1. Ecological research data and data sharing
complexities in Uganda
Simon Takozekibi Nampindo
April 25th, 2018
2. Presentation flow
• WCS Data
• Products generated
• Ecological and socioeconomic data sources in
Uganda
• Data access constraints and challenges
• Strategies and best practices
• Recommendations to government
3. VISION:
WCS envisions a world where wildlife thrives in healthy lands and seas, valued by
societies that embrace and benefit from the diversity and integrity of life on earth.
MISSION:
WCS saves wildlife and wild places worldwide through science, conservation
action, education, and inspiring people to value nature.
GOAL:
The conservation of more than 50 percent of the world’s biological diversity while
ensuring a positive impact on millions of people globally.
www.wcsuganda.org www.wcs.org www.albertinerift.org
4. WCS has been
supporting conservation
in Uganda since 1957
Current focus : Greater
Virunga Landscape,
Murchison-Semliki
Landscape and the
Kidepo Landscape.
https://uganda.wcs.org/
6. Taxa and sites with biological data
Taxon Location Recent Survey
period
Partners
Plants KVNP, Otzi and Agoro Agu FR, East Madi WR, QENP, and
Murchison-Semliki Landscape (i.e. MFNP, Kabwoya, Kaiso-Tonya,
Budongo, Bugungu, Karuma, Bugoma, Kagombe, Wambabya,
Bujawe, Corridor forests), QENP, Kyambura, RMNP, Kasyoha-
Kitomi, Kalinzu, Maramagambo (QECA), Semliki Forest, BINP,
Echuya
2014-2017 UWA, NFA
Makerere
University
(CONUS),
NBDB
Birds KVNP, East Madi WR, QENP, and Murchison-Semliki landscape, L.
Albert, Edward, MGAHINGA, BINP, RMNP
2014-2017 NBDB, UWA,
NFA
Small mammals Murchison-Semliki landscape 2014-2015 CONUS, Field
Museum,
Chicago, UWA
Amphibians and
reptiles
Murchison-Semliki landscape 2014-2015 CONUS, UWA
TRENTO
Butter flies and
dragon flies
Murchison-Semliki landscape 2014-2015 CONUS, UWA,
NBDB
Large and medium
mammal surveys
QECA, MFNP, KVNP, BINP, Budongo, Kabwoya, Kaiso-Tonya,
Bugungu, Karuma, Bugoma, KNP, RMNP, EAST MADI
1957- 2015 UWA, NFA
Fisheries L. George & Kazinga Channel (2007/8), L. Albert Catchment (2014) 2014 NaFIRRI
7. Species- specific surveys and sites
Species Location Period of
survey
Partners
Grey crowned crane Country-wide survey, forest
corridors in Murchison-Semliki
landscape
2006, 2016 NatureUganda
Lions QENP, MFNP, KVNP 2010 UWA
Crocodiles
Crocodylus niloticus
MFNP, KVNP 2009-2011 UWA, Mathias
Behangana
Chimpanzees Albertine Rift forests, KK, Kalinzu-
Maramagambo CFRs,
Corridor forests,
1999-2002;
2008, 2009
JGI, WCS, UWA
Mountain Gorillas Bwindi, and Mgahinga UWA, IGCP
Elephants KVNP, QENP, MFNP, Karenga WR,
Lipan
2014 UWA, WCS
8. Landscape level data
Data Type Location Period of
survey
Partners
Long term ecological data
Global Observation Research
Initiative in Alpine Environments
(GLORIA)
(http://www.gloria.ac.at/)
Rwenzori Mountains
NP, Mabira Central
Forest Reserves
2008 ITFC
TEAM
(http://www.teamnetwork.org/)
Bwindi INP, Virunga
Massif
2009 ITFC, CI
Climate data – weather
stations in AR
MFNP, BINP,
KVNP, QENP, SNP
2011 UWA,
ASU
Socioeconomic data AR 2003,
2006-2010
CARE int.,
17. Key sites of conservation importance for
endemic and threatened species in
Uganda
National Red list
assessment for
Uganda
(http://www.nati
onalredlist.org/ca
tegory/library/reg
ion/africa/)
18. DATA SHARING: A COMPLEX
SUBJECT AND VALUABLE
COMMODITY
• The senate committee on commerce and
judiciary spent 2 days discussing data
management, sharing and protection with Mark
Zuckerberg, Founder and CEO, FACEBOOK
20. Data sources
• National data holders
• Biomass data - (NFA)
• Oil & Gas data (Petroleum
Authority)
• Citizens data - National
Information Registration
Authority (NIRA)
• National Population and housing
census data – UBOS
• Biodiversity data (UWA)
• NBDB, DEM, MAK
• NEMA (EIAs, environmental data)
• Public Universities and Research
institutions
• UNCST
• UNRA
• URA (export and import,
revenue)
• Uganda National
Meteorology Authority
• Uganda Police – crime
data
• Judiciary – cases in formal
courts
• Indigenous
technical/ecological
knowledge – indigenous
peoples and Ugandans in
general
• NGOs,
• Private companies
21. Challenges
• Lengthy process, highly bureaucratic, costly
• Most Data is not centrally managed – all over the place
• Not standardized, varied scales (spatial and temporal)
and formats
• Citation/attribution inadequacies
• Legalities and ethical issues – confidential and sensitive
data
• Donor conditions/restrictions/confidentiality terms
• Barriers to effective data sharing and preservation are
deeply rooted in the practices and culture of the
research process as well as the researchers ourselves
• Restrictive Intellectual Property Rights (IPR)
• Competition from researchers and institutions
22. Strategies/best practices
• Some data is commercially available other data is by
request
• MoUs for data management and sharing plan
• Data sharing agreements
• Collaborations and Partnerships
• Provision of data to NBDB & other databases at
Museums, universities, herbaria, GBIF
• Contracts with data holders
• Purchase
• IP negotiations with donors/sponsors
23. Recommendations
• Government should create an open access policy to
publically funded data
• Government commit funding for data collection to
increase
• Develop and operationalize data sharing strategy, e.g. via
an institutional repository, data centre, website
• Data Handling Procedures in Government
• Government develop a clear policy on data availability
and access from donor sponsored data collection
managing and sharing data that apply to projects or the
centre
• Relax the IPRs for data and information of national and
global importance (e.g. IUCN red lists, GBIF) and
protection of IPRs for sensitive information