Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
RDM and data sharing landscape: overview for Salford DCC training 20140522L Molloy
Research data management and data sharing: a brief overview of where we are in the UK right now and some main drivers and benefits. Prepared for Salford university Digital Curation Centre training session, 22 May 2014. Contains material from across DCC resources.
Susanna Sansone's talk at the "Beyond Open" Knowledge Dialogues/Open Data Hong Kong event on research data, hosted at the Hong Kong Innocentre on Monday 20 November 2017.
Ross Wilkinson - Data Publication: Australian and Global Policy DevelopmentsWiley
Australia invests $AUD1-2B per annum in research data. Like most countries, it wants to get the best return possible on this data. Europe is spending E1.4B on their open data “pilot”. This means the data should be FAIR: findable, accessible, interoperable, and reusable. Part of this is that data should be routinely “published” and available in a “data repository”. But what does this mean?
Ross Wilkinson
CEO, Australian National Data Service
Presented at the 2015 Wiley Publishing Seminar, 5 November, Melbourne, Australia.
What is research data?
Value and potential of research data and who benefits
What is data sharing? Open/shared/closed models
Benefits of open data
Class discussion: does all data need to be open to get value from it?
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
RDM and data sharing landscape: overview for Salford DCC training 20140522L Molloy
Research data management and data sharing: a brief overview of where we are in the UK right now and some main drivers and benefits. Prepared for Salford university Digital Curation Centre training session, 22 May 2014. Contains material from across DCC resources.
Susanna Sansone's talk at the "Beyond Open" Knowledge Dialogues/Open Data Hong Kong event on research data, hosted at the Hong Kong Innocentre on Monday 20 November 2017.
Ross Wilkinson - Data Publication: Australian and Global Policy DevelopmentsWiley
Australia invests $AUD1-2B per annum in research data. Like most countries, it wants to get the best return possible on this data. Europe is spending E1.4B on their open data “pilot”. This means the data should be FAIR: findable, accessible, interoperable, and reusable. Part of this is that data should be routinely “published” and available in a “data repository”. But what does this mean?
Ross Wilkinson
CEO, Australian National Data Service
Presented at the 2015 Wiley Publishing Seminar, 5 November, Melbourne, Australia.
What is research data?
Value and potential of research data and who benefits
What is data sharing? Open/shared/closed models
Benefits of open data
Class discussion: does all data need to be open to get value from it?
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
High-level Meeting & Workshop on Environmental and Scientific Open Data for Sustainable Development Goals in Developing Countries. Madagascar, 4-6 December 2017
The Academy of Science of South Africa (ASSAf) takes proud in the implementation of this new initiative. We are looking forward working with all African continents in populating this platform with information.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
Presentation on behalf of the SA Weather Service presented during SA National Science Week - The harsh realities of climate change, 29 July to 2 August 2019.
Presented at a NeDICC (Network of Data and Information Curation Communities) meeting, 14 March 2019, CSIR, and at the University of Pretoria and the Carnegie Corporation of New York Capstone Conference, 24-29 March 2019, Kieviets Kroon.
Presented on 30 August 2018: Deployment of Open Data Driven Solutions for Socio-economic Value thorough Good Governance and Efficient Public Service Delivery -
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
1. The African Open Science Platform
Presented by Susan Veldsman
Director: Scholarly Publishing Porgramme
Academy of Science of South Africa (ASSAf)
Kampala Workshop, 25 April 2018
3. Fake Data, Fake Research
http://www.bbc.com/news/science-environment-39357819
4.
5. Trusted Research & Data
• Trust is at the centre of the process of science
• Trust research & researchers who have your
best interest at heart
• Build new research on existing research/data
• To be trusted, it needs to be managed
6. Square Kilometre Array (SKA)
• Data collection on a massive scale
• Telescope array to consist of 250,000 radio
antennas between Australia & SA
• Investment in machine learning and artificial
intelligence software tools to enable data analysis
• 400+ engineers and technicians in infrastructure,
fibre optics, data collection
• Supercomputers to process data (IBM)
• To come: super computer 3x times power of
world’s current fastest computer (Tianhe-2) to cope
with SKA data
8. “Construction of the SKA is due to begin in 2018 and finish
sometime in the middle of the next decade. Data acquisition
will begin in 2020, requiring a level of processing power
and data management know-how that outstretches current
capabilities.
Astronomers estimate that the project will generate 35,000-
DVDs-worth of data every second. This is equivalent to “the
whole world wide web every day,” said Fanaroff.”
10. • African human genomic research; Central node at University of
Cape Town
• Using NetMap to monitor connectivity
• Data transfer: Africa Globus Online (668,622 files transferred
between Rhodes University & UCT; 140TB data transferred from
USA to SA
• Challenges: slow & unstable Internet, unreliable power supply,
continent-wide obsolete computer infrastructure that varies
between medium-scale server infrastructure to a small number of
workstations, with multiple operating systems, lack of centralized,
secure data storage
• Other: database of participants (H3APRDB, REDCap), data analysis
incl. Galaxy, Job Management System, eBiokits, REDCap,
WebProtege, Pipelines for data execution, data repository
(European Genome-Phenome Archive)
11. Open Science Defined
“Open Science is the practice of science in such a
way that others can collaborate and contribute,
where research data, lab notes and other
research processes are freely available, under
terms that enable reuse, redistribution and
reproduction of the research and its
underlying data and methods.” - FOSTER Project,
funded by the European Commission
12. Benefits of open data
• Provide evidence for research conducted
• Collaboration advances science, discovery
• Predict trends & informed decisions
• Drive development, service delivery
• More entrepreneurs – using data in innovative
ways, create jobs
• Have potentially far more outcomes when open,
higher impact
• Democratising research & data towards achieving
2030 Sustainable Development Goals
14. “Several open science activities are underway
across Africa, but a great deal will be gained if, in
the context of developing inter-regional links,
these activities were to be coordinated and
developed through such a coordinating
initiative.” - CODATA
18. African Open Science Platform
• Platform = opportunity to engage in dialogue,
create awareness, connect all, provide continental
view
• Funded by SA Dept. of Science & Technology
through National Research Foundation
• 3 years (1 Nov. 2016 – 31 Oct. 2019)
• Managed by Academy of Science of South Africa
(ASSAf)
• Through ASSAf hosting ICSU Regional Office for Africa
(ICSU ROA)
• Direction from CODATA
http://africanopenscience.org.za/
19. Accord on Open Data in a
Big Data World
• Values of open data in
emerging scientific culture
of big data
• Need for an international
framework
• Proposes comprehensive
set of principles
• FAIR Principles
• Provides framework & plan
for African data science
capacity mobilization
initiative
• Proposes African Platform
Call to Endorse
20. Key Stakeholders
• Global Network of Science Academies (IAP)
• International Council for Science (ICSU)
• The World Academy of Sciences (TWAS)
• Research Data Alliance (RDA)
• NRENs (Internet Service Providers for Education)
• Association of African Universities (AAU)
• Network of African Science Academies (NASAC)
• African Research Councils (incl. DIRISA, funders)
• African Universities
• African Governments
• Other
24. Click to view Initiatives/Country
https://www.targetmap.com/viewer.aspx?reportId=56245
Please note: this is just a preview and data still to be cleaned and
updated and corrected.
26. Policy Framework
• Policy provide guidance & see to well-being of
all citizens - political will
• Policies to address (also see existing policies):
• FAIR Principles
• Raw vs Processed/other data
• Licensing
• Sensitive data
• Intellectual Property Issues
27. Policy Framework
• JKUT (Kenya) Institutional Open Data Policy
• Uganda Draft Open Data Policy
• Madagascar Lobbying for Open Data Policy
• Towards a White Paper on Open Research Data
Strategy in Botswana
• White Paper on Science , Technology and
Innovation in South Africa
• Funder Policy: National Research Foundation
(NRF)(SA)
• OECD Principles & Guidelines for Access to
Research Data from Public Funding
28. Intellectual Property Rights Policy
“In many African countries, intellectual property
protection is undeveloped, ineffective,
expensive and unenforced and in some African
countries there exists uncertainty on protection
of IP and the threat of innovation being stolen
away from inventors.”
https://ipstrategy.com/2016/12/05/a-new-look-at-intellectual-property-and-
innovation-in-africa/
30. Capacity Building Framework
• Data collector vs data user vs data manager
Therefore the following are core aspects to capacity building:
• Research Data Management Planning
• Repositories
• Command Line Interpretation
• Software Development
• Data Organisation
• Data Cleaning
• Data Management & Databases
• Data Analysis & Visualisation (incl. programming)
31. Capacity Building Framework
• Engineers, Statisticians, Data Scientists, Librarians, Data
Curators, Researchers, System Administrators,
Policymakers, Auditors, Data Centre Managers, Data
Architects – Wim Hugo
• Different skills for different categories of data workers
• Existing workshops presented
• Tertiary curricula need to adapt more rapidly
• Never too early to learn to work with data, program
32. Incentives Framework
• Funder requirements changing
• Mechanisms that acknowledge publication of
datasets and to promote data sharing
• How do we deal with difficulties in sharing
data—what are the solutions
• Why is sharing essential
• How do we make sharing successful
• How do we lay the fears down and ensure buy-
in
33. Closing Remarks
• Collaborate & learn from one another –
strength in diversity
• Take ownership & collect/curate data in ethical
way
• Downloaders vs Uploaders
• Trusted & valid data managed in trusted way
• Exploit data for the benefit of society (Min
Naledi Pandor)
• Tell the African story, in an African way
We are living in an increasingly data driven world – facebook, twitter, air bnb, uber
Malaria outbreak 2014-2015
World Economic Forum 2018
How to get rid of fake data
The scale of "fake research" in the UK appears to have been underestimated, a BBC investigation suggests.
Official data points to about 30 allegations of research misconduct between 2012 and 2015.
However, figures obtained by the BBC under Freedom of Information rules identified hundreds of allegations over a similar time period at 23 universities alone.
There are growing concerns around the world over research integrity.
The House of Commons Science and Technology Committee has begun an inquiry into the issue to reassure the public that robust systems are in place in the UK.
Stephen Metcalfe, the committee's chairman, said it was vitally important that people have confidence in research that is paid for by public funds.
"Where research has been found to be fraudulent at a later point it has a big impact on the public - it leads to mistrust," he told BBC News.
"What we want to do is to investigate how robust the mechanisms are for ensuring that research is ethical, it is accurate, it is, to a degree, reproducible."
Growing pressures
Requests by the BBC under Freedom of Information rules show that at least 300 allegations were reported at 23 of the 24 research-intensive Russell Group universities between 2011 and 2016 among staff and research students.
About a third of allegations of plagiarism, fabrication, piracy and misconduct were upheld. More than 30 research papers had to be retracted.
Commenting, a spokesman for the Russell Group said: "Our universities take research integrity seriously and work continuously to help staff and students maintain high standards of research.
"The UK has a global reputation for the quality of our scientific research. This is not least because our members are rigorous in their approach to research integrity."
Mr Metcalfe said the figures obtained by the BBC demonstrated the importance of the MPs' inquiry, but they had to be put in the context of the overall number of papers published.
"We do need to have accurate figures that are available so we can all have confidence that the research is being conducted properly, and when it's not, there is a system that challenges that," he said.
Universities UK, which represents vice-chancellors of universities, was asked to comment on the data obtained by the BBC, but declined.
Research retractions
There are growing pressures on researchers to publish their work and obtain grants. Retractions of scientific papers have increased about ten-fold during the past decade.
The blog, Retraction Watch, reports on retractions of scientific papers.
Co-founder of Retraction Watch, Dr Ivan Oransky, told BBC News: "We do not have a good handle on how much research misconduct takes place, but it's become quite clear that universities and funding agencies and oversight bodies are not reporting even a reasonable fraction of the number of cases that they see."
He said one of the most widely cited surveys suggests 2% of researchers admit to committing something that would be considered misconduct.
"If that's a ball-park figure of 2%, well, the number of cases that we hear about is a miniscule fraction of that," said Dr Oransky.
"Clearly there's a lot that's happening that we don't know about. I would say that any steps that universities can take to begin being more honest and forthright and disclosing these cases would be wonderful."
Regulation
Deliberate research fraud is thought to be extremely rare. However, if it does happen it can have severe consequences, such as risking public health and undermining public trust in research.
There have been calls for a UK regulatory body to oversee publicly funded research, based on models in the US and Denmark.
Image copyrightSPLMr Metcalfe said the idea of some sort of regulator would be explored, although he said "there is no appetite for that in the wider community at the moment".
He said the committee would also be looking at why there is so little official data on research misconduct.
Figures from Research Councils UK are regarded as the most reliable, according to a source.
The body, which represents the UK's seven Research Councils, reported 33 allegations of research misconduct between 2012 and 2015. Of these, five were formally upheld, 20 were dismissed and eight are ongoing.
In addition, Universities UK looked at statements on research misconduct published by 19 universities for the year 2013-14. It found 29 allegations were reported, with seven cases upheld after investigation.
It is not clear whether the figures relate to the same or different cases.
Concordat
In 2012, universities signed up to a concordat to support research integrity.
Under the agreement, universities are encouraged to use transparent, robust and fair processes to handle allegations of misconduct.
However, they are not obliged to publish figures on breaches of research integrity, making the scale of the problem difficult to determine.
An audit by Universities UK found that about 35 of 131 universities published annual statements on allegations of research misconduct that were made available to the public.
The BBC investigation asked 24 universities in England, Wales, Scotland and Northern Ireland within the Russell Group, which focus heavily on research, to reveal figures on allegations of research misconduct for academic years between 2011 and 2016. All but one university complied in full or in part.
A total of 319 cases were reported between 2011 and 2016 among staff and research students. The actual number is likely to be higher as some universities did not provide full figures.
Of these 103 were upheld, 173 were dismissed and 43 are ongoing.
Allegations that were upheld after investigation included:
Falsification of research
Passing off others' work as one's own
Data in a published paper taken from other sources without due acknowledgement
The investigations led to at least 32 research papers being retracted as well as at least three PhD theses. These figures are likely to be an underestimate as some universities could not supply data on retractions.
The first fully assembled SKA dish was unveiled today at a ceremonyin Shijiazhuang, China, by the Vice Minister of the Chinese Ministry of Science and Technology, in thepresence of representatives from the countries involved and the SKA Organisation. The dish is one of two final prototypes that will be tested ahead of production of an early array.
Collaborative projects in Biomedical Sciences – genomics research – catching up with outbreaks, ebola, malaria and more
Bioinformatics legs of H3Africa (Human Heridity and Health in Africa)
Work among 30 institutions, 15 Afrucan countries, 2 partners outside Africa
Trusted ICT Infrastructure required to do business
To get Africa talking to one another
Engineers, Statisticians, Data Scientists, Librarians, Data Curators, Researchers, System Administrators, Policymakers, Auditors, Data Centre Managers, Data Architects – Wim Hugo
