The following presentation was given by Daniel Bachlechner (Fraunhofer ISI and e-SIDES ) at the 13th Pre-ICIS Workshop on Information Security and Privacy (WISP 2018) held in San Francisco on December 13, 2018.
Why not all good technologies get happily embraced by people by Pille Pruulma...DigiComNet
Ms. Pille Pruulmann-Vengerfeldt is a Professor of Media and Communication at the University of Malmo where she teaches courses and researches on the use and application of new media, Internet-user typologies, eGovernment, and museum communications. She has authored publications on youth participation, online content creation, the digital divide in Europe, and museum technologies. Ms. Pille Pruulmann-Vengerfeldt has a PhD in Media and Communication from the University of Tartu. She speaks English, Estonian, German, and Russian.
Platform Strategy and Data-driven development in Pharmaceutical IndustryLukas Ott
The document discusses platform strategy and data-driven development in the pharmaceutical industry. It outlines the drug development process from target identification through discovery to approved product. It also discusses moving from enterprise architecture to platform strategy execution and global platform strategy as a foundation. Several use cases for data analytics are presented, including using natural language processing and machine learning to simplify compliance, optimize clinical trials, stay on top of research trends, and accelerate time to market.
Why Data is Becoming the Most Valuable Asset Companies PossesOSTHUS
The world is changing at a rapid pace. New varieties of data continue to spring up and be made available for integration and knowledge improvement across many domains. Knowledge engineering, using advanced techniques in data science, is therefore moving to the forefront of technology and IT concerns at many companies. We see this in the expansion of cloud technologies, semantic technologies, data analytics, and the construction of Data Lakes. Understanding one’s data and being able to derive complex patterns of interest from across a multitude of different data sources (public and private) should be of paramount concern for companies in the pharmaceutical, crop science and life science industries. Companies who embrace knowledge engineering practices will possess a distinct advantage in the coming years due to their ability to integrate and use data to their advantage. This talk will discuss recent trends in data science and will highlight some of the main points to consider for taking advantage of these new technologies and approaches. We will also cover certain lessons learned from real-world industry use cases to highlight how people are using these technologies for improved business benefits.
This presentation was provided by Daniel Calto of Elsevier during the NISO virtual conference, Research Information Systems: The Connections Enabling Collaboration, held on August 16, 2017.
626 Information leakage and Data Loss Prevention ToolsSplitty
This document discusses information leakage and data loss prevention (DLP) tools. It begins by defining information leakage as any accidental or malicious access of unauthorized parties to non-public data. Examples of information leakage like data breaches at Sony and the NIH are provided. The document then discusses why executives should care about information leakage due to its high costs, and how DLP tools can help defend against it by managing, discovering, monitoring and protecting sensitive data across networks and devices. Lastly, it provides a checklist and best practices for implementing a successful DLP program.
An Introduction to the Health Information Technology for Economic and Clinical Health Act -- HITECH and electronic medical records -- part of the economic stimulus package.
Poster presentation of the thesis conducted on the topic Data Security in Pharmaceutical and Healthcare: Analysis of Necessary Web Application Security Testing Tools.
Why not all good technologies get happily embraced by people by Pille Pruulma...DigiComNet
Ms. Pille Pruulmann-Vengerfeldt is a Professor of Media and Communication at the University of Malmo where she teaches courses and researches on the use and application of new media, Internet-user typologies, eGovernment, and museum communications. She has authored publications on youth participation, online content creation, the digital divide in Europe, and museum technologies. Ms. Pille Pruulmann-Vengerfeldt has a PhD in Media and Communication from the University of Tartu. She speaks English, Estonian, German, and Russian.
Platform Strategy and Data-driven development in Pharmaceutical IndustryLukas Ott
The document discusses platform strategy and data-driven development in the pharmaceutical industry. It outlines the drug development process from target identification through discovery to approved product. It also discusses moving from enterprise architecture to platform strategy execution and global platform strategy as a foundation. Several use cases for data analytics are presented, including using natural language processing and machine learning to simplify compliance, optimize clinical trials, stay on top of research trends, and accelerate time to market.
Why Data is Becoming the Most Valuable Asset Companies PossesOSTHUS
The world is changing at a rapid pace. New varieties of data continue to spring up and be made available for integration and knowledge improvement across many domains. Knowledge engineering, using advanced techniques in data science, is therefore moving to the forefront of technology and IT concerns at many companies. We see this in the expansion of cloud technologies, semantic technologies, data analytics, and the construction of Data Lakes. Understanding one’s data and being able to derive complex patterns of interest from across a multitude of different data sources (public and private) should be of paramount concern for companies in the pharmaceutical, crop science and life science industries. Companies who embrace knowledge engineering practices will possess a distinct advantage in the coming years due to their ability to integrate and use data to their advantage. This talk will discuss recent trends in data science and will highlight some of the main points to consider for taking advantage of these new technologies and approaches. We will also cover certain lessons learned from real-world industry use cases to highlight how people are using these technologies for improved business benefits.
This presentation was provided by Daniel Calto of Elsevier during the NISO virtual conference, Research Information Systems: The Connections Enabling Collaboration, held on August 16, 2017.
626 Information leakage and Data Loss Prevention ToolsSplitty
This document discusses information leakage and data loss prevention (DLP) tools. It begins by defining information leakage as any accidental or malicious access of unauthorized parties to non-public data. Examples of information leakage like data breaches at Sony and the NIH are provided. The document then discusses why executives should care about information leakage due to its high costs, and how DLP tools can help defend against it by managing, discovering, monitoring and protecting sensitive data across networks and devices. Lastly, it provides a checklist and best practices for implementing a successful DLP program.
An Introduction to the Health Information Technology for Economic and Clinical Health Act -- HITECH and electronic medical records -- part of the economic stimulus package.
Poster presentation of the thesis conducted on the topic Data Security in Pharmaceutical and Healthcare: Analysis of Necessary Web Application Security Testing Tools.
e-SIDES workshop at BDV Meet-Up, Sofia 14/05/2018e-SIDES.eu
The following presentation was given at the workshop "Technology solutions for privacy issues: what is the best way forward?" organized by e-SIDES at the BDVe Meet-up in Sofia on May 14, 2018. The workshop, chaired by Gabriella Cattaneo from IDC, involved stakeholders from ICT-18 projects.
BDVe Webinar Series - Why are privacy-preserving technologies not used more w...e-SIDES.eu
The following presentation was given by Daniel Bachlechner (Fraunhofer ISI & e-SIDES) during the BDVe webinar "New challenges for data regulation beyond the GDPR: how to assess risks and develop tools in an era of AI?" held on January 31, 2020.
BDVe Webinar Series - Why are privacy-preserving technologies not used more w...Big Data Value Association
What approaches are being taken to tackle the policy challenges within the big data landscape, and how are these solutions coping in reality? This webinar will address these issues through the perspective of two projects: e-SIDES and SMOOTH. Daniel Bachlechner, of e-SIDES, will discuss the organizational and technical challenges that privacy-preserving big data technologies present, and how an increased level of dialogue between stakeholders can pave the way for appropriate and fair solutions. Rosa M. Araujo Rivero will delve into the main challenges experienced by SMEs and startups in dealing with GDPR compliance. Rosa’s work with the SMOOTH project will demonstrate how the proposed solutions are experienced in practice.
Data- and database security & GDPR: end-to-end offerCapgemini
This document discusses Capgemini and Sogeti's end-to-end offering for database security and GDPR compliance. It outlines a four-phase approach including a GDPR readiness assessment, roadmap development, privacy impact assessment, and implementing database security solutions. Each phase has defined activities, timelines, and results to help organizations assess their GDPR compliance and secure databases containing personal data. The offering is designed to help organizations address new accountability and security requirements under the upcoming GDPR regulation.
Governance of Data Sharing in Agri-Food - towards common guidelinesSjaak Wolfert
Big Data is becoming a new asset in the agri-food sector including enterprise data from operational systems, sensor data, farm equipment data, etc. Recently, Big Data applications are being implemented, aiming at improving farm and chain performance. Many companies are refraining from sharing data because of the fear of governance issues such as data security, privacy and liability. Moreover, they are often in a deadlock or afraid to take the first step even though they expect to develop new business with data. To accelerate the development of Big Data applications, this paper analyses governance issues and introduces a set of guidelines for governance of data sharing in agri-food networks. A framework for analysis was derived from literature and used to identify lessons learned from recent projects or initiatives. From these results, a set of draft guidelines was developed. The framework and guidelines were evaluated in a workshop. The framework consists of factors that are related to governance on data sharing in networks. Internal factors are: efficiency, effectiveness, inclusiveness, legitimacy & accountability, credibility and transparency. External factors are: political, economic, social, technological, legal and environmental factors. For each of these factors, guidelines are provided in terms of: issues to be addressed, best practices and lessons learned from other projects and initiatives. It is concluded that the framework is complete in covering all relevant issues on governance in data sharing but the guidelines must be considered as a first set, which can be further improved and extended in the future. A wiki-type-of-website could help to upscale the guidelines at a global level. The guidelines could also be further refined accounting for different maturity levels of agri-food networks. The guidelines in this paper are considered to be a valuable step into the direction of solving governance issues in data sharing, which is expected to accelerate Big Data applications in the agri-food domain.
Ciso round table on effective implementation of dlp & data securityPriyanka Aash
The document discusses an effective implementation of data loss prevention (DLP) and data security. It covers key factors like the evolving threat landscape, business drivers for DLP, common challenges, and approaches to solve data security issues. An effective methodology is proposed, including identifying critical data and channels, deploying suitable policies, monitoring incidents, and establishing governance through continuous review and improvement. Critical success factors include business involvement, a phased implementation approach, and repeating the plan-do-check-act cycle periodically. The expected project outcomes are protection of critical channels, improved data tracking and awareness, and happier customers and auditors.
e-SIDES workshop at ICT 2018, Vienna 5/12/2018e-SIDES.eu
This document summarizes a session discussing how to build the next privacy and security research agenda for big data. The session included an introduction, a discussion of the e-SIDES community position paper and process for providing input, a mentimeter voting activity, and a panel on ensuring responsible research and innovation responds to real needs. The panel featured representatives from universities and research organizations discussing issues like integrating privacy from the start, understanding cultural and regional differences, and ensuring research aligns with societal values and needs. The position paper and future research agenda aim to provide recommendations for an ethically sound approach to big data.
e-SIDES workshop at ICE-IEEE Conference, Madeira 28/06/2017e-SIDES.eu
This document summarizes an e-SIDES workshop on societal and ethical challenges in the era of big data. The workshop was held on June 28, 2017 in Madeira, Portugal and included presentations on ethical and legal issues by Gabriella Cattaneo and societal and economic issues by Daniel Bachlechner. It also outlined an interactive session on these topics and next steps for the e-SIDES project, which aims to improve dialogue around big data technologies and address related ethical concerns.
This document outlines a roadmap for research in electronic governance over the next decade. It identifies four grand challenges: 1) Model-based collaborative governance to improve policy modeling and simulation; 2) Data-powered collective intelligence and action to leverage real-time open data; 3) Establishing a government service utility to provide ubiquitous, standardized public services; and 4) Developing a science base for ICT-enabled governance to systematize the field. For each challenge, it discusses short and long-term research directions to address gaps between current governance and a rapidly changing digital society. The overall goal is to transform policy-making using collaborative models, robust data analysis, and innovative digital service delivery.
The WITDOM first project presentation has been updated to include a summary of the results corresponding to the first 18 months of the project. The presentation includes a high-level overview of the project scenarios, methodologies to elicit requirements and to formalize them into technical requirements, as well as the initial architecture.
Access denied? Barriers for staff accessing, using and sharing published info...Catherine Ebenezer
This document presents a theoretical model of barriers that NHS staff face in accessing and sharing published information online. The model identifies several contributory factors, including attitude toward risk, inter-professional competition, external influences from regulations and oversight bodies, organizational information security posture, and culture of innovation. The researcher conducted a qualitative case study with interviews and document analysis at three NHS trusts to develop and examine this model of factors that can hinder online information use within the NHS in England.
Presentation on key legal issues regarding use and developments of BOTs, AI - GDPR, Data Protection. Case study BRISbot. Presentation delivered at Epicenter 30 of May 2017 in partnership with BRIS and Microsoft.
This document provides information about the DAPSI Open Call #1 webinar for applicants. It discusses the DAPSI project which aims to foster research in data portability through funding and services for researchers, SMEs, and startups. The incubation program will support up to 50 third parties with up to 150k Euros each over 9-10 months. The document reviews eligibility criteria, the evaluation process, and timeline for the first open call with an April 22 deadline. Infrastructure and tools are also described, including a support ticketing system, training resources, and free accounts on the FIWARE Lab cloud platform.
Guidelines for governance of data sharing in agri foodSjaak Wolfert
Big Data is becoming a new asset in the agri-food sector including enterprise data from operational systems, sensor data, farm equipment data, etc. Recently, Big Data applications are being implemented to improve farm and chain performance in agri-food networks. Still, many companies are refraining from sharing data because of fear of governance issues such as data insecurity, or lack of privacy or liability, among others. To overcome such barriers for developments with Big Data, this paper aims at: 1) analysing governance issues in agri-food networks, and 2) introducing a set of guidelines for data-sharing. Based on a literature review, a framework for analysing agri-food networks was developed, with internal governance factors (efficiency, effectiveness, inclusiveness, legitimacy & accountability, credibility and transparency) and external governance factors (political, economic, social, technological, legal and environmental factors). The framework contributes to development of a set of draft guidelines. Accordingly, for each factor, the guidelines address issues, best practices and lessons learned from other projects and initiatives. The approach developed in this paper creates a baseline for possible future developments of Big data in terms of 1) upscaling of the guidelines at a global level, 2) refining and fine-tuning of the guidelines for context specific agri-food networks, and 3) contributing to solving governance challenges in data sharing. In the future, the relevance of Big Data in the agri-food domain is expected to increase, and so are the contributions of this approach.
The document is a 4-page curriculum vitae for Emily Thompson. It outlines her professional qualifications and experience in information governance, data privacy, and project management. She has over 6 years of experience in these areas working for PwC. Some of her key projects include managing GDPR compliance reviews and assessments for various global companies. She also developed PwC's GDPR assessment tool and is considered a leading expert in operational impacts of the GDPR.
This document summarizes 10 research papers related to privacy and security aspects of big data. It discusses the key challenges around big data privacy including how large amounts of consumer data collected by companies may be misused and how securely storing and analyzing this information is critical. Various papers propose mechanisms for encrypting data and complying with data privacy laws. Overall, the review finds that big data brings important security and privacy issues given its scale, and continued research is needed to develop solutions that balance data needs with individual privacy.
Privacy, Accountability and Trust Privacy, Accountability and Trust Privacy, ...Karlos Svoboda
The document provides an overview of privacy, accountability and trust challenges and opportunities. It covers three perspectives: business side, user side, and architecture side. On the business side, it addresses the service value chain and analyzes behavioral tracking and profiling. It also briefly introduces monetizing privacy. On the user side, it covers technologies for policy display, informed consent, and transparency. On the architecture side, it focuses on privacy aspects of identity management, accountability, and trust frameworks. The document identifies means to enhance privacy protection from each perspective and makes recommendations to support policy initiatives and the development of privacy-preserving technologies.
The document discusses the "consumerisation of IT" where trends and technologies originating from consumer markets are increasingly being used in business settings. This is driven by factors like improved mobile devices, cloud services, and changing user expectations of consumer technologies in their personal and professional lives. While this poses risks to corporate IT like security and manageability issues, it also presents opportunities if IT can understand and adapt to these trends rather than fight them. The document provides examples of consumer technologies entering businesses and survey results on the extent companies are seeing this occur independently of IT strategy. It also outlines a balancing act for IT in addressing concerns while embracing opportunities and tips for policies, processes and skills to help manage the consumerisation of IT.
Big data adoption: State of the art and Research challengesNurul Mahfuz
This document summarizes a literature review on big data adoption that identified 42 significant factors and theoretical models used in previous studies. It outlines the paper's contributions in presenting the state of the art on models used for big data adoption and identifying adoption factors and challenges. The paper's methodology involved searching 8 databases using 5 keywords to find relevant papers published between 2015-2018. Key findings included that the most common models were TOE, DOI, TAM, and TTF frameworks, and that technology, organization, environment, and innovation-related factors influenced adoption. Challenges in current research were the theoretical models and factors studied, limited domains and populations, and need for more empirical studies.
Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019...e-SIDES.eu
This is the slide-deck of the community event held on November 14, 2019 in Brussels, titled "Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019". It includes the presentations given by the speakers.
"Towards Value-centric Big Data: Community Position Paper" Daniel Bachlechner...e-SIDES.eu
The document summarizes the work of the e-SIDES community towards developing a position paper on responsible and value-centric big data. It discusses the community's goals of identifying ethical issues, technologies, and opportunities related to big data. It also outlines the structure and purpose of the position paper in documenting challenges, stakeholders perspectives, and recommendations. Next steps include finalizing a draft of the paper by September and presenting it at a conference in November.
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What approaches are being taken to tackle the policy challenges within the big data landscape, and how are these solutions coping in reality? This webinar will address these issues through the perspective of two projects: e-SIDES and SMOOTH. Daniel Bachlechner, of e-SIDES, will discuss the organizational and technical challenges that privacy-preserving big data technologies present, and how an increased level of dialogue between stakeholders can pave the way for appropriate and fair solutions. Rosa M. Araujo Rivero will delve into the main challenges experienced by SMEs and startups in dealing with GDPR compliance. Rosa’s work with the SMOOTH project will demonstrate how the proposed solutions are experienced in practice.
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This document discusses Capgemini and Sogeti's end-to-end offering for database security and GDPR compliance. It outlines a four-phase approach including a GDPR readiness assessment, roadmap development, privacy impact assessment, and implementing database security solutions. Each phase has defined activities, timelines, and results to help organizations assess their GDPR compliance and secure databases containing personal data. The offering is designed to help organizations address new accountability and security requirements under the upcoming GDPR regulation.
Governance of Data Sharing in Agri-Food - towards common guidelinesSjaak Wolfert
Big Data is becoming a new asset in the agri-food sector including enterprise data from operational systems, sensor data, farm equipment data, etc. Recently, Big Data applications are being implemented, aiming at improving farm and chain performance. Many companies are refraining from sharing data because of the fear of governance issues such as data security, privacy and liability. Moreover, they are often in a deadlock or afraid to take the first step even though they expect to develop new business with data. To accelerate the development of Big Data applications, this paper analyses governance issues and introduces a set of guidelines for governance of data sharing in agri-food networks. A framework for analysis was derived from literature and used to identify lessons learned from recent projects or initiatives. From these results, a set of draft guidelines was developed. The framework and guidelines were evaluated in a workshop. The framework consists of factors that are related to governance on data sharing in networks. Internal factors are: efficiency, effectiveness, inclusiveness, legitimacy & accountability, credibility and transparency. External factors are: political, economic, social, technological, legal and environmental factors. For each of these factors, guidelines are provided in terms of: issues to be addressed, best practices and lessons learned from other projects and initiatives. It is concluded that the framework is complete in covering all relevant issues on governance in data sharing but the guidelines must be considered as a first set, which can be further improved and extended in the future. A wiki-type-of-website could help to upscale the guidelines at a global level. The guidelines could also be further refined accounting for different maturity levels of agri-food networks. The guidelines in this paper are considered to be a valuable step into the direction of solving governance issues in data sharing, which is expected to accelerate Big Data applications in the agri-food domain.
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The document discusses an effective implementation of data loss prevention (DLP) and data security. It covers key factors like the evolving threat landscape, business drivers for DLP, common challenges, and approaches to solve data security issues. An effective methodology is proposed, including identifying critical data and channels, deploying suitable policies, monitoring incidents, and establishing governance through continuous review and improvement. Critical success factors include business involvement, a phased implementation approach, and repeating the plan-do-check-act cycle periodically. The expected project outcomes are protection of critical channels, improved data tracking and awareness, and happier customers and auditors.
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This document summarizes a session discussing how to build the next privacy and security research agenda for big data. The session included an introduction, a discussion of the e-SIDES community position paper and process for providing input, a mentimeter voting activity, and a panel on ensuring responsible research and innovation responds to real needs. The panel featured representatives from universities and research organizations discussing issues like integrating privacy from the start, understanding cultural and regional differences, and ensuring research aligns with societal values and needs. The position paper and future research agenda aim to provide recommendations for an ethically sound approach to big data.
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This document outlines a roadmap for research in electronic governance over the next decade. It identifies four grand challenges: 1) Model-based collaborative governance to improve policy modeling and simulation; 2) Data-powered collective intelligence and action to leverage real-time open data; 3) Establishing a government service utility to provide ubiquitous, standardized public services; and 4) Developing a science base for ICT-enabled governance to systematize the field. For each challenge, it discusses short and long-term research directions to address gaps between current governance and a rapidly changing digital society. The overall goal is to transform policy-making using collaborative models, robust data analysis, and innovative digital service delivery.
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Big Data is becoming a new asset in the agri-food sector including enterprise data from operational systems, sensor data, farm equipment data, etc. Recently, Big Data applications are being implemented to improve farm and chain performance in agri-food networks. Still, many companies are refraining from sharing data because of fear of governance issues such as data insecurity, or lack of privacy or liability, among others. To overcome such barriers for developments with Big Data, this paper aims at: 1) analysing governance issues in agri-food networks, and 2) introducing a set of guidelines for data-sharing. Based on a literature review, a framework for analysing agri-food networks was developed, with internal governance factors (efficiency, effectiveness, inclusiveness, legitimacy & accountability, credibility and transparency) and external governance factors (political, economic, social, technological, legal and environmental factors). The framework contributes to development of a set of draft guidelines. Accordingly, for each factor, the guidelines address issues, best practices and lessons learned from other projects and initiatives. The approach developed in this paper creates a baseline for possible future developments of Big data in terms of 1) upscaling of the guidelines at a global level, 2) refining and fine-tuning of the guidelines for context specific agri-food networks, and 3) contributing to solving governance challenges in data sharing. In the future, the relevance of Big Data in the agri-food domain is expected to increase, and so are the contributions of this approach.
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This document summarizes 10 research papers related to privacy and security aspects of big data. It discusses the key challenges around big data privacy including how large amounts of consumer data collected by companies may be misused and how securely storing and analyzing this information is critical. Various papers propose mechanisms for encrypting data and complying with data privacy laws. Overall, the review finds that big data brings important security and privacy issues given its scale, and continued research is needed to develop solutions that balance data needs with individual privacy.
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The document discusses the "consumerisation of IT" where trends and technologies originating from consumer markets are increasingly being used in business settings. This is driven by factors like improved mobile devices, cloud services, and changing user expectations of consumer technologies in their personal and professional lives. While this poses risks to corporate IT like security and manageability issues, it also presents opportunities if IT can understand and adapt to these trends rather than fight them. The document provides examples of consumer technologies entering businesses and survey results on the extent companies are seeing this occur independently of IT strategy. It also outlines a balancing act for IT in addressing concerns while embracing opportunities and tips for policies, processes and skills to help manage the consumerisation of IT.
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This document summarizes a literature review on big data adoption that identified 42 significant factors and theoretical models used in previous studies. It outlines the paper's contributions in presenting the state of the art on models used for big data adoption and identifying adoption factors and challenges. The paper's methodology involved searching 8 databases using 5 keywords to find relevant papers published between 2015-2018. Key findings included that the most common models were TOE, DOI, TAM, and TTF frameworks, and that technology, organization, environment, and innovation-related factors influenced adoption. Challenges in current research were the theoretical models and factors studied, limited domains and populations, and need for more empirical studies.
Similar to e-SIDES presentation at WISP 2018, San Francisco 13/12/2018 (20)
Beyond Privacy: Learning Data Ethics - European Big Data Community Forum 2019...e-SIDES.eu
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"Towards Value-centric Big Data: Community Position Paper" Daniel Bachlechner...e-SIDES.eu
The document summarizes the work of the e-SIDES community towards developing a position paper on responsible and value-centric big data. It discusses the community's goals of identifying ethical issues, technologies, and opportunities related to big data. It also outlines the structure and purpose of the position paper in documenting challenges, stakeholders perspectives, and recommendations. Next steps include finalizing a draft of the paper by September and presenting it at a conference in November.
e-SIDES Community Position Paper User Manuale-SIDES.eu
e-SIDES is collecting community opinions related to the debate on how big data solutions can be developed and used in a responsible way, paying particular attention to the potential of privacy-preserving technologies.
By bringing together the viewpoints of stakeholders from different domains and with different expertise, we aim to complement our research and stimulate further dialogue around responsible big data innovation.
This presentation introduces the Community Position Paper, and provides detailed instruction about the collaborative editing process.
"Towards Value-Centric Big Data" e-SIDES Workshop - Slide-decke-SIDES.eu
This document summarizes a workshop session on value-centric big data. The session included presentations on several projects aiming to develop big data technologies and applications in an ethical manner that respects privacy and provides value. Speakers discussed challenges around privacy, profiling, and ensuring equitable and fair treatment when using big data. They also shared proposed solutions and best practices for addressing these challenges developed through their projects. The session concluded with an open discussion on experiences and approaches to overcoming barriers to responsible big data innovation.
"Towards Value-Centric Big Data" e-SIDES Workshop - "Privacy Preserving Techn...e-SIDES.eu
The following presentation was given by Tjerk Timan, Policy Ananlyst from TNO and BDVA, during the e-SIDES workshop "Towards Value-Centric Big Data" held on April 2, 2019 in Brussels.
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This document provides an overview of the AEGIS project, which aims to create a curated repository of public safety and personal security big data. It discusses the project objectives, including identifying and semantically linking diverse data sources and developing improved data handling and analysis tools. Three demonstrators are described that focus on automotive safety, smart homes, and smart insurance. The document outlines the project's commitment to ethics, including an Ethics Advisory Board and strategies to ensure privacy, data protection, and balance of interests. Requirements and frameworks for the technical platform emphasize privacy by design. Assessments of the system and demonstrators found them compliant with ethical and legal standards.
"Towards Value-Centric Big Data" e-SIDES Workshop - "The dangers of tech-dete...e-SIDES.eu
The following presentation was given by Barbara Giovanelli, Policy Officer, Digital Ethics at EPDS European Data Protection Supervisor, during the e-SIDES workshop "Towards Value-Centric Big Data" held on April 2, 2019 in Brussels.
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The following presentation was given by Prof. Ansar Yasar from the University of Hasselt during the e-SIDES workshop "Towards Value-Centric Big Data" held on April 2, 2019 in Brussels.
"Towards Value-Centric Big Data" e-SIDES Workshop - "Safe and secure data mar...e-SIDES.eu
The Safe-DEED project received Horizon 2020 funding to develop secure data marketplaces. The 36-month project involves 8 partners across Europe developing privacy-preserving technologies like secure multi-party computation. The project aims to address barriers to data sharing by enhancing trust and assessing data value to incentivize sharing. If successful, the project expects to see at least 30 companies using the software in new revenue streams within 3 years.
"Towards Value-Centric Big Data" e-SIDES Workshop - “You’re monitoring my wh...e-SIDES.eu
The following presentation was given by Duncan Brown, EMEA Chief Security Strategist at Forcepoint, during the e-SIDES workshop "Towards Value-Centric Big Data" held on April 2, 2019 in Brussels.
"Towards Value-Centric Big Data" e-SIDES Workshop - Slide-decke-SIDES.eu
This is the slide-deck of the workshop held on April 2, 2019 in Brussels, titled "Towards Value-Centric Big Data". It includes the presentations given by the speakers.
e-SIDES presentation at NordSteva Conference, 11/12/2018e-SIDES.eu
The following presentation was given by Karolina La Fors (e-Law Leiden University and e-SIDES ) at the NordSteva Conference held in Oslo on December 11, 2018.
e-SIDES workshop at EBDVF 2018, Vienna 14/11/2018 e-SIDES.eu
The following presentation was given at the workshop "From data protection and privacy to fairness and trust: the way forward" co-organized by e-SIDES at EBDVF 2018 in Vienna on November 14, 2018. The workshop, chaired by Jean-Cristophe Pazzaglia (SAP - BDVe) and Richard Stevens (IDC - e-SIDES), included a panel discussion with representatives from PAPAYA, SPECIAL and My Health My Data projects.
e-SIDES presentation at Leiden University 21/09/2017e-SIDES.eu
On September 21st the eLaw team member of e-SIDES, Magdalena Jozwiak, made a presentation of the e-SIDES project at a lunch event at the Leiden University’s Law Faculty. The event, organized within the Interaction Between Legal Systems research theme, attracted an interdisciplinary audience and was followed by a discussion on e-SIDES, its goals and approaches.
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
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.
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.