This presentation explains how us, at UNEP-MAP, deal with data: contextualizing the adopted data policy (http://193.206.192.248/en/communication/event/second-info-rac-national-focal-point-meeting/wg512_2_eng-3.pdf), identifying crucial points and possible barriers to data opening in the Mediterranean basin.
This document summarizes Simon Hodson's presentation on open science and FAIR data developments globally. Some key points:
1) There is a growing policy push for open research data, with funders and organizations adopting data sharing policies based on FAIR data principles of findability, accessibility, interoperability, and reusability.
2) Initiatives are working to build the international ecosystem of open science, including components for reporting research outputs, persistent identifiers, data standards, data repositories, and criteria for trustworthy data.
3) The African Open Science Platform aims to lay the foundations for open science in Africa through frameworks for policy, incentives, training, and technical infrastructure development.
4) International
This document summarizes an initiative focused on ethics, privacy, transparency and trust related to the use of location data. It discusses trends in these areas and introduces the Locus Charter, a set of draft principles for the responsible and ethical use of location data. Example projects funded by the initiative are also summarized, including tools for measuring representation in location datasets and understanding how location data is collected from mobile devices.
Stuart Macdonald steps through the process of creating a robust data management plan for researchers. Presented at the European Association for Health Information and Libraries (EAHIL) 2015 workshop, Edinburgh, 11 June 2015.
The document provides information on creating a data management plan (DMP) for grant applications. It discusses what a DMP is, why they are important, and what funders require in a DMP. A DMP outlines how research data will be collected, documented, stored, shared, and preserved. The document recommends addressing six key themes in a DMP: data types and standards; ethics and intellectual property; data access, sharing and reuse; short-term storage and management; long-term preservation; and resourcing. Developing a strong DMP helps researchers manage data effectively and makes data available and reusable by others.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
Kenya open data case 7.7.17 prof wafulaTom Nyongesa
This document summarizes Kenya's open data initiatives and policies. It discusses Kenya's open data national case study, key pillars of open data policy development, best practices for open data implementation, JKUAT's open data initiatives including its open data platform and policy, the Digital Health Applied Research Centre project, open data in agricultural research, and Kenya's draft national ICT policy which supports open data principles and use of data for e-services like e-health and e-agriculture. The document provides an overview of how Kenya is using open data to support smart and sustainable development.
This document summarizes Kenya's open data initiatives and policies. It discusses Kenya's open data national case study, key pillars of open data policy development, best practices for open data implementation, JKUAT's open data initiatives including its open data platform and policy, the Digital Health Applied Research Centre project, open data in agricultural research, and Kenya's draft national ICT policy which supports open data principles and use in various sectors like health, agriculture and more. The document provides an overview of how Kenya is working to develop its open data ecosystem through projects, policies and stakeholder engagement.
This document summarizes Simon Hodson's presentation on open science and FAIR data developments globally. Some key points:
1) There is a growing policy push for open research data, with funders and organizations adopting data sharing policies based on FAIR data principles of findability, accessibility, interoperability, and reusability.
2) Initiatives are working to build the international ecosystem of open science, including components for reporting research outputs, persistent identifiers, data standards, data repositories, and criteria for trustworthy data.
3) The African Open Science Platform aims to lay the foundations for open science in Africa through frameworks for policy, incentives, training, and technical infrastructure development.
4) International
This document summarizes an initiative focused on ethics, privacy, transparency and trust related to the use of location data. It discusses trends in these areas and introduces the Locus Charter, a set of draft principles for the responsible and ethical use of location data. Example projects funded by the initiative are also summarized, including tools for measuring representation in location datasets and understanding how location data is collected from mobile devices.
Stuart Macdonald steps through the process of creating a robust data management plan for researchers. Presented at the European Association for Health Information and Libraries (EAHIL) 2015 workshop, Edinburgh, 11 June 2015.
The document provides information on creating a data management plan (DMP) for grant applications. It discusses what a DMP is, why they are important, and what funders require in a DMP. A DMP outlines how research data will be collected, documented, stored, shared, and preserved. The document recommends addressing six key themes in a DMP: data types and standards; ethics and intellectual property; data access, sharing and reuse; short-term storage and management; long-term preservation; and resourcing. Developing a strong DMP helps researchers manage data effectively and makes data available and reusable by others.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
Kenya open data case 7.7.17 prof wafulaTom Nyongesa
This document summarizes Kenya's open data initiatives and policies. It discusses Kenya's open data national case study, key pillars of open data policy development, best practices for open data implementation, JKUAT's open data initiatives including its open data platform and policy, the Digital Health Applied Research Centre project, open data in agricultural research, and Kenya's draft national ICT policy which supports open data principles and use of data for e-services like e-health and e-agriculture. The document provides an overview of how Kenya is using open data to support smart and sustainable development.
This document summarizes Kenya's open data initiatives and policies. It discusses Kenya's open data national case study, key pillars of open data policy development, best practices for open data implementation, JKUAT's open data initiatives including its open data platform and policy, the Digital Health Applied Research Centre project, open data in agricultural research, and Kenya's draft national ICT policy which supports open data principles and use in various sectors like health, agriculture and more. The document provides an overview of how Kenya is working to develop its open data ecosystem through projects, policies and stakeholder engagement.
Data accessibility and the role of informatics in predicting the biosphereAlex Hardisty
The variety, distinctiveness and complexity of life – biodiversity in other words and by implication the ecosystems in which it is situated – is our life support system. It is absolutely essential and more important than almost everything else but it is typically taken for granted. Today’s big societal challenges – food and water security, coping with environmental change and aspects of human health – are beyond the abilities of any one individual or research group to solve. Solving them depends not only on collaboration to deliver the appropriate scientific evidence but increasingly on vast amounts of data from multiple sources (environmental, taxonomic, genomic and ecological) gathered by manual observation and automated sensors, digitisation, remote sensing, and genetic sequencing. In April 2012 we called the biodiversity and ecosystems research communities to arms to formulate a consensus view on establishing an infrastructure to improve the accessibility of the ever-increasing volumes of biological data. We published the whitepaper: “A decadal view of biodiversity informatics: challenges and priorities” that has since been viewed more than 24,000 times. We envisage a shared and maintained multi-purpose network of computationally-based processing services sitting on top of an open data domain. By open data domain we mean data that is accessible i.e., published, registered and linked. BioVeL, pro-iBiosphere, ViBRANT and other FP7 funded projects have all explored aspects of this vision.
Digital transformation to enable a FAIR approach for health data scienceVarsha Khodiyar
Invited talk for ConTech Pharma on 1st March 2022
Abstract
Health Data Research UK is the UK’s national institute for health data science, with a mission to unite the UK’s health data to enable discoveries that improve people’s lives. In this talk, Dr Varsha Khodiyar will outline how HDR UK is bringing together disparate health data from all four countries of the United Kingdom, creating the infrastructure to enable discovery of and access to health data, and the convening standards making bodies to improve data linkage and data reuse. Varsha will also discuss how HDR UK is moving beyond the traditional confines of FAIR data to also ensure that data sharing and data use is transparent and ‘fair’ for the patients and lay public who are the subjects of these datasets.
The document summarizes a presentation given by Tracey P. Lauriault on critiques and reflections of open data initiatives. Some key points from the presentation include:
- Open data definitions have evolved over time from sharing scientific data internationally to principles of open government data and 5 star deployment schemes.
- Most popular open data definitions center around access, redistribution, reuse and absence of technical restrictions.
- Examples of open data initiatives discussed include the Canadian Geospatial Data Infrastructure, which aims to provide comprehensive sharing of geospatial assets, and the Dublin Dashboard, which provides real-time city data.
- Considerations for open data include ensuring interaction with crowdsourced/volunteered data follows standards
Data management plans existed long before the NSF started requiring them. DMPs have inherent value despite their being relatively unknown to researchers until now. Proper, thorough data management plans are potentially a major time saver and a huge asset for the project. In this webinar, we will cover how to go beyond funder requirements and develop more thorough data DMPs The Gulf of Mexico Research Initiative requires an extensive data management plan for projects it funds; we will hear about their efforts and how they are planning to use the DMPTool going forward.
Data Sharing Principles and Legal Interoperability for Essential Biodiversity...agosti
The document discusses principles of open data sharing and legal interoperability of research data. It provides summaries of the GEO Data Sharing Principles from 2005 and a proposed updated version from 2015. The principles advocate sharing data as open data by default without charge or reuse restrictions. Exceptions can be made for reasons of national security, endangered species protection, or other restrictions allowed by law. The document also summarizes proposed principles from RDA/CODATA on facilitating lawful access to research data while balancing various legal interests through transparent communication of rights.
This document summarizes a presentation on open science and open data. It discusses the importance of open research data for reproducibility and innovation. It outlines key policy developments promoting open data, including funder data policies and journal data policies. It also describes CODATA's activities related to data policies, frameworks for developing open data strategies, and components of the international open science ecosystem.
Presentation on INSPIRE and Higher Education (1 of 2)JISC GECO
Presentation designed to explain the relationship between academic data and the EU INSPIRE Directive. Produced by staff from EDINA and the Digital Curation Centre.
This document summarizes a workshop on Linked Open Data in Agriculture that took place in Berlin on September 27-28, 2017. The workshop included two tracks on policy/strategy and technologies/applications. Goals were to share current practices, determine data demand and supply, discuss applications and next steps. Topics included research data sharing, open geodata, vocabularies, and applications in livestock and supply chain. Presentations and information are available online. Principles of findable, accessible, interoperable and reusable data were discussed. Actions include forming collaborations around specific tasks and data types. In conclusion, following FAIR principles and international cooperation were emphasized for advancing open data and innovation in agriculture.
Tracey P. Lauriault discusses open data and technological citizenship. She makes three key points:
1) Data are not objective or politically neutral, but are inseparable from the ideas, technologies, and contexts that produce them.
2) Technological citizenship involves engaging with data and technology as a form of political participation and action.
3) Various definitions and principles of open data have emerged over time from organizations aiming to make data accessible and shareable.
Europa requisitos y servicios en torno a los datos de investigacionmaredata
Europa requires and provides services around research data:
- It requires openly sharing research publications and data from publicly funded research by 2020. Countries will implement their own open access policies.
- It offers guidelines for researchers, infrastructure support, and funding incentives for open science practices like publishing with open access and sharing research data.
- The European Open Science Cloud aims to provide a supporting environment for open science through federated infrastructure and initiatives across member states.
FAIR data: what it means, how we achieve it, and the role of RDASarah Jones
Presentation on FAIR data, the FAIR Data Action Plan developed by the European Commission Expert Group and the role of the Research Data Alliance on implementing FAIR. The presentation was given at the RDAFinland workshop held on 6th June - https://www.csc.fi/web/training/-/rda_and_fair_supporting_finnish_researchers
I o dav data workshop prof wafula final 19.9.17Tom Nyongesa
The document summarizes an iODaV Data Workshop held at JKUAT in Kenya on open data and the JORD policy. It discusses why open data is important for reproducibility, innovation and scientific discovery. It outlines the FAIR principles for open data and metadata to make data findable, accessible, interoperable and reusable. It also discusses opportunities and challenges of open data for universities, including developing skills and infrastructure. Finally, it provides examples of open data initiatives at JKUAT including developing an open data policy, the iODaV program, contributions to national ICT policies, and the digital health applied research centre.
This document discusses data management plans (DMPs), which are brief plans that define how research data will be created, documented, stored, shared, and preserved. DMPs are often required as part of grant applications. The document provides an overview of why DMPs are important, how they benefit researchers and institutions, and key aspects to address in a DMP such as data organization, stakeholders, and making data FAIR (findable, accessible, interoperable, and reusable). Examples of DMPs from real projects are also presented.
CIARD Información accesible para todos (Inglés)RIBDA 2009
1. The document discusses CIARD, a new global partnership formed in 2008 to provide coherence between agricultural research information initiatives and ensure that information is accessible to all.
2. CIARD's vision is to make public agricultural research information widely accessible. It aims to coordinate efforts, promote common standards, and adopt open systems among partner organizations.
3. The document outlines CIARD's objectives, principles, and pathways to achieving its vision through capacity building, sharing content, technical coherence, and investment.
20170530_Open Research Data in Horizon 2020OpenAIRE
This document discusses open research data in Horizon 2020 projects. It provides an overview of the OpenAIRE network, the European Commission's open access mandate, and requirements for open research data under Horizon 2020. Projects starting in 2017 are included in the open data policy by default and must make their data openly available. Reasons for opting out of open data requirements are also presented.
Presented at the:
Canadian Aviation Safety Collaboration Forum
International Civil Aviation Organization (ICAO)
Montreal, QC
January 23, 2019
This presentation was made in real-time while attending the Forum. The objective was to observe and listen, and share some examples outside of this community that may provide insight about data sharing models with a focus on governance.
Big Data Europe: SC6 Workshop 3: The European Research Data Landscape: Opport...BigData_Europe
Slides of the keynote at the 3rd Big Data Europe SC6 Workshop co-located at SEMANTiCS2018 in Amsterdam (NL) on: The European Research Data Landscape: Opportunities for CESSDA by Peter Doorn, Director DANS, Chair, Science Europe W.G. on Research Data. Chair, CESSDA ERIC General Assembly
Securing, storing and enabling safe access to dataRobin Rice
Invited talk as part of Westminster Insight Research Data Management Forum, https://www.westminsterinsight.co.uk/event/3416/Research_Data_Management_Forum
This multi-level agent-based model was created to assess forest fire management in southern Switzerland. It simulates the daily movements of individuals to investigate the impact on fire occurrences. The model employs an open-source platform called GAMA to build spatially explicit agent-based simulations allowing multiple levels of modeling. Preliminary results show the model can perform a visual correlation between fire ignitions and human presence by tracking people moving on the road network and capturing population distribution over time. Investigation of firefighters' response efficiency is still ongoing.
The document discusses a simulation model called SIMARIS that couples a geographic information system (GIS) and an agent-based model (ABM) to simulate marine activities. It aims to represent multiple activities simultaneously, evaluate their impacts on marine protected areas, and identify potential conflict zones. The model integrates the GIS GRASS with the ABM platform GAMA using Python. Preliminary results from a test simulation in a 40km2 area of France show maps of boat traffic patterns over time and the consumption and regeneration of fishing resources like king scallops.
Data accessibility and the role of informatics in predicting the biosphereAlex Hardisty
The variety, distinctiveness and complexity of life – biodiversity in other words and by implication the ecosystems in which it is situated – is our life support system. It is absolutely essential and more important than almost everything else but it is typically taken for granted. Today’s big societal challenges – food and water security, coping with environmental change and aspects of human health – are beyond the abilities of any one individual or research group to solve. Solving them depends not only on collaboration to deliver the appropriate scientific evidence but increasingly on vast amounts of data from multiple sources (environmental, taxonomic, genomic and ecological) gathered by manual observation and automated sensors, digitisation, remote sensing, and genetic sequencing. In April 2012 we called the biodiversity and ecosystems research communities to arms to formulate a consensus view on establishing an infrastructure to improve the accessibility of the ever-increasing volumes of biological data. We published the whitepaper: “A decadal view of biodiversity informatics: challenges and priorities” that has since been viewed more than 24,000 times. We envisage a shared and maintained multi-purpose network of computationally-based processing services sitting on top of an open data domain. By open data domain we mean data that is accessible i.e., published, registered and linked. BioVeL, pro-iBiosphere, ViBRANT and other FP7 funded projects have all explored aspects of this vision.
Digital transformation to enable a FAIR approach for health data scienceVarsha Khodiyar
Invited talk for ConTech Pharma on 1st March 2022
Abstract
Health Data Research UK is the UK’s national institute for health data science, with a mission to unite the UK’s health data to enable discoveries that improve people’s lives. In this talk, Dr Varsha Khodiyar will outline how HDR UK is bringing together disparate health data from all four countries of the United Kingdom, creating the infrastructure to enable discovery of and access to health data, and the convening standards making bodies to improve data linkage and data reuse. Varsha will also discuss how HDR UK is moving beyond the traditional confines of FAIR data to also ensure that data sharing and data use is transparent and ‘fair’ for the patients and lay public who are the subjects of these datasets.
The document summarizes a presentation given by Tracey P. Lauriault on critiques and reflections of open data initiatives. Some key points from the presentation include:
- Open data definitions have evolved over time from sharing scientific data internationally to principles of open government data and 5 star deployment schemes.
- Most popular open data definitions center around access, redistribution, reuse and absence of technical restrictions.
- Examples of open data initiatives discussed include the Canadian Geospatial Data Infrastructure, which aims to provide comprehensive sharing of geospatial assets, and the Dublin Dashboard, which provides real-time city data.
- Considerations for open data include ensuring interaction with crowdsourced/volunteered data follows standards
Data management plans existed long before the NSF started requiring them. DMPs have inherent value despite their being relatively unknown to researchers until now. Proper, thorough data management plans are potentially a major time saver and a huge asset for the project. In this webinar, we will cover how to go beyond funder requirements and develop more thorough data DMPs The Gulf of Mexico Research Initiative requires an extensive data management plan for projects it funds; we will hear about their efforts and how they are planning to use the DMPTool going forward.
Data Sharing Principles and Legal Interoperability for Essential Biodiversity...agosti
The document discusses principles of open data sharing and legal interoperability of research data. It provides summaries of the GEO Data Sharing Principles from 2005 and a proposed updated version from 2015. The principles advocate sharing data as open data by default without charge or reuse restrictions. Exceptions can be made for reasons of national security, endangered species protection, or other restrictions allowed by law. The document also summarizes proposed principles from RDA/CODATA on facilitating lawful access to research data while balancing various legal interests through transparent communication of rights.
This document summarizes a presentation on open science and open data. It discusses the importance of open research data for reproducibility and innovation. It outlines key policy developments promoting open data, including funder data policies and journal data policies. It also describes CODATA's activities related to data policies, frameworks for developing open data strategies, and components of the international open science ecosystem.
Presentation on INSPIRE and Higher Education (1 of 2)JISC GECO
Presentation designed to explain the relationship between academic data and the EU INSPIRE Directive. Produced by staff from EDINA and the Digital Curation Centre.
This document summarizes a workshop on Linked Open Data in Agriculture that took place in Berlin on September 27-28, 2017. The workshop included two tracks on policy/strategy and technologies/applications. Goals were to share current practices, determine data demand and supply, discuss applications and next steps. Topics included research data sharing, open geodata, vocabularies, and applications in livestock and supply chain. Presentations and information are available online. Principles of findable, accessible, interoperable and reusable data were discussed. Actions include forming collaborations around specific tasks and data types. In conclusion, following FAIR principles and international cooperation were emphasized for advancing open data and innovation in agriculture.
Tracey P. Lauriault discusses open data and technological citizenship. She makes three key points:
1) Data are not objective or politically neutral, but are inseparable from the ideas, technologies, and contexts that produce them.
2) Technological citizenship involves engaging with data and technology as a form of political participation and action.
3) Various definitions and principles of open data have emerged over time from organizations aiming to make data accessible and shareable.
Europa requisitos y servicios en torno a los datos de investigacionmaredata
Europa requires and provides services around research data:
- It requires openly sharing research publications and data from publicly funded research by 2020. Countries will implement their own open access policies.
- It offers guidelines for researchers, infrastructure support, and funding incentives for open science practices like publishing with open access and sharing research data.
- The European Open Science Cloud aims to provide a supporting environment for open science through federated infrastructure and initiatives across member states.
FAIR data: what it means, how we achieve it, and the role of RDASarah Jones
Presentation on FAIR data, the FAIR Data Action Plan developed by the European Commission Expert Group and the role of the Research Data Alliance on implementing FAIR. The presentation was given at the RDAFinland workshop held on 6th June - https://www.csc.fi/web/training/-/rda_and_fair_supporting_finnish_researchers
I o dav data workshop prof wafula final 19.9.17Tom Nyongesa
The document summarizes an iODaV Data Workshop held at JKUAT in Kenya on open data and the JORD policy. It discusses why open data is important for reproducibility, innovation and scientific discovery. It outlines the FAIR principles for open data and metadata to make data findable, accessible, interoperable and reusable. It also discusses opportunities and challenges of open data for universities, including developing skills and infrastructure. Finally, it provides examples of open data initiatives at JKUAT including developing an open data policy, the iODaV program, contributions to national ICT policies, and the digital health applied research centre.
This document discusses data management plans (DMPs), which are brief plans that define how research data will be created, documented, stored, shared, and preserved. DMPs are often required as part of grant applications. The document provides an overview of why DMPs are important, how they benefit researchers and institutions, and key aspects to address in a DMP such as data organization, stakeholders, and making data FAIR (findable, accessible, interoperable, and reusable). Examples of DMPs from real projects are also presented.
CIARD Información accesible para todos (Inglés)RIBDA 2009
1. The document discusses CIARD, a new global partnership formed in 2008 to provide coherence between agricultural research information initiatives and ensure that information is accessible to all.
2. CIARD's vision is to make public agricultural research information widely accessible. It aims to coordinate efforts, promote common standards, and adopt open systems among partner organizations.
3. The document outlines CIARD's objectives, principles, and pathways to achieving its vision through capacity building, sharing content, technical coherence, and investment.
20170530_Open Research Data in Horizon 2020OpenAIRE
This document discusses open research data in Horizon 2020 projects. It provides an overview of the OpenAIRE network, the European Commission's open access mandate, and requirements for open research data under Horizon 2020. Projects starting in 2017 are included in the open data policy by default and must make their data openly available. Reasons for opting out of open data requirements are also presented.
Presented at the:
Canadian Aviation Safety Collaboration Forum
International Civil Aviation Organization (ICAO)
Montreal, QC
January 23, 2019
This presentation was made in real-time while attending the Forum. The objective was to observe and listen, and share some examples outside of this community that may provide insight about data sharing models with a focus on governance.
Big Data Europe: SC6 Workshop 3: The European Research Data Landscape: Opport...BigData_Europe
Slides of the keynote at the 3rd Big Data Europe SC6 Workshop co-located at SEMANTiCS2018 in Amsterdam (NL) on: The European Research Data Landscape: Opportunities for CESSDA by Peter Doorn, Director DANS, Chair, Science Europe W.G. on Research Data. Chair, CESSDA ERIC General Assembly
Securing, storing and enabling safe access to dataRobin Rice
Invited talk as part of Westminster Insight Research Data Management Forum, https://www.westminsterinsight.co.uk/event/3416/Research_Data_Management_Forum
This multi-level agent-based model was created to assess forest fire management in southern Switzerland. It simulates the daily movements of individuals to investigate the impact on fire occurrences. The model employs an open-source platform called GAMA to build spatially explicit agent-based simulations allowing multiple levels of modeling. Preliminary results show the model can perform a visual correlation between fire ignitions and human presence by tracking people moving on the road network and capturing population distribution over time. Investigation of firefighters' response efficiency is still ongoing.
The document discusses a simulation model called SIMARIS that couples a geographic information system (GIS) and an agent-based model (ABM) to simulate marine activities. It aims to represent multiple activities simultaneously, evaluate their impacts on marine protected areas, and identify potential conflict zones. The model integrates the GIS GRASS with the ABM platform GAMA using Python. Preliminary results from a test simulation in a 40km2 area of France show maps of boat traffic patterns over time and the consumption and regeneration of fishing resources like king scallops.
The document describes a project analyzing maritime traffic in coastal zones of France using data from semaphore stations. It outlines 3 main tasks: 1) cleaning the raw semaphore data, 2) extracting routes of boat movements, and 3) analyzing the temporal evolution of traffic patterns. Python scripts are used to automatically standardize the data and extract routes between defined coordinate points, with the goal of quantifying and grouping traffic flows over time for further study.
This document outlines a presentation on implementing a vertical sorting model in GIS. The main goals are to produce a useful tool for researchers to analyze river morphology and granulometric profiles, avoiding hard field work. It will use the equilibrium sorting model by Blom & Parker, which can consider sediment mixtures, vertical fluxes, and bedforms in a powerful yet complex way. GIS is well suited for this as it can handle geospatial data and GRASS GIS specifically allows users to develop new analysis capabilities as an open source project with an active community.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
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
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
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.
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...
UNEP-MAP Data Policy in brief
1. The MAP Data Policy: implications for
Contracting Parties
October 2022
Annalisa Minelli – Knowledge Management Officer
annalisa.minelli@info-rac.org
2. Presentation Outline
• The approved MAP Data Policy: document, actors, objectives
• Principles behind prescriptions
• Implications for Contracting Parties
3. Data Policy: the document
Adoption of the Data Policy:
UNEP/MED IG.25/27, Decision IG.25/10 (p. 353)
• Approved during the Convention for the Protection of the
Marine Environment and the Coastal Region of the
Mediterranean (Barcelona Convention) and its Protocols
at their 22nd Meeting
• Aim to achieve a base level of legal interoperability
• Establishing base principles, objectives and means to
achieve this interoperability for each data flow belonging
to the MAP
4. Data Policy: actors
The decision (UNEP/MED IG.25/27, Decision IG.25/10) is about:
1. Adopt the United Nations Environment Programme/Mediterranean Action Plan (UNEP/MAP) Data Policy as set out in
Annex I to the present Decision;
2. Request the Secretariat (INFO/RAC) to provide the necessary technical support to Contracting Parties and to address
any needs identified to fully implement the UNEP/MAP Data Policy;
3. Call upon the Contracting Parties to take effective measures to implement the UNEP/MAP Data Policy.
5. Data Policy: actors
The decision (UNEP/MED IG.25/27, Decision IG.25/10) is about:
1. Adopt the United Nations Environment Programme/Mediterranean Action Plan (UNEP/MAP) Data Policy as set out in
Annex I to the present Decision;
2. Request the Secretariat (INFO/RAC) to provide the necessary technical support to Contracting Parties and to address
any needs identified to fully implement the UNEP/MAP Data Policy;
3. Call upon the Contracting Parties to take effective measures to implement the UNEP/MAP Data Policy.
What we are doing, as INFO/RAC
6. Data Policy: actors
The decision (UNEP/MED IG.25/27, Decision IG.25/10) is about:
1. Adopt the United Nations Environment Programme/Mediterranean Action Plan (UNEP/MAP) Data Policy as set out in
Annex I to the present Decision;
2. Request the Secretariat (INFO/RAC) to provide the necessary technical support to Contracting Parties and to address
any needs identified to fully implement the UNEP/MAP Data Policy;
3. Call upon the Contracting Parties to take effective measures to implement the UNEP/MAP Data Policy.
What the CP are supposed to
do, with the help of INFO/RAC
7. Data Policy: objectives
• availability of latest data and maintenance of long-term
series
• exploitation, re-use and re-combination of data from
different sources in different frameworks and media
• full, free and open access to all kinds of data, where
possible, whilst recognizing and respecting the variety of
business models and data ownerships
• protection of integrity, transparency, and traceability in
environmental data, analysis and forecasts
• recognition of data providers and of their intellectual
property rights through citation and data licenses
• meeting relevant national legislations and government
guidance on the management and distribution of
environmental information
• implementation of INSPIRE, SEIS principles, Copernicus
and GEOSS data sharing principles
• interoperability and use of standards
• use of crowd sourced and citizen science data
• recognition of the quality of data through quality
assurance and quality control procedures
• publication of relevant metadata
• stewardship and sharing of data from research projects.
Support – Promote – Enable
(p. 358)
8. Data Policy: objectives
Support
Promote
Enable
availability of latest data
and maintenance of
long-term series
re-use of data
from different
sources
full, free and
open access
protection of integrity,
transparency, and
traceability of
environmental data
recognition of
intellectual
property rights
meeting relevant
national legislations
implementation of INSPIRE, SEIS
principles, Copernicus and GEOSS
data sharing principles
interoperability and
use of standards
citizen
science data
quality assurance
and quality control
procedures
publication of
metadata
research data
stewardship
9. Data Policy: objectives
Support
Promote
Enable
availability of latest data
and maintenance of
long-term series
re-use of data
from different
sources
full, free and
open access
protection of integrity,
transparency, and
traceability of
environmental data
recognition of
intellectual
property rights
meeting relevant
national legislations
implementation of INSPIRE, SEIS
principles, Copernicus and GEOSS
data sharing principles
interoperability and
use of standards
citizen
science data
quality assurance
and quality control
procedures
publication of
metadata
research data
stewardship
Elements
involved
10. Data Policy: objectives
Support
Promote
Enable
availability of latest data
and maintenance of
long-term series
re-use of data
from different
sources
full, free and
open access
protection of integrity,
transparency, and
traceability of
environmental data
recognition of
intellectual
property rights
meeting relevant
national legislations
implementation of INSPIRE, SEIS
principles, Copernicus and GEOSS
data sharing principles
interoperability and
use of standards
citizen
science data
quality assurance
and quality control
procedures
publication of
metadata
research data
stewardship
Qualities of
the elements
11. Data Policy: objectives
Support
Promote
Enable
availability of latest data
and maintenance of
long-term series
re-use of data
from different
sources
full, free and
open access
protection of integrity,
transparency, and
traceability of
environmental data
recognition of
intellectual
property rights
meeting relevant
national legislations
implementation of INSPIRE, SEIS
principles, Copernicus and GEOSS
data sharing principles
interoperability and
use of standards
citizen
science data
quality assurance
and quality control
procedures
publication of
metadata
research data
stewardship
Constraints
12. Data Policy: objectives
Support
Promote
Enable
availability of latest data
and maintenance of
long-term series
re-use of data
from different
sources
full, free and
open access
protection of integrity,
transparency, and
traceability of
environmental data
recognition of
intellectual
property rights
meeting relevant
national legislations
implementation of INSPIRE, SEIS
principles, Copernicus and GEOSS
data sharing principles
interoperability and
use of standards
citizen
science data
quality assurance
and quality control
procedures
publication of
metadata
research data
stewardship
Principles
13. Principles behind prescriptions
GENERAL: Data should be managed as close as possible to its source, collected once, shared with others,
readily available to fulfil UNEP-MAP mandate. (p.356)
NO data duplication
YES fair and FAIR organization
Findable
Accessible
Interoperable
Reusable
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for
scientific data management and stewardship. Sci Data 3, 160018 (2016).
https://doi.org/10.1038/sdata.2016.18
14. Principles behind prescriptions
GENERAL: Data should be managed as close as possible to its source, collected once, shared with others,
readily available to fulfil UNEP-MAP mandate
NO duplication of efforts
YES exploitation of others’ work (where available)
15. Principles behind prescriptions
GENERAL: Data should be managed as close as possible to its source, collected once, shared with others,
readily available to fulfil UNEP-MAP mandate
NO data ownership
YES data stewardship
«Data is MINE and I preserve it on my PC»
«Data is a PUBLIC GOOD, I understand its
usefulness for everyone, I will do anything
I can to promote progress»
European Commission, Directorate-General for Research and Innovation, Open innovation, open science,
open to the world : a vision for Europe, Publications Office,
2016, https://data.europa.eu/doi/10.2777/061652
to
from
16. Principles behind prescriptions
A. Interoperability and use of Standards
Interoperability means that any piece of information can be
shared among multiple actors with the same quality level (quality
of instruments, quality of information, quality of elaboration)
This is possible only by means of Standards: «universally»
recognised rules to share information (protocols)
17. Principles behind prescriptions
B. Open Access
Data must be as open as possible, respecting the constraints
imposed by local legislation, sensitivity of data, and copyrights
Open Access means ensure the possibility
for less rich Countries to access knowledge
We don’t want a Two-speed
world, we want a Unique world
Fallout of data collected by means of public
funds should be available for the wide public
18. Principles behind prescriptions
B. Open Access
Data must be as open as possible, respecting the constraints
imposed by local legislation, sensitivity of data, and copyrights
To formalize Open Access we need
Open Data licenses:
• Public Domain (CC-0)
• Creative Commons Attribution (CC-
BY)
19. Principles behind prescriptions
B. Open Access
Data must be as open as possible, respecting the constraints
imposed by local legislation, sensitivity of data, and copyrights
To formalize Open Access we need
Open Data licenses:
• Public Domain (CC-0)
• Creative Commons Attribution (CC-
BY)
Data Policy
20. Principles behind prescriptions
B. Open Access
Data must be as open as possible, respecting the constraints
imposed by local legislation, sensitivity of data, and copyrights
To formalize Open Access we need
Open Data licenses:
• Public Domain (CC-0)
• Creative Commons Attribution (CC-
BY)
Eventually
sensitive
data
21. Principles behind prescriptions
C. Re-use of data
Since we don’t want to duplicate efforts, data must be
enabled to be reused, exploited and recombined from
different sources to different frameworks and media
To be Reusable:
• meta(data) are richly described with a plurality of
accurate and relevant attributes
• (meta)data are released with a clear and accessible data
usage license
• (meta)data are associated with detailed provenance
• (meta)data meet domain-relevant community standards
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for
scientific data management and stewardship. Sci Data 3, 160018 (2016).
https://doi.org/10.1038/sdata.2016.18
relevant attributes
license
provenance
standards
22. Principles behind prescriptions
C. Re-use of data
Since we don’t want to duplicate efforts, data must be
enabled to be reused, exploited and recombined from
different sources to different frameworks and media
To be Reusable:
• meta(data) are richly described with a plurality of
accurate and relevant attributes
• (meta)data are released with a clear and accessible data
usage license
• (meta)data are associated with detailed provenance
• (meta)data meet domain-relevant community standards
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for
scientific data management and stewardship. Sci Data 3, 160018 (2016).
https://doi.org/10.1038/sdata.2016.18
provenance
The provenance of data must be clear and stated
in the metadata: owner, contact person and
responsible for data must be clearly identified
23. Principles behind prescriptions
C. Re-use of data
Since we don’t want to duplicate efforts, data must be
enabled to be reused, exploited and recombined from
different sources to different frameworks and media
To be Reusable:
• meta(data) are richly described with a plurality of
accurate and relevant attributes
• (meta)data are released with a clear and accessible data
usage license
• (meta)data are associated with detailed provenance
• (meta)data meet domain-relevant community standards
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for
scientific data management and stewardship. Sci Data 3, 160018 (2016).
https://doi.org/10.1038/sdata.2016.18
relevant attributes
The choice of attributes is codified and often
stated in vocaboulary or standards. Relevant
attributes increase the value of data.
24. Principles behind prescriptions
D. INSPIRE, SEIS, Copernicus and GEOSS principles
• Data should be collected only once and kept where it can be maintained most effectively.
• It should be possible to combine seamless spatial information from different sources across
Europe and share it with many users and applications.
• It should be possible for information collected at one level/scale to be shared with all
levels/scales; detailed for thorough investigations, general for strategic purposes.
• Geographic information needed for good governance at all levels should be readily and
transparently available.
• Easy to find what geographic information is available, how it can be used to meet a particular need,
and under which conditions it can be acquired and used.
Infrastructure for Stadard Information in Europe (INSPIRE)
25. Principles behind prescriptions
D. INSPIRE, SEIS, Copernicus and GEOSS principles
• Managed as close as possible to its source.
• Collected once and shared with others for many purposes.
• Readily available to easily fulfil reporting obligations.
• Easily accessible to all users.
• Accessible to enable comparisons at the appropriate geographical scale and the participation of
citizens.
• Fully available to the general public and at national level in the relevant national language(s).
• Supported through common, free, open software standards.
Shared Environmental Information System (SEIS)
26. Principles behind prescriptions
D. INSPIRE, SEIS, Copernicus and GEOSS principles
The vast majority of data/information delivered by Copernicus is made available and accessible to
any citizen, and any organisation around the world on a free, full, and open basis.
Copernicus
27. Principles behind prescriptions
D. INSPIRE, SEIS, Copernicus and GEOSS principles
• data, metadata and products will be shared as Open Data by default, by making them available as
part of the GEOSS Data Collection of Open Resources for Everyone (Data-CORE) without charge or
restrictions on reuse, subject to the conditions of registration and attribution when the data are
reused;
• where international instruments, national policies or legislation preclude the sharing of data as
Open Data, data should be made available with minimal restrictions on use and at no more than
the cost of reproduction and distribution;
• all shared data, products and metadata will be made available with minimum time delay.
Group on Earth Observation System of Systems (GEOSS)
28. Implications for Contracting Parties
• If there are adequate competencies, data must be
handled as close as possible to its source, following
the principle to do not duplicate data.
• Data shall be made available with the minimum time
delay at no cost.
• Data created by UNEP-MAP, Regional Activity Centers,
and MAP components should be as open as possible
(fully available to the general public), where for
“open” we intend free, accessible without further
barriers and covered by an open license.
• Data should be given with location (or
Latitude/Longitude coordinates) whenever possible
for environmental data.
Common implications for all the data:
29. Implications for Contracting Parties
• In the case of data owned by the Contracting Parties
or third parties, eventual barriers or limitations to
data sharing must be verified to assess their
compliance with the data policy before any action to
be pursued on data. Also, intellectual property rights,
use or reuse conditions, confidentiality, and data
quality statement must be verified.
• If data is “restricted” or strategic for the Contracting
Party it will be not opened to the large public but it
will be shared only among appropriate (authorized)
users.
• When necessary, confidential, or sensitive data could
be reclassified or aggregated by cooperating with
INFO/RAC in order to open the dataset.
• If data is matter of scientific publication or it is
involved in consortium contract or patent
registration, it could be subjected to embargo. To
formalize the embargo (which should not last less
than 24 months, ideally) the partner must motivate
the request (for embargo) and in the metadata
embargo duration should be explicitly stated.
Particular implications for sensitive data:
30. Implications for Contracting Parties
• In particular, restrictions to put attention on are:
o Binding rules
o International treaties
o National legislation
o Personal data (protection of)
o Statistical confidentiality
o Protection of intellectual property rights
o Protection of national security
o Defense purposes
o Public security
Particular implications for sensitive data:
31. Implications for Contracting Parties
• In particular, restrictions to put attention on are:
o Binding rules
o International treaties
o National legislation
o Personal data (protection of)
o Statistical confidentiality
o Protection of intellectual property rights
o Protection of national security
o Defense purposes
o Public security
Particular implications for sensitive data:
32. Thanks for the Attention
Questions
?
Annalisa.Minelli@info-rac.org
You can reuse this
work upon attribution