This presentation was given by Christian Reimsbach-Kounatze of the OECD at the CERI Conference on Innovation, Governance and Reform in Education on 5 November 2014 during session 6.b: The Role of “Big Data”.
Firms, Collective Intelligence and Sustainability : MIT Crowds and Climate Co...Peter C. Evans, PhD
Can firms harness collective intelligence and advance sustainability goals? How large is the intersection between digital tools that permit expanding collaborative networks and reducing the time and cost of innovation?
These were some of the areas discussed at the Crowds and Climate conference held at MIT on November 6-8th organized by the MIT Center for Collective Intelligence.
Peter Evans, Vice President at Center for Global Enterprise, participated in a plenary panel with Nancy Pfund Founder and Managing Partner, DBL Investors and Otto Scharmer, Senior Lecturer, MIT; Founding Chair, Presencing Institute. Jason Jay, Director, MIT Sloan Sustainability Initiative served as the session moderator.
Evans’ presentation focused on the how firms can leverage the power of internal networks through the use of digital platform tools and crowdsourcing.
In the third part of the workshop series Smart Policies for Data, we will focus on two central building blocks – interoperability and balanced data sharing.
The presentations of the event:
- Szymon Lewandowski, DG CONNECT, European Commission
- Marko Turpeinen, CEO, 1001 Lakes
- Lars Nagel, CEO, International Data Spaces Association
To be of value, big data must often flow across national borders from one country to another. Mandated local data storage of consumer as well as industrial data can restrict or prevent these data flows. This presentation examines restrictive data trade policies and the implications for companies and countries.
Firms, Collective Intelligence and Sustainability : MIT Crowds and Climate Co...Peter C. Evans, PhD
Can firms harness collective intelligence and advance sustainability goals? How large is the intersection between digital tools that permit expanding collaborative networks and reducing the time and cost of innovation?
These were some of the areas discussed at the Crowds and Climate conference held at MIT on November 6-8th organized by the MIT Center for Collective Intelligence.
Peter Evans, Vice President at Center for Global Enterprise, participated in a plenary panel with Nancy Pfund Founder and Managing Partner, DBL Investors and Otto Scharmer, Senior Lecturer, MIT; Founding Chair, Presencing Institute. Jason Jay, Director, MIT Sloan Sustainability Initiative served as the session moderator.
Evans’ presentation focused on the how firms can leverage the power of internal networks through the use of digital platform tools and crowdsourcing.
In the third part of the workshop series Smart Policies for Data, we will focus on two central building blocks – interoperability and balanced data sharing.
The presentations of the event:
- Szymon Lewandowski, DG CONNECT, European Commission
- Marko Turpeinen, CEO, 1001 Lakes
- Lars Nagel, CEO, International Data Spaces Association
To be of value, big data must often flow across national borders from one country to another. Mandated local data storage of consumer as well as industrial data can restrict or prevent these data flows. This presentation examines restrictive data trade policies and the implications for companies and countries.
Presentation on Open Data delivered by Paul Wilkinson at the COMIT Community Day held on September 8th at Hemel Hempstead, hosted by Sir Robert McAlpine
For a country like Finland, which is full of innovations and startups, Gaia-X is a gateway for reaching the next step of the data economy ladder. The potential of this groundbreaking initiative is enormous and far-reaching.
Gaia-X is the answer to a massive demand for safe, secure and sovereign data across Europe. By merging hundreds of different organisations in different domain and from across the globe in a single endeavour, Gaia-X combines challenging use cases with innovative solutions to bring the most value out of the European data economy.
Gaia-X project is accelerating rapidly with the launch of Gaia-X regional hubs. We are pleased to invite you to our Gaia-X for Finland – Hub launch event.
During the event, you will learn about the role of a Gaia-X as a game-changer for data-driven businesses, hear about the strategy and operational model of the Finnish Gaia-X Hub and get insights from companies already involved in Gaia-X.
The event page: https://www.sitra.fi/en/events/gaia-x_for_finland_hub_launch/
Presentations:
Jaana Sinipuro, Project Director, Sitra
Hubert Tardieu, Independent Board Member in charge of relationship with governments
Lars Albäck, CEO, Vastuu Group
Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019...IDC4EU
This is the slide-deck of the community event held on November 14, 2019 in Brussels, titled "Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019". It includes the presentations given by the speakers.
OECD Digital Economy Outlook 2017: Setting the foundations for the digital tr...innovationoecd
The Digital Economy Outlook 2017 shows how Internet infrastructure and usage varies across countries and firms in the OECD area. It looks at policy implications of the digital transformation as well as a wide array of trends. Report available at http://oe.cd/deo2017 - See also the OECD Going Digital project: www.oecd.org/going-digital
Collaboraton Across Digital Industries Competition - Maurizio Pilu, TSBChinwag
The Technology Strategy Board's (TSB) Maurizio Pilu's presentation covering the £18m Collaboration Across Digital Industries competition.
The presentation gives an overview of the tensions the competition is addressing and sheds light on the scope and scale of proposals.
More information about this competition is available http://chinwag.com/events/pfi
This was originally presented at the Partnering for Innovation 2010 event in Glasgow.
Keynote: Data isn’t just valuable, it’s going to save the planet! Miles CheethamAlan Quayle
TADSummit EMEA Americas 2021 Keynote: Data isn’t just valuable, it’s going to save the planet!
Miles Cheetham, Co-Chair Open Energy Steering Group, developing standards-based marketplaces for environmental & financial data.
How Open Banking proved how we could share data securely at scale (and we’ve now realised that it’s one use case of many)
Open Energy showed how the approach and infrastructure is transferable to other sectors (and that interoperability across sectors is possible)
What else is possible? (when you start thinking about what you can do with data, you realise the wealth of use cases and problems you can solve)
How data will lead us to better decisions (informing corporate and consumer behaviour, investments/use of capital etc.)
What we need to do to make this real? (what government, treasuries, regulators and industry need to do)
EDF2014: Kush Wadhwa, Senior Partner, Trilateral Research & Consulting: Addre...European Data Forum
Selected Talk by Kush Wadhwa, Senior Partner, Trilateral Research & Consulting at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Addressing risks and opportunities engendered by big data: The BYTE project
Asia is second only to North America in generating large successful platform companies. The growing significance of platform companies is perhaps inevitable, given the size and scale of Asia in the global economy, a large and growing middle class, rapidly growing internet usage and a knack for quickly trying and adapting new business models. Platforms such as Tencent, Alibaba, Naver, Flipkart and Garena — to name but a few — are becoming important vehicles to efficiently provide services to the region’s large and growing middle class as it embraces digital technology. The survey identified 62 major platform companies operating across Asia, with a market capitalization of $800 million or more. The final list of companies is diverse. The companies serve 10 major industry sectors, with headquarters in 18 different cities. They have grown dramatically in the past decade, with a significant number of platforms now servicing hundreds of millions of users. These companies have also attracted significant investor attention. The market value of the 62 companies now exceeds $1.1 trillion, and they are having a growing influence on shaping markets throughout the region.
Presentation on Open Data delivered by Paul Wilkinson at the COMIT Community Day held on September 8th at Hemel Hempstead, hosted by Sir Robert McAlpine
For a country like Finland, which is full of innovations and startups, Gaia-X is a gateway for reaching the next step of the data economy ladder. The potential of this groundbreaking initiative is enormous and far-reaching.
Gaia-X is the answer to a massive demand for safe, secure and sovereign data across Europe. By merging hundreds of different organisations in different domain and from across the globe in a single endeavour, Gaia-X combines challenging use cases with innovative solutions to bring the most value out of the European data economy.
Gaia-X project is accelerating rapidly with the launch of Gaia-X regional hubs. We are pleased to invite you to our Gaia-X for Finland – Hub launch event.
During the event, you will learn about the role of a Gaia-X as a game-changer for data-driven businesses, hear about the strategy and operational model of the Finnish Gaia-X Hub and get insights from companies already involved in Gaia-X.
The event page: https://www.sitra.fi/en/events/gaia-x_for_finland_hub_launch/
Presentations:
Jaana Sinipuro, Project Director, Sitra
Hubert Tardieu, Independent Board Member in charge of relationship with governments
Lars Albäck, CEO, Vastuu Group
Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019...IDC4EU
This is the slide-deck of the community event held on November 14, 2019 in Brussels, titled "Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019". It includes the presentations given by the speakers.
OECD Digital Economy Outlook 2017: Setting the foundations for the digital tr...innovationoecd
The Digital Economy Outlook 2017 shows how Internet infrastructure and usage varies across countries and firms in the OECD area. It looks at policy implications of the digital transformation as well as a wide array of trends. Report available at http://oe.cd/deo2017 - See also the OECD Going Digital project: www.oecd.org/going-digital
Collaboraton Across Digital Industries Competition - Maurizio Pilu, TSBChinwag
The Technology Strategy Board's (TSB) Maurizio Pilu's presentation covering the £18m Collaboration Across Digital Industries competition.
The presentation gives an overview of the tensions the competition is addressing and sheds light on the scope and scale of proposals.
More information about this competition is available http://chinwag.com/events/pfi
This was originally presented at the Partnering for Innovation 2010 event in Glasgow.
Keynote: Data isn’t just valuable, it’s going to save the planet! Miles CheethamAlan Quayle
TADSummit EMEA Americas 2021 Keynote: Data isn’t just valuable, it’s going to save the planet!
Miles Cheetham, Co-Chair Open Energy Steering Group, developing standards-based marketplaces for environmental & financial data.
How Open Banking proved how we could share data securely at scale (and we’ve now realised that it’s one use case of many)
Open Energy showed how the approach and infrastructure is transferable to other sectors (and that interoperability across sectors is possible)
What else is possible? (when you start thinking about what you can do with data, you realise the wealth of use cases and problems you can solve)
How data will lead us to better decisions (informing corporate and consumer behaviour, investments/use of capital etc.)
What we need to do to make this real? (what government, treasuries, regulators and industry need to do)
EDF2014: Kush Wadhwa, Senior Partner, Trilateral Research & Consulting: Addre...European Data Forum
Selected Talk by Kush Wadhwa, Senior Partner, Trilateral Research & Consulting at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Addressing risks and opportunities engendered by big data: The BYTE project
Asia is second only to North America in generating large successful platform companies. The growing significance of platform companies is perhaps inevitable, given the size and scale of Asia in the global economy, a large and growing middle class, rapidly growing internet usage and a knack for quickly trying and adapting new business models. Platforms such as Tencent, Alibaba, Naver, Flipkart and Garena — to name but a few — are becoming important vehicles to efficiently provide services to the region’s large and growing middle class as it embraces digital technology. The survey identified 62 major platform companies operating across Asia, with a market capitalization of $800 million or more. The final list of companies is diverse. The companies serve 10 major industry sectors, with headquarters in 18 different cities. They have grown dramatically in the past decade, with a significant number of platforms now servicing hundreds of millions of users. These companies have also attracted significant investor attention. The market value of the 62 companies now exceeds $1.1 trillion, and they are having a growing influence on shaping markets throughout the region.
Data Science For Social Good: Tackling the Challenge of HomelessnessAnita Luthra
A talk presented at the Champions Leadership Conference Series - leveraging data provided by New York City’s Department of Homeless Services, software vendor Tibco partnered with SumAll.Org to help tackle the societal challenge of homelessness in New York City.
Intuit 2020 Report: The New Data DemocracyIntuit Inc.
Authored by Emergent Research. Explores emerging trends that are driving a data revolution. More information at: http://network.intuit.com/2012/12/13/the-coming-era-of-big-data-for-the-little-guy/
US National Archives & Open Government Data3 Round Stones
Presentation to the US National Archives on the use of Linked Data by US Government. Linked Data increases access and re-use opportunities for publishers and data consumers.
BigData & Supply Chain: A "Small" IntroductionIvan Gruer
In the frame of the master in logistic LOG2020, a brief presentation about BigData and its impacts on Supply Chains at IUAV.
Topics and contents have been developed along the research for the MBA final dissertation at MIB School of Management.
Convergence of AI, IoT, Big Data and Blockchain: A Review.
Kefa Rabah .
Mara Research, Nairobi, Kenya .
Abstract
Data is the lifeblood of any business. Today, big data has applications in just about every industry – retail, healthcare,
financial services, government, agriculture, customer service among others. Any organization that can assimilate data
to answer nagging questions about their operations can benefit from big data. In overall, the demand for big data
transcend across all sectors and business. Those who work to understand their customers’ business and their problems
will be able to proactively identify big data solutions appropriate to their needs, and thus gain competitive advantage
over their competitors. Job demand for people with big data skill-set is also in the rise especially professional,
scientific and technical services; information technology; manufacturing; and finance and insurance; and retail.
DevOps is baseless without the cloud. IoT needs cloud to operate efficiently, for computing is required by the cloud
operate efficiently. AI remained only as model up until the advent of big data. Blockchain and related distributed
ledger technologies are disrupting the technology sector as we know it. The confluence of technologies is just
inevitable and often they are beneficial especially today when usher in the 4th industrial revolution (Rabah, 2017a)
and the forth coming machine economy (Rabah, 2018). More-so, data is a key ingredient of approaches to developing
AI and machine learning, which are now being applied to a wide variety of uses, from stock trading to chatbots to
self-driving cars. There is barely a business or human activity today that is not considered as a target for AI in future
years and decades.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Andreas Schleicher presents at the launch of What does child empowerment mean...EduSkills OECD
Andreas Schleicher presents at the launch of ‘What does child empowerment mean today? Implications for education and well-being’ on the 15 May 2024. The report was launched by Mathias Cormann, OECD Secretary-General and can be found here: https://www.oecd-ilibrary.org/education/what-does-child-empowerment-mean-today_8f80ce38-en
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
Andreas Schleicher, Director for Education and Skills at the OECD, presents at the webinar
No Child Left Behind: Tackling the School Absenteeism Crisis on 30 April 2024.
AI & cheating on high-stakes exams in upper secondary - Introduction by Shivi...EduSkills OECD
Shivi Chandra, Analyst at the OECD, presents slides to set the scene at the OECD Education Directorates Webinar 'AI and cheating in education: How can we safeguard the integrity of exams?' on 17 April 2024
Advancing Gender Equality The Crucial Role of Science and Technology 4 April ...EduSkills OECD
Eric Charbonnier, Analyst in the Innovation and Measuring Progress Division, OECD presents at the webinar 'Advancing Gender Equality: The Crucial Role of Science and Technology' on 4 April 2024.
Managing Choice, Coherence and Specialisation in Upper Secondary Education - ...EduSkills OECD
Camilla Stronati, Junior Policy Analyst, Transitions in Upper Secondary Education project, Directorate for Education and Skills, OECD, presents at the webinar 'The art of balancing curricular choice in upper secondary education' on 29 February 2024
Andreas Schleicher - 20 Feb 2024 - How pop music, podcasts, and Tik Tok are i...EduSkills OECD
Andreas Schleicher presentation at the OECD webinar 'Lights, Camera, Fluency: How pop music, podcasts, and Tik Tok are impacting English language learning' on 20 February 2024 which launched the OECD report 'How 15-Year-Olds Learn English: Case Studies from Finland, Greece, Israel, the Netherlands and Portugal'
Andreas Schleicher - Making learning resilient in a changing climate - 8 Febr...EduSkills OECD
Andreas Schleicher presents at the OECD webinar 'Making learning resilient in a changing climate ' on 8 February 2024. The discussion was based on the OECD Skills Outlook 2023 publication, ‘Skills for a Resilient Green and Digital Transition’.
Jordan Hill - Presentation of Engaging with education research- With a little...EduSkills OECD
Jordan Hill from the OECD Strengthening the Impact of Education Research project presents at the OECD webinar 'Engaging with education research- With a little help from the system' on 26 January 2024.
RETHINKING ASSESSMENT OF SOCIAL AND EMOTIONAL SKILLS by Adriano Linzarini OEC...EduSkills OECD
Adriano Linzarini (Lead Analyst, Rethinking Assessment of Social and Emotional Skills project, OECD) presents at the OECD webinar 'Social and Emotional Learning – does it make a difference in children’s lives?' on 17 January 2024
Moving up into upper secondary by Hannah Kitchen - OECD Education Webinar 23N...EduSkills OECD
Hannah Kitchen, Project Leader of Above and Beyond: Transitions in Upper Secondary Project at the OECD presents at the webinar Moving up into upper secondary on the 23 November 2023
Ana Carrero -European year of skills – EU updateEduSkills OECD
Ana Carrero, Deputy Head of Unit, DG EMPL, European Commission, presents European year of skills – EU update at the webinar Charting the Future of Vocational Education and Training: Insights and Strategies for Tomorrow’s Workforce on 26 October 2023
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
1. DATA-DRIVEN INNOVATION
FOR EDUCATION
5 November 2014
CERI CONFERENCE ON
INNOVATION, GOVERNANCE AND REFORM IN EDUCATION
Christian.Reimsbach-Kounatze@oecd.org
Directorate for Science, Technology and Innovation (DSTI)
2. 1. Why should we care about “big data” or
data-driven innovation (DDI)?
2. What is really new about it?
3. What are the key opportunities?
4. What are the key challenges?
2
Structure
4. A lot of “big data” buzz
• “Data is the new oil.” Andreas Weigend, Stanford (ex Amazon)
• “The future belongs to companies and people that turn
data into products”, Mike Loukides, O’Reilly Media
“Why big data
is a big deal”
InfoWorld – 9/1/11
“Keeping Afloat
in a Sea of 'Big
Data”
ITBusinessEdge – 9/6/11
“The challenge–
and opportunity–
of big data”
McKinsey Quarterly—5/11
“Getting a Handle
on Big Data with
Hadoop”
Businessweek-9/7/11
“Ten reasons why
Big Data will
change the travel
industry”
Tnooz -8/15/11
“The promise of
Big Data”
Intelligent Utility-8/28/11
4
Source: http://www.google.com/trends/explore#q=%22big%20data%22
5. What is “big data”? And why we should
rather refer to Data-Driven Innovation?
• Defining “big data” is challenging:
– Data for which the “size is beyond the ability of
typical database software tools to capture, store,
manage, and analyse” (McKinsey Global Institute,
2011)
– Data that is characterized by the 3Vs: volume,
velocity (real-time data) and variety (unstructured
data) (Gartner, 2011).
• DDI refers to the use of data and analytics to
improve or foster new products, processes,
organisational methods and markets.
5
6. 6
Data: unlimited source for growth
Health and Aging
Public Administration Retail
Transportation and
energy
Agriculture
Science and Education
8. Data has always been key to social
and economic activities
• “Business intelligence” and “data
warehousing” already emerged in the
1960s and became popular in the late
1980s (Luhn, 1958; Keen, 1978).
• “Formal education has always been a data-rich
activity, with many data collected by
teachers and schools about learning
outcomes, attendance, enrolments”
(see agenda)
8
9. 9
DDI is not only about data,
it is about the data value cycle
10. The exponential growth in data
generated and collected
Monthly global IP traffic, 2005-16
In exabytes (billions of gigabytes)
Average data storage cost, 1998-2012
In USD per gigabyte (log scale)
Source: Source: OECD based on Cisco (2012) OECD based on Pingdom (2011)
10
11. The democratisation of computation
and analytic capacities
Open source data
processing and analytics
Data requests in Netflix, 2010-11
Data centre capacity
Sources: Netflix.com
In billions
11
12. A new paradigm in decision making?
Machine learning is now mainstream
12
15. Personal data is increasingly used
for customization
15
Personalised services Collaborative filtering
16. Data and analytics are empowering
process automation
16
• Automatic adjustment of production (e.g. smart grids)
• Autonomous machines in retail warehousing or
self-driving cars
Growth in algorithmic trading as share of total trading
Source: The Economist (2012)
20. Loss of autonomy and freedom
20
• Discrimination may result in greater
efficiencies, but also limits an individual’s
ability to escape the impact of prejudices
• Filter bubbles: users become separated
from information that disagrees with their
viewpoints, effectively isolating them in
their own cultural or ideological bubbles.
21. Lack of data scientists across the
economy
21
United States, 2013 EU, 2013
Professional
and business
services, 43%
Others,
5%
Financial
Wholesale and
retail trade, 5%
Information,
6%
administration,
Manufacturing,
11%
Public
7%
Educational activities, 12%
and health
services, 11%
Professional,
scientific and
technical
activities, 43%
Public
administration,
defence, and
sociale
services, 15%
Wholesale and
retail trade, 6%
Information
and
communication
, 9%
Manufacturing
industry, 12%
Financial and
insurance
activities, 7%
Transportation
and storage,
2%
Others,
7%
* Based on preliminary working definition of “data scientists”; ICT services included in “Professional *”.
Source: OECD based on US CPS (March Supplement 2013) and EU LFS
22. • Data ownership?
• Data interoperability?
• Data portability?
Better data sharing platforms and common
standards could be needed;
Privacy as well as IPR concerns may better be
addressed in a more differentiated manner;
22
Getting data governance
frameworks right
23. Thank you for your attention!
23
• OECD project site: http://oe.cd/bigdata
• OECD (2013), “Exploring Data-Driven Innovation as a
New Source of Growth: Mapping the Policy Issues
Raised by ‘Big Data’”: http://oe.cd/bigdata1
• OECD (2015), Data-Driven Innovation for Growth and
Well-being
– Preliminary synthesis report on “Data-Driven Innovation for
Growth and Well-being”: http://oe.cd/bigdata2
• Contact: Christian.Reimsbach-Kounatze@oecd.org
Editor's Notes
Good morning every one!
It is my pleasure to share with you today // the interim results of the work carried out // under the data pillar of KBC2.
These results have been provided to you via the first draft of the synthesis report // which has the cote DSTI/ICCP(2014)11 // as well as the overall report // including 10 draft chapters // provided as ANNEX document.
The synthesis report is the basis of this presentation.
Explain structure,
On 1.) Highlight that at the ende of this section you should also understand what we mean by data-driven innovation
On 3.) The policy opportunities discussed are not only relevant for the EU but for other oecd countries as well as some of its key partner economies.
Then give the disclaimer that your presentation reflects your expert opinion and does not necessarly reflect the position of the OECD SG or that of its member countries.
More data was created in 2013 than in all the preceding years of human history combined, and every minute the world generates enough data to fill more than 360,000 standard DVDs
This includes tweets, public Facebook posts, geotags that locate where photos were taken and news stories. It can also include de-identified records of mobile phone activity
MGI estimates suggest that:
Private sector retailers using big data can boosting productivity growth and increase their operating margin by over 60%
Public administration could generate EUR 100 billion in savings from operational efficiency improvements.
The use of geo-location data could generate almost USD 500 billion by 2020 in consumer surplus attributable to saved time and fuel.
We have to be cautious about these numbers. But what is more important here is that data is now increasingly used across economy, even in agriculture. Companies such as John Deere (US) or Lely (NL), are increasing innovating based on the data their collect.
Why is it important to highlight this, because data-driven innovation in the past was mainly about internet firms!
However, to have a more nuanced view on DDI, it is helpful to also consider the full data value cycle. This can help for example to identify specific issues that occur at the different phases of the data value cycle.
Decision makers do not necessarily need to understand a phenomenon, before they act on it. In other words: first comes the analytical fact, then the action, and last, if at all, the understanding.
For example, a company such as Wal-Mart Stores may change the product placement in its stores based on correlations without the need to know why the change will have a positive impact on its revenue.
As Anderson (2008) explains: “Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity.” And he conclude by challenging the usefulness of models in an age of massive datasets, arguing that with large enough data sets, machines can detect complex patterns and relationships that are invisible to researchers. And he concludes that the scientific method has in most cases become obsolete, because correlations are enough.
1.) The use of geo-location data will generate almost USD 500 billion by 2020 in consumer surplus attributable to saved time and fuel.
2.) NSOs exploring the use of “big data” for the supplement of official statistics: Analysts at the Chilean Central bank have used Google Insights to create a Google Trend Activity Index (GTAI) to sucessfully forecast the year-over-year (y-o-y) growth in the volume of car sales in Chile.
3.) Twitter not only for flue trends: Twitter as potential (unstructured) data source for analysing and even predicting the “emotional roller coaster” and its impact on the ups and downs of stock markets (Grossman, 2010; MIT Technology Review, 2010).
GNS Healthcare, Cambridge based companies uses different data sets (gene expression, SNPs, proteomics, metabolomics to, more recently, next-generation gene sequence data and Electronic Health Records and Health Information Exchanges data) to deliver personalized medical recommendations.
some have suggested that with big data, decision makers could base their actions only on analytical facts without the need to understand the phenomenon
This is because with big data correlations can often appear statistically significant even if there is no causal relationship
Changing data environment!
Data analytics, in particular when used for decision automation, can sometimes be easily “gamed” once the factors affecting the underlying algorithms have been understood, for example, through reverse engineering.
Marcus and Davis (2014) present for example the case where essay evaluation analytics that relied on measures like sentence length and word sophistication to determine typical scores given by human graders, were gamed by students who suddenly started “writing long sentences and using obscure words, rather than learning how to actually formulate and write clear, coherent text”.
Data analytics does not need to be intentionally gamed to lead to wrong results. Often they are just not robust enough to unexpected changes in the data environment.
The elephant is the room when we speak of big data really is privacy.
The key challenge to regulation is that the concept of personal data is becoming less and less operationable. Because what seems non-personal data will be able to convey personal information if linked to other data that seems non-personal.
Computers and devices are encoding a lot of information about what we are doing, when we are doing it, and where we are doing it from.
This comes with some key risks such as:
Discrimination: Customer segmentation can support dynamic pricing, raising issues related to equality. Predictive analytics can perpetuate existing stereotypes. Consumers may not realise that they are treated differently, and have little opportunity to contest such treatment. Could be extended to employment, insurance and credit.
Information asymmetry: Yes the web puts a wealth of information at a surfer’s finger types. Price comparisons, user reviews, etc have an importantly empowering impact. But businesses are likewise obtaining information about individual customers of greater and greater refinement. There is a general lack of transparency about these processes to consumers that may put them at a commercial disadvantage.
PRIVACY FWKS IN NEED OF ADJUSTMENT: OECD Privacy Gls revised. To be submitted to Council on 11 July for adoption. Further adjustments may be needed to specifically protect privacy in the context of big data (e.g. the [intact] basic principles may need to be adapted to better address the issue of secondary uses of personal data).
Let me give another example of a cross-cutting issue: data security breach.
The security dimension is clear: the compromise of IT systems is a been a long-standing problem.
Where the lost or stolen data is personal data, you have a privacy problem.
And then there are consumer risks: identity theft has for years been at or near the top of list of consumer complaints.
Security breaches are regrettably commonplace. This slide notes 3 breaches – a very partial list of breaches announced this month alone.
One is a breach affecting at least 70 million customers of the 3rd largest US retailer. Following the breach, Target reduced its 4th quarter earnings forecast by 25%.
Another involved 3 Korean credit card companies and affected 20 million individuals – 40 % of the population. Some 3 dozen executives lost jobs.
A 3rd breach involves data from several million users of an app to send secure private messages. Snapchat. How do you measure damage to a start-up whose business is trust?
Current debate about tackling the information asymmetry issue => increasing transparency about the use of personal data and increasing users’ (consumers’) control over their personal data by given them open access to these data sets. One example for the latter emerged last year in the UK and it is known as the “midata” initiative. It aims at giving consumers access to the data created through their household utility use, banking, internet transactions and high street loyalty cards. (see https://www.gov.uk/government/consultations/midata-2012-review-and-consultation) .
This leads to the issues related to open data >>
Data analytics make it increasingly easy to infer information about individuals, even if they never shared this information with anyone.
Privacy regimes are based on the concept of personal data. However, data analytics make it possible to infer personal information from non-personal data. In particular when data sets are linked!!!
The elephant is the room when we speak of big data really is privacy.
The key challenge to regulation is that the concept of personal data is becoming less and less operationable. Because what seems non-personal data will be able to convey personal information if linked to other data that seems non-personal.
Computers and devices are encoding a lot of information about what we are doing, when we are doing it, and where we are doing it from.
This comes with some key risks such as:
Discrimination: Customer segmentation can support dynamic pricing, raising issues related to equality. Predictive analytics can perpetuate existing stereotypes. Consumers may not realise that they are treated differently, and have little opportunity to contest such treatment. Could be extended to employment, insurance and credit.
Information asymmetry: Yes the web puts a wealth of information at a surfer’s finger types. Price comparisons, user reviews, etc have an importantly empowering impact. But businesses are likewise obtaining information about individual customers of greater and greater refinement. There is a general lack of transparency about these processes to consumers that may put them at a commercial disadvantage.
PRIVACY FWKS IN NEED OF ADJUSTMENT: OECD Privacy Gls revised. To be submitted to Council on 11 July for adoption. Further adjustments may be needed to specifically protect privacy in the context of big data (e.g. the [intact] basic principles may need to be adapted to better address the issue of secondary uses of personal data).
Let me give another example of a cross-cutting issue: data security breach.
The security dimension is clear: the compromise of IT systems is a been a long-standing problem.
Where the lost or stolen data is personal data, you have a privacy problem.
And then there are consumer risks: identity theft has for years been at or near the top of list of consumer complaints.
Security breaches are regrettably commonplace. This slide notes 3 breaches – a very partial list of breaches announced this month alone.
One is a breach affecting at least 70 million customers of the 3rd largest US retailer. Following the breach, Target reduced its 4th quarter earnings forecast by 25%.
Another involved 3 Korean credit card companies and affected 20 million individuals – 40 % of the population. Some 3 dozen executives lost jobs.
A 3rd breach involves data from several million users of an app to send secure private messages. Snapchat. How do you measure damage to a start-up whose business is trust?
Current debate about tackling the information asymmetry issue => increasing transparency about the use of personal data and increasing users’ (consumers’) control over their personal data by given them open access to these data sets. One example for the latter emerged last year in the UK and it is known as the “midata” initiative. It aims at giving consumers access to the data created through their household utility use, banking, internet transactions and high street loyalty cards. (see https://www.gov.uk/government/consultations/midata-2012-review-and-consultation) .
This leads to the issues related to open data >>
Data analytics make it increasingly easy to infer information about individuals, even if they never shared this information with anyone.
Privacy regimes are based on the concept of personal data. However, data analytics make it possible to infer personal information from non-personal data. In particular when data sets are linked!!!
While Hal is famous for promoting the sexy nature of being a statistician, processing and mining Big Data takes a special type of statistician, increasingly called a “Data Scientist”.
MGI (2011) estimates that demand for “deep analytical talent” in the US could be 50 to 60% greater than its projected supply by 2018.
This suggests that NSOs would be bidding against private firms for people who have these skills and could be forced to pay a premium to attract this talent.
Why work for ABS when you can work for Google?
PIAAC data across economies reveal that between 7% and 27% of adults have no experience in using computers or lack the most elementary computer skills, such as the ability to use a mouse.
Highlight that 35% within the 43% in Professional, scientific, and technical activities are in ICT services.
Michael made the point on looking at personal data a binary concept (O and I)
In the case of PSI:
Knowledge is a source of competitive advantage in the “information economy” and a major source of growth
Wide diffusion of data can be economically significant
Benefits from improving access to and facilitating reuse of data include:
Developing new products built directly on PSI
Developing complementary products, software and services
Reducing transaction costs in accessing and using information
Improving efficiency and productivity
Enabling efficiency gains in the public sector
Mixing public and private information in new goods and services
Almost all countries have Creative Commons (CC) or Creative Commons-like unrestricted licensing models to encourage use and innovation
Attribution is the main licence requirement
Most public pricing practices moved progressively from seeing public sector information and data as resources to be exploited
…..To
Seeing them as potential drivers of innovation, business creation and expansion
Making data free or available at marginal cost
Finally, here is the outline of the overall publication.
Finally I would like to thank your attention and highlighting that this work is based on a collaborative work across divisions and directorates.
And I may have missed to highlight some of the important elements done by my colleagues during the presentation.
The most successful high-tech internet companies such as Google and Amazon have built their business models on the collection and exploitation of big data.
These companies were able to scale without mass:
Talk about revenue per employee: Google 1 million USD per employee.
At Google, physical assets accounted for only about 13% of Google’s worth as of 31 December 2012
(calculated based annual balance sheet data as follow: (p – d) / a, where p: the total gross value for property, plant, and equipment; d: total accumulated depreciation; and a: total assets.)
In 2008, Google already processed over 20 petabytes of data per day (100 petabyte in 2012)
through 1 to 10 million servers operating every day
1 Petabyte = 1 milliong gigabytes = 0.5 billion HQ photos
20 Petabytes = Total production of hard-disk drives in 1995 = volume 1000 times the quantity of all printed material in the U.S. Library of Congress
The 3rd phase of the Internet will be the “Internet of Things” or M2M.
It will be less PC / personal device centric and more embedded devices;
– that open up huge new opportunities for controlling supply chains, tracking objects and monitoring the environment
-- But also poise some issues regarding security and privacy.
-- these devices will throw off huge amounts of data;
-- Ericsson estimates that already by 2020 that there will be 50 billion devices connected to the Internet
Available evidence confirm that DDI is a NEW SOURCE OF GROWTH.
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Looking first at the supply side for data and analytics // estimates suggest that the global market for data analytics is growing by 40% a year on average // and will reach 17 billion USD by 2015;
According our estimates // the OECD market for public sector data was worth 97 billion USD in 2008.
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What is more relevant from a policy maker perspective // however // is the impact of the use of data and analytics // that is // the impact of DDI // across the economy.
Empirical firm level studies confirm that the use of data analytics can boost firms’ productivity. Depending on the study, the impact ranges between 5% to up to 13%.
We believe that 5-10% is a reasonable conservative estimate // which is still an impressive figure // in particular if you consider that productivity growth in the OECD area was at 1.6% between 2009-12;
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At this point // it is very important to be aware that these figures DO NOT capture the full social benefits of data and analytics. // Such as the social benefits of better transparency of governments activities through open data // or the benefits of the personal use of data and analytics for health care or self-awareness raising // as promoted for example by the quantified-self movement.
These social benefits // that relate to consumer surplus // or to aspects of well-being // are still poorly captured by economic statistics // if at all.
It is important to recall this // also because in contrast to the economic benefits which are well captured quantitatively // potential social costs due to the inappropriate use of data and analytics are hard to measure // and may not appear on a radar screen which only capture quantitative figures.
Policy makers also need to understand the risks and challenges that come with DDI.
What are these risks and challenges?
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Looking at the supply side first again//
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Barriers to the free flow of data can be identified as one of the most critical challenges preventing possible spill-over effects.
These barriers are not only an issue across borders, // but also across sectors and organisations, // including between organisations and individuals // the latter is relevant when we talk about data portability.
It is important to note that there are some legitimate reasons for the limitation of the free flow of data // privacy is often cited as one, as well as security // or the protection of trade secrets.
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An other challenges are related to the limited applicability of the concept of ownership //
The concept of ownership entails the right of exclusion, as well as the right to fully dispose of the data including the right to delete the data at will.
However, when it comes to personal data in particular // there are some unrestrictable control rights granted to data subjects // that limit the control rights of the data controller // to such an extent that data controllers can hardly be seen as data owners in the traditional sense.
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At this point // it important to note that // the limited applicability of the concept of ownership is at the source of some of the incentives problems // related to data quality control or data curation that we see in science but also in health care, as well as some of the incentive issues related to data sharing.
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Looking now at the demand side //
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Lack of skills and competencies is an issue that emerged in all working streams of the project, be it // skills in the area of science, health care, or even public administration.
A number of empirical studies have also confirmed the lack of skills as an important barrier to DDI in businesses.
I have already talked about skills and
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Organisational change
And
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Entrepreneurship as important demand side issues.
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So please let me now highlight some of the societal challenges that are affecting not only the supply side or the demand side but society at large.
The first issue is related to the economic property of data discussed in the previous slide:
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As I highlighted, the increasing returns to scale and scope favour market concentration and dominance.
This can raise competition // as well as consumer protection issues // where such a market dominance is abused.
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Furthermore, the agglomeration of data can also lead to greater information asymmetry between the data controller and the data subjects.
This information asymmetry may lead to a shift in power away from the data subject and // may exacerbate existing inequalities; leading to a new type of digital divide : a digital divide 3.0 if you want.
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Last, but not least, trust deterioration in face of (i) the risks of loosing autonomy and freedom but also due to the (ii) increased cybersecurity risks needs to be considered by policy makers.
Finally, here is the outline of the overall publication.
I would like to take this opportunity to thank the Netherlands for their in-kind contribution through a module produced by TNO. The content of the module was very much appreciated and used for chapter 3 and chapter 10.
Many thanks to the NL.