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Introducing the SAEON uLwazi Node’s new Data Science team members
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SAEON’s uLwazi Node has been growing capacity and skill sets with a number of recent recruits, including in the newly formed Data Science team.
With a full complement of data scientists, the team is uniquely positioned within SAEON to assist South Africa to respond effectively to long-term global change.
The Data Science team consists of Dr Claire Davis-Reddy (lead), Hayden Wilson, Amelia Hilgart and three new members, which include two GIS analysts and one data scientist:
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Keneilwe Hlahane has a BSc honours in Geographic Information Systems (GIS) and an MSc in Ocean and Atmosphere Science from the University of Cape Town (UCT).
She was awarded the 2017 Esri South Africa GIS Young Scholar Award and the 2017 Department of Science and Technology (DST) Women in Science Award for her master's research. Her interests are in GIS and remote sensing of vegetation and water quality.
Keneilwe previously worked at the South African National Biodiversity Institute (SANBI) as part of the South African national vegetation mapping team. She was attracted to SAEON because of its environmental and Earth observation science research.
She joins SAEON as a GIS technician/analyst in the Data Science team. She will be working in the South African Risk and Vulnerability Atlas project where her responsibilities include the classification of impacts, risks and vulnerabilities from various data sets.
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Bonolo Mokoatsi is a master's candidate with a strong background in GIS, remote sensing and environmental management systems/techniques.
Her academic training also involved renewable energy technologies, including the energetic use of biomass.
She recently joined SAEON's Data Science team, following her NRF-DST internship at the CSIR. Her interests lie mainly in vegetation studies and natural resource management, using remote sensing techniques to monitor changes over time and detect possible environmental threats.
Bonolo was attracted to SAEON’s data-driven environment and research support (prospects, too). Her role as GIS analyst allows her to apply her acquired skills to explore different data sets and analysis techniques for the betterment of environmental observations in the interest of environmental sustainability.
She describes her involvement in the Renewable Energy Atlas as a ‘monumental task’ and is excited about the learning curves that come with it!
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Dr Marc Pienaar joined SAEON’s uLwazi Node as a senior systems developer in mid-March 2019. Marc has a PhD in Electrical Engineering from UCT, specialising in wavelet analysis, time series classification, and other machine-learning and data-mining techniques.
Prior to joining SAEON, he was a senior scientist in the Global Change and Ecosystems Dynamics group at the CSIR, with over 14 years of experience in model development, data analysis, and the design and development of various decision-support tools and platforms. He enjoys working with Earth and environmental science data and finding novel ways to extract information from the feature space, but also to develop algorithms for the manipulation, resampling or transformation of such data.
“Many of us are pre-biased in our analytical approach and tend to choose the statistics or results that best match our assumptions or desired outcomes. I believe end-users (scientists, funders and decision-makers) should be afforded the ability to navigate and explore relationships in the data themselves, through the development of function-rich visualisation and analytical interfaces. Data science is not only about integrity, but also information discovery using multi-disciplinary methods. This is what the uLwazi Node is all about, and thus presents a great opportunity to further develop skills in these areas,” says Marc.
“Additionally, there is the possibility to work with various data types and multidisciplinary teams from other SAEON nodes, which is, to a large extent, what attracted me to this job,” he explains.
As senior systems developer, Marc works in both the Data Science and Systems Development teams. His responsibilities are mostly back-end development, including the development of data pipelines and analysis and processing algorithms; building analytical systems and visualisation and decision-support interfaces (for instance profiling tools for the third phase of the South African Risk and Vulnerability Atlas); developing systems for data quality assurance; audio-visual processing and automated feature identification; and developing miscellaneous analytical end-user tools (such as software plugins [e.g. for QGIS] or standalone applications for analyses of data from digital atlases and other data products).
About the Data Science team
The team is one of four core teams working together to host and disseminate scientific data and to provide decision-support tools for various government departments based on that scientific evidence.
The mission of the Data Science team is to conceptualise, design and develop new approaches to decision and policy support, conduct research into data infrastructure and interoperability, and develop new tools, systems and data products to assist with translation of scientific evidence into societal benefit.
The integration and publishing of data products and systems in an understandable and accessible manner will facilitate the decision-making process and allow for a defensible response to a range of social, economic and environmental drivers.
The Data Science team will be primarily involved in three funded projects between 2019 and 2022:
- National Climate Change Information System (NCCIS): integration of systems commissioned by the then Department of Environmental Affairs (DEA) from SAEON and from third-party systems developers, locally and abroad.
- South African Risk and Vulnerability Atlas (SARVA) version 3: aims to make research into characterising and understanding global change accessible and usable to policy- and decision-makers on a local scale.
- Renewable Energy Atlas: updates to BioEnergy Atlas, inclusion feasibility and viable projects for other renewables, updates to carbon distributions and invasive alien plants/bush encroachment data sets.
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