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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
Data Driven World
Fake Data, Fake Research
http://www.bbc.com/news/science-environment-39357819
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
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
Africa participation
• Botswana
• Ghana
• Kenya
• Madagascar
• Mauritius
• Mozambique
• Namibia
• Zambia
“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.”
H3ABioNet (H3Africa)
30 institutions, 15 African countries, 2 partners
outside Africa
• 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)
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
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
Open Data, Open Science &
Research Lifecycle (Foster)
“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
Open Data Repositories (re3data - 16)
http://opendatabarometer.org/?_year=2016&indicator=ODB
https://index.okfn.org/place/#map
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/
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
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
Database Experts & Initiatives
800+
Landscape Survey: Countries & Initiatives
567
Concentration of Activities
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.
AOSP Focus Areas
Policy Infrastructur
Capacity
Building
Incentives
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
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
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/
African NRENs
Source: https://www.geant.org/News_and_Events/PublishingImages/
WorldBank_Map2.jpg
• Cluster 1: Southern and
Easter Africa-
UbuntuNet Alliance
• Cluster 2: Western and
Central Africa-WACREN
• Cluster 3: North Africa-
--Asren
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)
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
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
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
http://internationaldataweek.org/
Thank you!
Susan Veldsman
susan@assaf.org.za
http://africanopenscience.org.za

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The African Open Science Platform/Susan Veldsman

  • 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
  • 7. Africa participation • Botswana • Ghana • Kenya • Madagascar • Mauritius • Mozambique • Namibia • Zambia
  • 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.”
  • 9. H3ABioNet (H3Africa) 30 institutions, 15 African countries, 2 partners outside Africa
  • 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
  • 13. Open Data, Open Science & Research Lifecycle (Foster)
  • 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
  • 15. Open Data Repositories (re3data - 16)
  • 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
  • 21. Database Experts & Initiatives 800+
  • 22. Landscape Survey: Countries & Initiatives 567
  • 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.
  • 25. AOSP Focus Areas Policy Infrastructur Capacity Building Incentives
  • 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/
  • 29. African NRENs Source: https://www.geant.org/News_and_Events/PublishingImages/ WorldBank_Map2.jpg • Cluster 1: Southern and Easter Africa- UbuntuNet Alliance • Cluster 2: Western and Central Africa-WACREN • Cluster 3: North Africa- --Asren
  • 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

Notes de l'éditeur

  1. 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
  2. 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.
  3. 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.
  4. 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
  5. Trusted ICT Infrastructure required to do business
  6. To get Africa talking to one another
  7. Engineers, Statisticians, Data Scientists, Librarians, Data Curators, Researchers, System Administrators, Policymakers, Auditors, Data Centre Managers, Data Architects – Wim Hugo