ue
Ma
law
i
Gh
an
a
DR
C
Nig
eri
a
Ug
an
da
Le
soth
o
So
uth
Afr
ica
Ta
nza
nia
Rw
an
da
Za
mb
ia
Zim
ba
bw
e
Ke
nya
Sie
rra
Le
on
eS
ud
an
Net
enr
olm
ent r
ate,
per
cen
t
■ 1990 starting point■ 2015 targetcurrent position: ● on track ● slightly off track ● seriously off track Note: traffic light results take intermediate data into account
Page 15
MDG 2 - Progress towards universal primary education, Africa PSA countries
0
20
40
60
80
100
Eth
iop
ia
Mo
zam
biq
ue
Ma
law
i
Gh
an
a
DR
C
Nig
eri
a
Ug
an
da
Le
soth
o
So
uth
Afr
ica
Ta
nza
nia
Rw
an
da
Za
mb
ia
Zim
ba
bw
e
Ke
nya
Sie
rra
Le
on
eS
ud
an
Net
enr
olm
ent r
ate,
per
cen
t
■ 1990 starting point■ 2015 targetcurrent position: ● on track ● slightly off track ● seriously off track Note: traffic light results take intermediate data into account
Page 16
MDG 2 - Progress towards universal primary education, Africa PSA countries
0
20
40
60
80
100
Eth
iop
ia
Mo
zam
biq
ue
Ma
law
i
Gh
an
a
DR
C
Nig
eri
a
Ug
an
da
Le
soth
o
So
uth
Afr
ica
Ta
nza
nia
Rw
an
da
Za
mb
ia
Zim
ba
bw
e
Ke
nya
Sie
rra
Le
on
eS
ud
an
Net
enr
olm
ent r
ate,
per
cen
t
■ 1990 starting point■ 2015 targetcurrent position: ● on track ● slightly off track ● seriously off track Note: traffic light results take intermediate data into account
Page 17
MDG 2 - Progress towards universal primary education, Africa PSA countries
0
20
40
60
80
100
Eth
iopi
a
Moz
ambi
que
Mal
awi
Gha
na
DR
C
Nig
eria
Uga
nda
Leso
tho
Sou
thA
fric
a
Tan
zani
a
Rw
anda
Zam
bia
Zim
babw
e
Ken
ya
Sie
rra
Leon
e
Sud
an
Net
enr
olm
ent r
ate,
per
cen
t
■ 1990 starting point■ 2015 targetcurrent position: ● on track ● slightly off track ● seriously off track Note: traffic light results take intermediate data into account
ETH & MOZ had some of the low est rates in 1990 yet are on track to reach 100% by 2015
Although their 1990 position is unknow n, recent progress in TAN, RWA, ZAM yields an 'on track' assessment
Malaw i data show huge progress, but w ith a reversal since 2000. Hence the 'off track' results: on current trends, the target w ould be missed
Page 18
Still looking at NER …
Page 20
That’s the why
The what –
DevInfo v 4.0
Standard indicator selectionGoal/sectorTimeGeography
DevInfo v 4.0
Presentations in tables
DevInfo v 4.0
Presentations in Graphs
DevInfo v 4.0
Presentations in Maps
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Page 44
Next steps
• Internal feedback is very positive• Adding more content• Deploying with a small group of users
• But our needs aren’t unique
• Have you a solution? • Can you help find a solution?