Extended Title: Appointment of a service provider with background in spatial statistics to support the Analysis Platform for the National Invasive Alien Plants Survey (NIAPS)
Appointment of a service provider with background in spatial statistics to support the Analysis Platform for the National Invasive Alien Plants Survey (NIAPS)
Issuer: National: National Research Foundation: SA ENVIRONMENTAL OBSERVATION NETWORK
Bid Number: NRF/ SAEON/ HDWSUPP/ 2017
Bid Description: Appointment of a service provider with background in spatial statistics to support the Analysis Platform for the National Invasive Alien Plants Survey (NIAPS).
Bids are invited for a 3 –year period, with initial appointment for 1 year.
Subsequent renewals will depend on availability of funding to continue the project.
Name of Institution: National: National Research Foundation: SA ENVIRONMENTAL OBSERVATION NETWORK
Place where goods, works or services are required:
SAEON has seven offices countrywide, with a National Office in Pretoria.
The hardware and services requested in this bid will be supplied at the SAEON offices in Foretrust Building, Martin Hammerschlag Way, Cape Town, or to the SAAO, Liesbeeck Parkway, Observatory, Cape Town.
Closing Date / Time: 20 April 2017 / 11:00am
Contact Person: Lawrence Matsena
Telephone number: 012 349 7720
FAX Number: 012 349 7719
Where bid documents can be obtained: Website: www.saeon.ac.za
SAEON National Office The Woods,
Ground Floor Persequor Technopark,
Where bids should be delivered:
SAEON National Office The Woods,
Ground Floor Persequor Technopark,
A compulsory / Optional briefing session will be held on: N/A
The National Invasive Alien Plant Survey (NIAPS) is a long-term invasive alien plant monitoring programme (established in 2005) that is funded by the Department of Environmental Affairs. Support services in spatial statistics are required with special emphasis on:
- Experience in incomplete and unbalanced factorial experimental designs which is almost always the case within random sampling on a national extent.
- An extended experience in data mining within huge national data sets that includes large amounts of remotely sensed data at a range of spatial and temporal scales.
- Comprehensive knowledge of systematic distributed computing during implementation of statistical and simulation models within huge data (‘Big Data’).
- This person is to support the programme in terms of the necessary data preparation that comprises a comprehensive knowledge of environmental data and plant communities which is cardinal during the extraction of tree cover from aerial photography.
- Potential opportunities and guidance for publications and presentations of research in professional journals and to the scientific community must be provided and participation is strongly recommended.
- The requirement emphasis is on experience, ability and proven participation in required projects.
- The successful bidder will be required to perform system maintenance, optimisation, and model or algorithm improvement/ execution on behalf of DEA and ARC.
- A minimum qualification of a national diploma in natural science to enable a sound understanding of the application of spatial statistics within a natural/semi-natural environment.
1. Domain Experience
a. A minimum of 10 years of ecological and agricultural field surveys within a natural/semi-natural environment that includes:
i. Survey designs based on sound statistical principles
ii. Conducting actual surveys
iii. Data analysis
iv. Recommendations to relevant industry based on results
b. Experience in Invasive alien plant (IAP) surveys: NRF/SAEON/HDWSUPP/2017 Page 17 of 46 Initials:
i. A minimum of 10 years of experience is required in the IAP field.
ii. Design and implement IAP surveys at a range of spatial scales.
iii. Survey simulations at a range of spatial scales that is applicable to different target populations.
iv. Have conducted at least three national level IAP field surveys.
v. Data analysis of survey results.
vi. Publication of survey results to at least a progress report level.
2. Technology Transfer
a. A minimum of 10 years of technology transfer that includes:
b. Field survey design recommendations to other scientists
c. Statistical procedures and data analysis courses
3. Data Analysis, Processing and Management
a. Must have at least 15 years’ experience performing advanced quantitative data analyses.
b. Be able to determine the best methods of integrating data from several different sources and formats for use in Advanced Data Analyses.
c. Employ sophisticated analytics programs, machine learning, image enhancement and statistical methods to prepare and clean data for use in predictive and prescriptive modelling.
d. Implementing new data sources and determine how best to use the data in advanced analyses.
e. Proven ability to apply advanced statistical methodologies that must include:
i. Data mining procedures,
ii. Neural networks that includes a detailed knowledge and application of self-organizing maps, probability networks and machine learning.
iii. Advanced statistical models in a spatial environment that includes supervised and unsupervised classification techniques.
iv. Development, validation, and cross-validation of predictive models.
v. Proven ability to apply mathematical operations to such tasks as cluster analytics, sampling theory and design of surveys, analysis of variance, correlation techniques, and factor analysis.
f. Proven ability to design, apply and optimize advanced simulation modelling methodologies and techniques.
g. Proven ability to manipulate, analyse and interpret terabytes of data and therefore fully comprehend the concept of Big Data processing within a CPU, GPU, parallel and distributed computing environment.
h. Temporal data analysis capacity and the ability to demonstrate the application of time series analysis to a range of fields within the natural environment.
i. The ability to incorporate results within a database environment and apply data visualization techniques.
j. Proven ability to organize findings and translate into actionable insights using original thinking.
4. Software knowledge and engineering skills (distributed computing, algorithms and data structures):
a. Provident in:
i. Mathworks Matlab application and scripting in a single processor, GPU, parallel and distributed environment.
ii. ESRI ArcGIS that includes Python scripting.
iii. DELL Statistical
iv. Microsoft Windows server
b. Computer system designs within a distributed computing environment that includes the optimization between hardware and processing requirements combined with software solutions.
c. The ability to provide guidance regarding required data processing
NRF/SAEON/HDWSUPP/2017 Page 18 of 46 Initials: applications related to specific hardware and software system requirements as well as the operationalization of such a system.
a. Excellent attention to detail.
b. Interpret and communicate analytic results to analytical and non-analytical scientific partners and executive decision makers.
c. Develops innovative approaches to accomplish short- and long-term objectives.
d. Willingness to be proactive in sharing thoughts and opinions.
e. Capacity to communicate technically and in laymen’s terms.
f. Comfortable interacting with all levels of the organization.