Presentation to the Open Data Charter Implementation Working Group meeting, November 2019 on ways to manage the barriers to open government data release.
The document discusses challenges related to open data including:
1. Ensuring quality by providing good context about data collection methods and known limitations, as well as opportunities for feedback.
2. Addressing concerns about misuse by emphasizing context, describing data collection purposes and variables clearly, and noting liability limitations in Creative Commons licenses.
3. Overcoming cultural and resource barriers through an open by default approach, prioritizing high demand data, reusing existing technologies, and starting small.
Dr Masood Ahmed and Alan Davies - ECO 17: Transforming care through digital h...Innovation Agency
Presentation by Dr Masood Ahmed, Advisor, Digital Health London and Alan Davies, Director of Digital Health, Innovation Agency: Getting AI into practice in the NHS at ECO 17: Transforming care through digital health on Tuesday 4 December at Lancaster University, Lancaster
FOSS4G UK: Locus Charter: Helping to use location data ethically and responsiblyPLACE
The Locus Charter is an international set of principles and guidance for the ethical use of location data. It aims to help practitioners better understand location data ethics and provide real-world tools to address risks and opportunities. The charter is being developed through a series of workshops with input from governments, organizations, and practitioners worldwide. It covers principles like location truth and privacy, as well as a location data lifecycle framework. The goal is to launch the charter in October 2020 after finalizing language and public review.
This document discusses credit scoring and the use of alternative or "big data". It summarizes that PERC advocates the inclusion of alternative data sources like utility payments, rent payments, and telecom payments to make more informed credit decisions. While big data holds promise, it also has risks if not approached with caution. Key risks include misplaced faith in big data, data ownership issues, overfitting models, and removing the consumer from the process.
Tim Estes - Information Systems in an Entity Centric WorldDigital Reasoning
Tim Estes, CEO of Digital Reasoning, talks about the use of Hadoop and other scalable technologies along with Digital Reasoning's analytics for automated understanding of cloud-scale text challenges.
This presentation was delivered at Hadoop World in New York in Oct 2010
AIDR2019 - standards - tools - incentives - what does it take to enable data ...Fiona Nielsen
Fiona Nielsen founded Repositive to address the challenges of data sharing and accessibility in genomics research. Repositive developed tools to make large amounts of genomic data more discoverable, including a search engine of over 1 million public data sets. Repositive also launched a marketplace to help cancer researchers find the right models for their studies by organizing complex data on genetic profiles and phenotypes of thousands of cancer models. However, Nielsen notes that while standards and tools are important, incentives are also needed to motivate data sharing and reuse at scale. She advocates recognizing data stewardship contributions and aligning policies and practices, like hiring and funding, to incentivize open data practices.
Data managementfornonprofits 2014-06-19501 Commons
The document provides information about choosing a data management system for nonprofits. It discusses assessing an organization's needs, prioritizing requirements, and mapping out desired software features. Key steps include narrowing options, contacting vendors, and piloting top contenders. While technology is important, the presenter emphasizes that effective data management depends most on having the right people and processes in place.
The document discusses challenges related to open data including:
1. Ensuring quality by providing good context about data collection methods and known limitations, as well as opportunities for feedback.
2. Addressing concerns about misuse by emphasizing context, describing data collection purposes and variables clearly, and noting liability limitations in Creative Commons licenses.
3. Overcoming cultural and resource barriers through an open by default approach, prioritizing high demand data, reusing existing technologies, and starting small.
Dr Masood Ahmed and Alan Davies - ECO 17: Transforming care through digital h...Innovation Agency
Presentation by Dr Masood Ahmed, Advisor, Digital Health London and Alan Davies, Director of Digital Health, Innovation Agency: Getting AI into practice in the NHS at ECO 17: Transforming care through digital health on Tuesday 4 December at Lancaster University, Lancaster
FOSS4G UK: Locus Charter: Helping to use location data ethically and responsiblyPLACE
The Locus Charter is an international set of principles and guidance for the ethical use of location data. It aims to help practitioners better understand location data ethics and provide real-world tools to address risks and opportunities. The charter is being developed through a series of workshops with input from governments, organizations, and practitioners worldwide. It covers principles like location truth and privacy, as well as a location data lifecycle framework. The goal is to launch the charter in October 2020 after finalizing language and public review.
This document discusses credit scoring and the use of alternative or "big data". It summarizes that PERC advocates the inclusion of alternative data sources like utility payments, rent payments, and telecom payments to make more informed credit decisions. While big data holds promise, it also has risks if not approached with caution. Key risks include misplaced faith in big data, data ownership issues, overfitting models, and removing the consumer from the process.
Tim Estes - Information Systems in an Entity Centric WorldDigital Reasoning
Tim Estes, CEO of Digital Reasoning, talks about the use of Hadoop and other scalable technologies along with Digital Reasoning's analytics for automated understanding of cloud-scale text challenges.
This presentation was delivered at Hadoop World in New York in Oct 2010
AIDR2019 - standards - tools - incentives - what does it take to enable data ...Fiona Nielsen
Fiona Nielsen founded Repositive to address the challenges of data sharing and accessibility in genomics research. Repositive developed tools to make large amounts of genomic data more discoverable, including a search engine of over 1 million public data sets. Repositive also launched a marketplace to help cancer researchers find the right models for their studies by organizing complex data on genetic profiles and phenotypes of thousands of cancer models. However, Nielsen notes that while standards and tools are important, incentives are also needed to motivate data sharing and reuse at scale. She advocates recognizing data stewardship contributions and aligning policies and practices, like hiring and funding, to incentivize open data practices.
Data managementfornonprofits 2014-06-19501 Commons
The document provides information about choosing a data management system for nonprofits. It discusses assessing an organization's needs, prioritizing requirements, and mapping out desired software features. Key steps include narrowing options, contacting vendors, and piloting top contenders. While technology is important, the presenter emphasizes that effective data management depends most on having the right people and processes in place.
Galaxy Consulting provides information management consulting services to help organizations control the growing volume of information. They assist with enterprise content management, records management, and document control to create central repositories, enable collaboration, automate processes, and improve efficiency. Without proper information management, organizations experience lost productivity from employees searching for information and legal and compliance risks.
A safer approach to build recommendation systems on unidentifiable dataKishor Datta Gupta
Conference: 14th International Conference on Agents and Artificial Intelligence (ICAART 2022)
In recent years, data security has been one of the biggest concerns, and individuals have grown increasingly worried about the security of their personal information. Personalization typically necessitates the collection of individual data for analysis, exposing customers to privacy concerns. Companies create an illusion of safety to make people feel safe using a mainstream word, "encryption". Though encryption protects personal data from an external breach, the companies can still exploit personal data collected from users as they own the encryption keys. We present a naive yet secure approach for recommending movies to consumers without collecting any personally identifiable information. Our proposed approach can assist a movie recommendation system understand user preferences using the user's movie watch-time and watch history only. We conducted a comprehensive and comparative study on the performance of three deep reinforcement learning architectures, namely DQN, DDQN, and D3QN, on the same task. We observed that D3QN outperformed the other two architectures and achieved a precision of 0.880, recall of 0.805, and F1 score of 0.830. The results show that we can build a competitive movie recommendation system using unidentifiable data.
Data analytics with managerial application ass 3Nishant Kumar
Data does not inherently create meaning - we impose meaning on data through analysis and interpretation. With massive amounts of big data, we have the potential to make bad decisions quickly if we do not think critically about what the data means and what other possibilities exist. As managers, developing critical thinking skills through fields like humanities is important for properly analyzing big data and avoiding misuse or misinterpretation that could have serious consequences for a company. Innovation requires questioning existing frames of reference and assumptions in order to find new opportunities.
Wikistrat is the world's first crowdsourced consultancy that operates a global network of over 2,000 subject matter experts who collaborate online to help clients address complex strategic challenges. Wikistrat's crowdsourced methodology allows it to generate diverse insights from experts and provide services such as simulations, intelligence monitoring, and briefings to clients three times faster than traditional consultancies at lower cost. Some of Wikistrat's predictive successes have included forecasting major geopolitical events months in advance.
Netflix was a trailblazing innovator in machine learning as applied to personalization and recommendation systems but there are many other applications of machine learning at Netflix, especially as we further evolve into a global entertainment company. This talk will give an overview of how machine learning is leveraged before content launches on Netflix and how machine learning can support the creative process and serve as a tool for decision makers in our content and marketing organization. The process of creating content is a high-touch, creative endeavor so we need to be similarly creative in the machine learning innovations we develop. From neural nets that predict audience size for content that doesn't exist yet, to NLP and deep learning techniques that mine scripts to highlight properties we need legal clearance for ... we are building unprecedented innovations. The talk will also broadly cover the challenges we face in this space, including data scarcity and making ML interpretable for non-technical stakeholders.
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...OW2
Open Source software projects have diverse goals, but they mainly have a mission in common: promote the adoption and collaboration of their specific products. They might have different reasons for it and different policies to achieve that vision. But it ends being about the people using and developing those products.
Talking about "success", in this case, it would mean that the products are used and developed by individuals or by the industry. How could we measure this success? Metrics are useful for project transparency, neutrality, marketing and engineering, and during this talk we will present some use cases and tools to manage your open source and collaborative software projects in an effective way.
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...Digital Reasoning
In this presentation, O'Reilly author and Digital Reasoning CTO Matthew Russell along with Dr. Steve Kramer, founder and chief scientist at Paragon Science, discuss how Digital Reasoning processed the Enron corpus with its advanced Natural Language Processing (NLP) technology - effectively transforming it into building blocks that are viable for data science. Then, Paragon Science used dynamic graph analysis inspired from particle physics to tease out insights from the data in order to better understand whether an enterprise fiasco such as the Enron scandal could have been thwarted.
Data & Digital Ethics - CDAO Conference Sydney 2018Kate Carruthers
Kate Carruthers gave a presentation on data and digital ethics. She discussed how ethics is important with data and algorithms. Traditional approaches to ethics like codes of conduct have issues, so new approaches are needed like fairness in machine learning. Education is also important. Overall, formal ways to consider ethics for data uses are required as technology cannot determine ethics on its own.
Big data refers to the large amounts of structured and unstructured data that businesses receive daily. While the volume of data is large, it is what organizations do with the data that matters by analyzing it for insights to improve decisions and strategies. The amount of global data continues to grow exponentially, increasing the potential to glean key insights, yet only a small percentage of data is currently analyzed. Businesses should focus on better utilizing the information they receive every day to reduce costs, improve efficiency, develop new products and services, and make smarter decisions through big data analytics. However, data must be carefully interpreted and can be misused, so context from fields like the humanities and social sciences is important for critical thinking.
Talking about Big Data generates a lot of questions; however, most of the focus is on the technologies and skills required to collect and store this volume of information as opposed to the insight that companies need to derive from it. What factors should organizations consider in order to ensure that they are capitalizing on their investments with these technologies? How do you break through business silos to enable sharing of data to increase organizational value? Leveraging his cross-industry experience at companies like The Walt Disney Company, Travelers Insurance and Demand Media, Brendan Aldrich will discuss the question of “big value” with industry examples and a particular focus on his current work to deploy a “data democracy” within the City Colleges of Chicago.
Session Discovery Topics:
• Big value - keeping an eye on the forest (assumptions, judgment and bias)
• Data democracy - increasing productivity with data transparency and open access
Privacy by Design - taking in account the state of the artJames Mulhern
Establishing transparency and building trust provide an opportunity to develop greater, more meaningful relationships with data subjects i.e people, customers, colleagues... in turn this can lead to more effective and valuable services that help transform organisations.
A "Privacy by design" approach can help achieve this but it doesn't happen by accident and transformation doesn't occur over night. So a deliberate approach that looks beyond May 2018 and compliance is required.
Presentation to representatives from the technology and Local Government sectors at TechUK, the UK's trade association for the technology.
This document describes the qualifications and experience of Brian Kelly for a Community Engagement Manager position at an organization focused on open data. It outlines Brian's technical skills and experience with open data, social media management of organizational accounts, strong written and oral communication abilities, experience defining metrics and strategies for community engagement, and proven ability to work with diverse professionals and create impact. Brian has over 15 years of experience advocating for open practices through numerous conference talks, published papers, openly licensed resources, and events promoting openness in areas like education and cultural heritage.
The document discusses several key topics related to data privacy in the digital economy:
- Challenges of safeguarding privacy rights with the rise of technology and data collection.
- Assessing privacy maturity based on generally accepted privacy principles.
- Implementing privacy enhancing technologies and practices like privacy by design.
- Understanding consumer concerns about privacy and gaining their consent for data use.
Towards data responsibility - how to put ideals into actionMindtrek
Track | Sustainable and Future-proof Tech
Mikko Eloholma Accelerator of Digital skills, TIEKE
Mindtrek Conference
3rd of October 2023.
Tampere, Finland
www.mindtrek.org
This document summarizes a presentation about big data. The presentation covered what big data is, the four V's of big data (volume, velocity, variety, and veracity), a brief history of big data, diving deeper into Hadoop and its ecosystem, and two case studies. The presentation also discussed the big data initiative at the company CCC and how it aims to use big data for student success, retention, graduation rates, and improving advising.
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTIONPranav Godse
Data mining involves collecting and analyzing large amounts of customer data. While this can provide commercial benefits, it also raises ethical issues regarding customer privacy. Some key ethical challenges include ambiguity around how social networks label relationships, uncertainty around future uses of customer data by companies, and a lack of transparency around passive collection of mobile location data. To address these challenges, companies should focus on ethical data mining practices like verifying data sources, respecting customer expectations of privacy, developing trust through transparency and control over data access. Regulators also need to continue updating laws and regulations to balance the benefits of data analytics with protecting individual privacy rights.
Galaxy Consulting provides information management consulting services to help organizations control the growing volume of information. They assist with enterprise content management, records management, and document control to create central repositories, enable collaboration, automate processes, and improve efficiency. Without proper information management, organizations experience lost productivity from employees searching for information and legal and compliance risks.
A safer approach to build recommendation systems on unidentifiable dataKishor Datta Gupta
Conference: 14th International Conference on Agents and Artificial Intelligence (ICAART 2022)
In recent years, data security has been one of the biggest concerns, and individuals have grown increasingly worried about the security of their personal information. Personalization typically necessitates the collection of individual data for analysis, exposing customers to privacy concerns. Companies create an illusion of safety to make people feel safe using a mainstream word, "encryption". Though encryption protects personal data from an external breach, the companies can still exploit personal data collected from users as they own the encryption keys. We present a naive yet secure approach for recommending movies to consumers without collecting any personally identifiable information. Our proposed approach can assist a movie recommendation system understand user preferences using the user's movie watch-time and watch history only. We conducted a comprehensive and comparative study on the performance of three deep reinforcement learning architectures, namely DQN, DDQN, and D3QN, on the same task. We observed that D3QN outperformed the other two architectures and achieved a precision of 0.880, recall of 0.805, and F1 score of 0.830. The results show that we can build a competitive movie recommendation system using unidentifiable data.
Data analytics with managerial application ass 3Nishant Kumar
Data does not inherently create meaning - we impose meaning on data through analysis and interpretation. With massive amounts of big data, we have the potential to make bad decisions quickly if we do not think critically about what the data means and what other possibilities exist. As managers, developing critical thinking skills through fields like humanities is important for properly analyzing big data and avoiding misuse or misinterpretation that could have serious consequences for a company. Innovation requires questioning existing frames of reference and assumptions in order to find new opportunities.
Wikistrat is the world's first crowdsourced consultancy that operates a global network of over 2,000 subject matter experts who collaborate online to help clients address complex strategic challenges. Wikistrat's crowdsourced methodology allows it to generate diverse insights from experts and provide services such as simulations, intelligence monitoring, and briefings to clients three times faster than traditional consultancies at lower cost. Some of Wikistrat's predictive successes have included forecasting major geopolitical events months in advance.
Netflix was a trailblazing innovator in machine learning as applied to personalization and recommendation systems but there are many other applications of machine learning at Netflix, especially as we further evolve into a global entertainment company. This talk will give an overview of how machine learning is leveraged before content launches on Netflix and how machine learning can support the creative process and serve as a tool for decision makers in our content and marketing organization. The process of creating content is a high-touch, creative endeavor so we need to be similarly creative in the machine learning innovations we develop. From neural nets that predict audience size for content that doesn't exist yet, to NLP and deep learning techniques that mine scripts to highlight properties we need legal clearance for ... we are building unprecedented innovations. The talk will also broadly cover the challenges we face in this space, including data scarcity and making ML interpretable for non-technical stakeholders.
The MEASURE project : Measuring Software Engineering, Manrique Lopez, OW2con'...OW2
Open Source software projects have diverse goals, but they mainly have a mission in common: promote the adoption and collaboration of their specific products. They might have different reasons for it and different policies to achieve that vision. But it ends being about the people using and developing those products.
Talking about "success", in this case, it would mean that the products are used and developed by individuals or by the industry. How could we measure this success? Metrics are useful for project transparency, neutrality, marketing and engineering, and during this talk we will present some use cases and tools to manage your open source and collaborative software projects in an effective way.
Got Chaos? Extracting Business Intelligence from Email with Natural Language ...Digital Reasoning
In this presentation, O'Reilly author and Digital Reasoning CTO Matthew Russell along with Dr. Steve Kramer, founder and chief scientist at Paragon Science, discuss how Digital Reasoning processed the Enron corpus with its advanced Natural Language Processing (NLP) technology - effectively transforming it into building blocks that are viable for data science. Then, Paragon Science used dynamic graph analysis inspired from particle physics to tease out insights from the data in order to better understand whether an enterprise fiasco such as the Enron scandal could have been thwarted.
Data & Digital Ethics - CDAO Conference Sydney 2018Kate Carruthers
Kate Carruthers gave a presentation on data and digital ethics. She discussed how ethics is important with data and algorithms. Traditional approaches to ethics like codes of conduct have issues, so new approaches are needed like fairness in machine learning. Education is also important. Overall, formal ways to consider ethics for data uses are required as technology cannot determine ethics on its own.
Big data refers to the large amounts of structured and unstructured data that businesses receive daily. While the volume of data is large, it is what organizations do with the data that matters by analyzing it for insights to improve decisions and strategies. The amount of global data continues to grow exponentially, increasing the potential to glean key insights, yet only a small percentage of data is currently analyzed. Businesses should focus on better utilizing the information they receive every day to reduce costs, improve efficiency, develop new products and services, and make smarter decisions through big data analytics. However, data must be carefully interpreted and can be misused, so context from fields like the humanities and social sciences is important for critical thinking.
Talking about Big Data generates a lot of questions; however, most of the focus is on the technologies and skills required to collect and store this volume of information as opposed to the insight that companies need to derive from it. What factors should organizations consider in order to ensure that they are capitalizing on their investments with these technologies? How do you break through business silos to enable sharing of data to increase organizational value? Leveraging his cross-industry experience at companies like The Walt Disney Company, Travelers Insurance and Demand Media, Brendan Aldrich will discuss the question of “big value” with industry examples and a particular focus on his current work to deploy a “data democracy” within the City Colleges of Chicago.
Session Discovery Topics:
• Big value - keeping an eye on the forest (assumptions, judgment and bias)
• Data democracy - increasing productivity with data transparency and open access
Privacy by Design - taking in account the state of the artJames Mulhern
Establishing transparency and building trust provide an opportunity to develop greater, more meaningful relationships with data subjects i.e people, customers, colleagues... in turn this can lead to more effective and valuable services that help transform organisations.
A "Privacy by design" approach can help achieve this but it doesn't happen by accident and transformation doesn't occur over night. So a deliberate approach that looks beyond May 2018 and compliance is required.
Presentation to representatives from the technology and Local Government sectors at TechUK, the UK's trade association for the technology.
This document describes the qualifications and experience of Brian Kelly for a Community Engagement Manager position at an organization focused on open data. It outlines Brian's technical skills and experience with open data, social media management of organizational accounts, strong written and oral communication abilities, experience defining metrics and strategies for community engagement, and proven ability to work with diverse professionals and create impact. Brian has over 15 years of experience advocating for open practices through numerous conference talks, published papers, openly licensed resources, and events promoting openness in areas like education and cultural heritage.
The document discusses several key topics related to data privacy in the digital economy:
- Challenges of safeguarding privacy rights with the rise of technology and data collection.
- Assessing privacy maturity based on generally accepted privacy principles.
- Implementing privacy enhancing technologies and practices like privacy by design.
- Understanding consumer concerns about privacy and gaining their consent for data use.
Towards data responsibility - how to put ideals into actionMindtrek
Track | Sustainable and Future-proof Tech
Mikko Eloholma Accelerator of Digital skills, TIEKE
Mindtrek Conference
3rd of October 2023.
Tampere, Finland
www.mindtrek.org
This document summarizes a presentation about big data. The presentation covered what big data is, the four V's of big data (volume, velocity, variety, and veracity), a brief history of big data, diving deeper into Hadoop and its ecosystem, and two case studies. The presentation also discussed the big data initiative at the company CCC and how it aims to use big data for student success, retention, graduation rates, and improving advising.
ETHICAL ISSUES WITH CUSTOMER DATA COLLECTIONPranav Godse
Data mining involves collecting and analyzing large amounts of customer data. While this can provide commercial benefits, it also raises ethical issues regarding customer privacy. Some key ethical challenges include ambiguity around how social networks label relationships, uncertainty around future uses of customer data by companies, and a lack of transparency around passive collection of mobile location data. To address these challenges, companies should focus on ethical data mining practices like verifying data sources, respecting customer expectations of privacy, developing trust through transparency and control over data access. Regulators also need to continue updating laws and regulations to balance the benefits of data analytics with protecting individual privacy rights.
Innovation and economic growth depends on company's ability to gain insight into data. However, data is growing exponentially, but our ability to make use of it is not. Untapped economic value resides in this unutilized data, called "dark data." This presentation looks at some of the causes for the explosion of data, some of the impediments preventing exploring and creating business value from dark data; and some ideas for ways around those impediments.
This document outlines an agenda and activities for a workshop on practical data management planning. The workshop will discuss challenges with data management, including data loss and how poor management affects all. Activities will guide participants in inventorying their data and developing storage and backup plans. The goal is to help researchers effectively manage their data over the long-term and address funder and legal requirements.
Data mining and privacy preserving in data miningNeeda Multani
Data mining involves analyzing data from different perspectives to discover useful patterns and relationships not previously known. It can be used to increase profits, reduce costs, and more. Privacy preservation in data mining aims to protect individual privacy while still providing valid mining results, using techniques like cryptographic protocols to run algorithms on joined databases without revealing unnecessary information. Data mining has various applications like fraud detection, credit risk assessment, customer profiling, and more.
Module 3 - Improving Current Business with External Data- Online caniceconsulting
The document discusses how to use external data to improve business. It defines external data as data generated outside an organization that can come from a variety of sources and serve nearly every industry. The document outlines different types of external data like primary data, secondary data, and open data. It provides examples of sources for primary data, which is original and reliable, and secondary data, which already exists. The benefits of using external data to supplement internal data and gain a more comprehensive view are also discussed.
Your Personal Information is none of anyone’s Business. Information Architecture can help keep it that way.
Are you creating products that respect the needs and autonomy of your users? Would you like to learn how to evaluate your digital products for respectful behavior?
It’s possible to measure ethical behavior of technology and Information Architecture is a key component. Join Noreen Whysel and you will Learn:
-How can IA inform the design of safe and respectful apps and websites?
-What is the Me2B Safe Technology Specification?
-How can you get involved?
This document discusses ethics in data warehousing and data mining. It notes that data mining can discover new patterns and relationships but also raises ethical issues when used to discriminate against groups for things like loans or special offers. The project manager is responsible for ensuring ethical use of data and establishing access controls and qualifications for users. Small data sets can also raise ethical concerns if users learn information they should not. The project manager must decide what public data is integrated and ensure end users, testing practices, and data mining applications comply with ethical standards and legal regulations.
Similar to Managing the Barriers to an Open Data Culture (20)
This document discusses open data in New Zealand. It notes that under the 2011 NZ Declaration on Open and Transparent Government, government agencies are required to proactively release non-personal data that has potential for reuse. When data is opened and reused, more value is realized in the forms of economic, social, and democratic benefits. Examples are given of open data being used for new products/services, visualization/debate, and more efficient government. The document outlines principles for open data and issues to consider like provenance, context, licensing, and indigenous data sovereignty.
Open and transparent practices through open dataenotsluap
The document discusses the benefits of open data and open government practices. It notes that open data can create economic, social and democratic value as data is reused. The New Zealand Declaration on Open and Transparent Government commits government agencies to proactively releasing non-personal data online to encourage reuse. Open consultation practices and releasing open source software can also increase transparency and participation in government.
Open data and business - presentation to the Hawke's Bay Chamber of Commerce September 2019. Open Government policy, what is open data, what is available, how has it been used, and what data could businesses be making open for their benefit.
This document provides an overview of New Zealand's open data program and initiatives. It discusses the history of open data in New Zealand dating back to 2008. It outlines guidance around licensing open data with Creative Commons and key documents/strategies like the NZGOAL framework, Data.govt.nz, and the 2011 NZ Data Principles. Examples are given of types of open government data available on Data.govt.nz and how this data is being reused through new products/services, data journalism, and more efficient data sharing across government.
Hawke's Bay Open Data Conference - 2 May 2019enotsluap
Hawke's Bay Open Data Conference - 2 May 2019. Presentation on open data Policy, data available and innovative ways it is being reused. Also why the private sector could/should release data.
Presentation to an audience of the Institute of Public Administration NZ (IPANZ), covering the value of open data; government's policy; the role of the Government Chief Data Steward; what sort of data is open and innovative ways it has been reused for new products, services and insights.
Open data policy and intentions in New Zealand - why open has more potential to generate value. The Chief Government Data Steward role and what's happening to lift data capability across government. What's out there as open data and how is it being used to make an impact.
Symbiotic relationships: bringing about change for open data togetherenotsluap
Presentation to the Open Data Leaders Summit at IODC18, Buenos Aires, about the value of symbiotic relationships and an informal approach to bring about open data change.
Presentation on the open data landscape - government policy and its intentions; open by design vs privacy by design; the Open Data Charter; what the programme is doing; some examples of open data put to use; and some examples of data found on Data.govt.nz
Hawkes bay local governent workshop 9 december 2015enotsluap
The document outlines an agenda for a meeting on open government data and information between Hawke's Bay regional and territorial authorities. It discusses New Zealand's open data policies and principles, resources available to support open data, examples of how open data has been used, and data that users want made available, such as property valuations, river flows, and council contracting information. The goal is to encourage government agencies to proactively release non-personal data and embrace open data practices.
- The document discusses New Zealand's Open Government Information and Data Programme, providing examples of apps and tools developed through open data initiatives like GovHack.
- Over 3,000 people participated in GovHack across Australia and New Zealand, developing over 100 projects using open government datasets to address real issues.
- Examples of apps developed include tools for emergency services, immigrants, tourists, and more to help reduce wait times, find communities and flatmates, and bring together emergency information.
Community and voluntary sector research forum march 2015enotsluap
Paul Stone from the New Zealand Open Government Data Programme gave a presentation about open data. He defined open data as data that can be freely used, reused and redistributed by anyone with attribution. He described New Zealand's open government data policies and initiatives like NZGOAL and Data.govt.nz. He provided several examples of open government data sources and how data has been used, such as using health, contracts and crime data for advocacy. He concluded that the community sector has potential to use open data but lacks data skills and would rely on researchers to analyze data for them.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
Managing the Barriers to an Open Data Culture
1. Open Data
Challenges
Paul Stone, NZ Open Government Data Programme,
Data Leadership and Capability, Stats NZ.
ODC Implementation Working Group, November 2019
2. Quality
Some data is better than
no data…
1. Good context
• Purpose of collection
• Method of collection
• Known strengths and
weaknesses
2. Opportunity for
feedback
3. Creative Commons
Licence
Image: Quality by Nick Youngson CC BY-SA 3.0 Alpha Stock Images
3. Accurac
y
• Context – inform how data is
collected and for what purpose.
• Be upfront about limitations in
the data or risk of human error
• Create a feedback loop - invite
data users to contribute and help
lift the accuracy of the data
4. Creative Commons
Licence – not liable for
quality
THE LICENSOR OFFERS THE LICENSED MATERIAL AS-IS AND
AS-AVAILABLE, AND MAKES NO REPRESENTATIONS OR
WARRANTIES OF ANY KIND CONCERNING THE LICENSED
MATERIAL… THIS INCLUDES… FITNESS FOR A PARTICULAR
PURPOSE…
5. Ignorant misuse
Context, context, context.
• Describe the collection
method and purpose
• Describe well the
variables in the data and
what they mean
• Don’t assume everyone is
ignorant.
6. Malicious
misuse Don’t let one bad
potential use prevent
the opportunity for
many good uses
Further clause on
liability in CC licence.
7. Creative Commons
Licence – not liable for
reuse (misuse)
…IN NO EVENT WILL THE LICENSOR BE LIABLE TO YOU ON
…DAMAGES ARISING OUT OF THIS PUBLIC LICENSE OR USE
OF THE LICENSED MATERIAL…
8. Reputation
• Transparency builds trust
• Good context reduces
misunderstanding
• An opportunity to contribute to
data quality is an opportunity to
engage and build relationships
All good reasons to release the
data – with good context.
9. Lack of resources
• Open by design
• Prioritise
o Alignment to organisational
strategy
o demand
• Don’t re-invent the wheel
• Start small
10. Lack of technology
• Keep it simple
• Start small
• Every agency has a website
• Most agencies have API
capability but just don’t use it
12. Culture
Probably the biggest challenge.
Shifting the mindset of the whole
organisation to open by default.
Challenges are manageable, not
insurmountable.
Key messages – like “we are
custodians of a public data asset”