The document discusses open science in Africa and the need for coordination and capacity building. It proposes the creation of an African Open Science Platform to promote open data policies, training, and infrastructure development across the continent. The platform would help African countries develop their ability to manage and utilize scientific data for societal benefit. Several existing collaborative initiatives and networks are mentioned that could help align and strengthen open science efforts in Africa on both a regional and global scale.
This document discusses the ethics of increasing automation and the evolving knowledge infrastructure. It notes challenges around trusting automated analysis with no human in the loop, and understanding complex and evolving data sources. Breakout groups are proposed to discuss interventions for improving research quality, issues around reproducibility with different data types, and the impact of large online data on reproducibility in social sciences. The document references challenges around safety vs security, and tradeoffs between hardening systems and adaptive response.
This document discusses big data, social machines, and the evolving knowledge infrastructure. It notes that big data does not respect disciplinary boundaries and enables new types of research. Social machines are described as processes where people do creative work and machines do administration, allowing new forms of social processes to be created. The challenges are to foster socio-technical systems that enable sense-making using expertise, data, models, and narratives. Overall, there are shifts occurring with large data volumes, new computational infrastructure, a move from datasets to dataflows, and the need for responsible innovation.
Canada is a data and technological society. There is no sector that is uninformed by data or unmediated by code, algorithms, software and infrastructure. Consider the Internet of Things (IoT), smart cities, and precision agriculture; or smart fisheries, forestry, and energy and of course governing. In a data based and technological society, leadership is the responsibility of all citizens, a parent, teacher, scholar, administrator, public servant, nurse and doctor, mayor and councillor, fisher, builder, business person, industrialist, MP, MLA, PM, and so on. In other words leadership is distributed and requires people power. This form of citizenship, according to Andrew Feenberg, Canada Research Chair in Philosophy of Technology, requires agency, knowledge and the capacity to act or power. In this GovMaker Keynote I will introduce the concept of technological citizenship, I will discuss what principled public interest governing might look like, and how we might go about critically applying philosophy in our daily practice. In terms of practice I will discuss innovative policy and regulation such as the right to repair movement, EU legislation such as the right to explanation, data subjects and the right to access and also data sovereignty from a globalization and an indigenous perspective.
"'Tis true. There's magic in the Web: The Short and the Long of Co-Creation, Web Science, and Data Driven Innovation". Keynote for the DATA-DRIVEN INNOVATION WORKSHOP 2016 collocated with ACM Web Science 2016, Hannover, Germany, Sunday 22 May 2016
Experiences as a producer, consumer and observer of open dataProgCity
Peter Mooney, is an Environmental Protection Agency (EPA) funded Research Fellow at the Department of Computer Science, NUI Maynooth. He has been working with the EPA on making environmental data publicly accessibly for the last ten years.
Presentation was part of The 1st Seminar of the ERC Funded Programmable City Project based at NIRSA, NUI Maynooth, Republic of Ireland.
This document summarizes a conference presentation on using crowdsourcing approaches like volunteered geographic information (VGI), citizen science (CS), and participatory mapping (PM) to engage the public in policymaking. It defines these approaches and provides examples. While governments have been reluctant to use crowdsourced data due to quality and legal concerns, the presenters argue that capitalizing on established crowdsourcing models and open data practices could help develop public policies to formally incorporate crowdsourcing into government decision-making and engagement. Recommendations are provided for overcoming barriers and assuaging government adoption of these approaches.
The document discusses open science in Africa and the need for coordination and capacity building. It proposes the creation of an African Open Science Platform to promote open data policies, training, and infrastructure development across the continent. The platform would help African countries develop their ability to manage and utilize scientific data for societal benefit. Several existing collaborative initiatives and networks are mentioned that could help align and strengthen open science efforts in Africa on both a regional and global scale.
This document discusses the ethics of increasing automation and the evolving knowledge infrastructure. It notes challenges around trusting automated analysis with no human in the loop, and understanding complex and evolving data sources. Breakout groups are proposed to discuss interventions for improving research quality, issues around reproducibility with different data types, and the impact of large online data on reproducibility in social sciences. The document references challenges around safety vs security, and tradeoffs between hardening systems and adaptive response.
This document discusses big data, social machines, and the evolving knowledge infrastructure. It notes that big data does not respect disciplinary boundaries and enables new types of research. Social machines are described as processes where people do creative work and machines do administration, allowing new forms of social processes to be created. The challenges are to foster socio-technical systems that enable sense-making using expertise, data, models, and narratives. Overall, there are shifts occurring with large data volumes, new computational infrastructure, a move from datasets to dataflows, and the need for responsible innovation.
Canada is a data and technological society. There is no sector that is uninformed by data or unmediated by code, algorithms, software and infrastructure. Consider the Internet of Things (IoT), smart cities, and precision agriculture; or smart fisheries, forestry, and energy and of course governing. In a data based and technological society, leadership is the responsibility of all citizens, a parent, teacher, scholar, administrator, public servant, nurse and doctor, mayor and councillor, fisher, builder, business person, industrialist, MP, MLA, PM, and so on. In other words leadership is distributed and requires people power. This form of citizenship, according to Andrew Feenberg, Canada Research Chair in Philosophy of Technology, requires agency, knowledge and the capacity to act or power. In this GovMaker Keynote I will introduce the concept of technological citizenship, I will discuss what principled public interest governing might look like, and how we might go about critically applying philosophy in our daily practice. In terms of practice I will discuss innovative policy and regulation such as the right to repair movement, EU legislation such as the right to explanation, data subjects and the right to access and also data sovereignty from a globalization and an indigenous perspective.
"'Tis true. There's magic in the Web: The Short and the Long of Co-Creation, Web Science, and Data Driven Innovation". Keynote for the DATA-DRIVEN INNOVATION WORKSHOP 2016 collocated with ACM Web Science 2016, Hannover, Germany, Sunday 22 May 2016
Experiences as a producer, consumer and observer of open dataProgCity
Peter Mooney, is an Environmental Protection Agency (EPA) funded Research Fellow at the Department of Computer Science, NUI Maynooth. He has been working with the EPA on making environmental data publicly accessibly for the last ten years.
Presentation was part of The 1st Seminar of the ERC Funded Programmable City Project based at NIRSA, NUI Maynooth, Republic of Ireland.
This document summarizes a conference presentation on using crowdsourcing approaches like volunteered geographic information (VGI), citizen science (CS), and participatory mapping (PM) to engage the public in policymaking. It defines these approaches and provides examples. While governments have been reluctant to use crowdsourced data due to quality and legal concerns, the presenters argue that capitalizing on established crowdsourcing models and open data practices could help develop public policies to formally incorporate crowdsourcing into government decision-making and engagement. Recommendations are provided for overcoming barriers and assuaging government adoption of these approaches.
In scientific communication, we observe a complex interaction of several stakeholder groups, each of which have distinct interests, strategies and approaches for Open Access and Open Data. The German government initiated a “Commission for the Future of the Information Infrastructure” (KII) in Germany. In this commission, most of the stakeholders are working together in order to design a future scenario for the supply of scientific information. The KII’s evaluation and recommendations for Open Access as well as research data will be particularly highly recognized and will significantly influence Open Access and Open Data developments in Germany.
I will outline the current situation in Germany – players and their interactions in terms of Open Access and Open Data – and present two initiatives and their work in detail. One of them, the KII process, will show the official site, the other one will show the grassroots site of the story.
CeRDI Research RUN Vietnam Agriculture GroupHelen Thompson
Federation University's Centre for eResearch and Digital Innovation (CeRDI) is participating in the Regional University Network (RUN) Vietnam Agriculture Group. This presentation provides some background on CeRDI initiatives in eResearch.
Areas of focus include capacity building and engagement, research collaborations around soil management, water resources, land use, crop productivity, climate change and adaption, biodiversity, participatory GIS and citizen science.
Major technology and research trends link to ubiquitous high-speed broadband, the petabyte age, open data policies and the opportunities for Universities and particularly regional universities to play a significant role in generating insight from data.
Mobile technologies… App development and responsive design – for student and staff recruitment, engagement, knowledge transfer
3d and visualisation technologies… Massive innovation and research opportunities
Opening talk at the "Interdisciplinary Data Resources to Address the Challenges of Urban Living” Workshop at the Urban Big Data Centre, University of Glasgow, 4 April 2016
Social Science Landscape for Web ObservatoriesDavid De Roure
1. The document discusses big data for social science research and the role of web observatories.
2. It notes that big data does not respect disciplinary boundaries and enables new types of research questions using real-time social media data at large scales.
3. Web observatories aim to facilitate interdisciplinary social research using computational analysis of online data through infrastructure for data access, curation, analysis and sharing of results.
The document discusses open data and open access in Tanzania. It provides an overview of open data concepts, initiatives in Tanzania including the government open data portal and projects by the Tanzania dLab at the University of Dar es Salaam to enhance the data ecosystem. Some of the challenges to open data mentioned include lack of standards. The document also outlines achievements in open access in Tanzania through initiatives by EIFL and COTUL to establish institutional repositories and draft open access policies and build capacity at universities.
Digital humanities involves the intersection of digital technologies and humanities research. It can include building digital collections and tools for authoring, analyzing, and managing research. Digital humanities centers typically offer resources like databases, tools for analysis, and training. They serve as hubs for innovation and experimentation in applying new technologies to answer humanities questions. Debates include whether digital humanities should apply technologies or critically examine their impact, and whether databases can support narrative scholarship. Visualizations are increasingly important in digital humanities for exploring subjects like ancient cities in new ways.
OKCon 2008 - Lessons from Environmental informationMuki Haklay
The presentation covers several areas of open information and access to environmental information, starting with a short overview of the background, followed by some examples of environmental information over the internet from the past 14 years, then a few examples of recent development, and a discussion of the work that we’ve been carrying out at UCL recently. Finally, there are observations on access to information in the environmental field .
The document discusses open data initiatives and tools for data sharing. It describes projects from the EDINA National Data Centre, DISC-UK DataShare project which investigated legal and technical issues around research data sharing, and tools for visualizing and sharing numeric and spatial data online like Many Eyes, Gapminder and OpenStreetMap. It also covers barriers to data sharing, harnessing collective intelligence through open science, and citizens contributing geographic data through tools like geograph.
The document discusses citizen science and its potential synergies with Earth observation (EO) data. It describes OpenStreetMap as an example of citizen science, noting its open data license and global community of contributors. The document advocates cross-fertilization between citizen science and EO to better leverage billions of intelligent sensors. It also discusses recent EO developments like the Digital Earth concept, geospatial web, big data platforms, and the potential of artificial intelligence to harness these new capabilities for studying the Earth.
Putting Data to Work: Moving science forward together beyond where we thought...Erin Robinson
This document discusses how putting data to work through community. It outlines the traditional approach of individual science projects versus a community approach. The traditional approach involves scientists independently finding, accessing, analyzing and publishing data. The community approach advocates opening this process up through shared infrastructure and standards to allow more collaborative data reuse. It provides examples of communities like the air quality community that have worked to develop interoperable standards and services. Overall, it argues that a community approach where data and standards are shared can lead to more open science and greater data reuse.
Seminar at CSAIL, MIT, Cambridge, Mass. Date: Friday October 30, 2015. Time: 4:00 pm - 5:00 pm, Location: D463 (Star)
Abstract:
Today we are witnessing several shifts in scholarly practice, in and across multiple disciplines, as researchers embrace digital techniques to tackle established research questions in new ways and new questions afforded by digital and digitized collections, approaches, and technologies. Pervasive adoption of technology, coupled with the co-creation of new social processes, has created a new and complex space for scholarship where citizens both generate and analyse data as they interact at the intersection of the physical and digital. Drawing on a background in distributed computing, and adopting the lens of Social Machines, this talk discusses current activity in digital scholarship, framing it in its interdisciplinary settings.
Bio:
David De Roure is Professor of e-Research at University of Oxford, Director of the Oxford e-Research Centre, and chairs Oxford’s Digital Humanities research programme. He previously directed the Digital Social Research programme for the UK Economic and Social Research Council, and serves as a strategic advisor in new forms of data and realtime analytics. Trained in electronics and computer science, his career has involved interdisciplinary collaborations in chemistry, astrophysics, bioinformatics, social computing, digital libraries, and sensor networks. His personal research is in Computational Musicology, Web Science, and Internet of Things. He is a frequent speaker and writer on digital research and the future of scholarly communications. URL: http://www.oerc.ox.ac.uk/people/dder
The document discusses open data and its potential to create economic, environmental, and social value by allowing people to generate insights and ideas. It defines open data as data that anyone is free to use, reuse, and redistribute, with some attribution requirements. The Open Data Institute is presented as catalyzing the evolution of open data culture to realize this potential, with a team that includes experts in open data, linked data, government transparency, and commercial technology.
This document discusses the opportunities and challenges presented by big data for social sciences research. New forms of data from social media, tracking, and internet-connected devices allow researchers to study social processes as they unfold in real-time at large scales. However, analyzing this data requires new computational skills and infrastructure. Researchers must also consider new methods and address issues like reproducibility, ethics, and access to ensure quality results. Overall, big data has the potential to transform social sciences by enabling the study of phenomena in new ways, but significant challenges around data, skills, and research practices must be overcome.
Keynote talk given during the 9th Conf. on Artificial Intelligence in Security and Defence, AISD2019, Beirut, 26th-29th March,
2019
----
Open data in disaster management
The UN General Assembly defined in February 2017 a disaster as “A serious disruption of the functioning of a community or a society at any scale due to hazardous events interacting with conditions of exposure, vulnerability and capacity, leading to one or more of the following human, material, economic and environmental losses and impacts. It is deeply intertwined with the broader concept of risks, defined by the European commission as a “combination of the probability of occurrence of a hazard generating harm in a given scenario and the severity of that harm.”
Managing these uncertainties requires a large spectrum of data coming from different sources, government being one of the most important. Open Government Data (OGD) is a philosophy and a set of policies that promotes transparency, accountability and value creation by making government data available to all. According to the OGD 8 principles, defined in 2007, Sebastopol, California, these data should be: complete, primary, timely, accessible, machine processable, non-discriminatory, non-proprietary, license-free.
One goal of Open Government Data is to rise the interest of third-parties stakeholders and their (open) innovation capabilities, Open Data is providing trusted information which is important in a troubled context, with a lot of rumors (see also the emergence of fake news). As governments are among the largest data creators and providers, OGD is a central issue for disaster management or risk mitigation, for example through the provision of costly and/or rare data, like data related to infrastructures, weather data or satellite imagery. By definition, OGD is contributing to remove the data silos created by the different information systems of different bodies of government, administration or external stakeholders, allowing a cross-boundary information sharing. It is also a tool to improve cooperation among stakeholders in case of emergency. All of this is of paramount importance regarding disaster management.
Through a set of use cases, this talk will highlight (1) how OGD has been or could be used during the whole of the disaster management cycle, from prevention and preparedness, emergency management, response, and recovery; (2) its current or potential benefits and possible improvements through its linkage with other sources of information, structured and unstructured, such social media and crowdsourcing ; and (3) its identified barriers regarding data availability and quality, organizational readiness, multi-stakeholders involvement, and cooperation.
Supercomputer Earth: The Future of Civilization (& Africa\'s part in it)Christian Heller
The document discusses the evolution of technology and intelligence over the past 500,000 years, from early language to modern computing networks and the world wide web. It describes how Web 2.0 has enabled greater participation and new ways of sharing information. The growth of global supercomputing power through more connected human intelligence and improvements in artificial systems is also covered. Africa's opportunity to "leapfrog" older technologies and directly adopt newer, decentralized approaches is presented as a way for the continent to play a role in and benefit from this continued technological progress.
This paper describes the principles, methods and strategies for the design of everyday objects that embody data – or Data Objects. The work presented in the paper connects the fields of industrial design and data physicalisation to introduce the concept of using data as a design material. To support the
creative synthesis of Data Objects the paper provides a literature review, methods and guidance on the creation of Data Objects alongside examples - and possible opportunities, challenges, and future scenarios - for the practice, use and the study of Data Objects.
Keywords: Big Data; Design Principles; Design Methods; Speculative Design; Design Activism.
New forms of data for the social sciences: Smarter cities, more efficient organisations, and healthier communities. Wednesday 3rd November 2015, UCL, London, United Kingdom
Big Data for the Social Sciences - David De Roure - Jisc Digital Festival 2014Jisc
The analysis of government data, data held by business, the web, social science survey data will support new research directions and findings. Big Data is one of David Willetts’ 8 great technologies, and in order to secure the UK’s competitive advantage new investments have been made by the Economic Social Science Research Council ( ESRC) in Big Data, for example the Business Datasafe and Understanding Populations investments. In this session the benefits of the use of Big Data in social science , and the ESRCs Big Data strategy will be explained by Professor David De Roure.of the Oxford e-Research Centre and advisor to the ESRC.
Keynote talk at the Web Science Summer School, Singapore, 8 December 2014. Today we see the rise of Social Machines, like Twitter, Wikipedia and Galaxy Zoo—where communities identify and solve their own problems, harnessing commitment, local knowledge and embedded skills, without having to rely on experts or governments.
The Social Machines paradigm provides a lens onto the interacting sociotechnical systems of our hybrid digital-physical world, citizen-centric and at scale—emphasising empowerment and sociality in a world of pervasive technology adoption and automation.
This talk will present the Social Machines paradigm as an approach to social media analytics and a rethinking of our scholarly practices and knowledge infrastructure.
In scientific communication, we observe a complex interaction of several stakeholder groups, each of which have distinct interests, strategies and approaches for Open Access and Open Data. The German government initiated a “Commission for the Future of the Information Infrastructure” (KII) in Germany. In this commission, most of the stakeholders are working together in order to design a future scenario for the supply of scientific information. The KII’s evaluation and recommendations for Open Access as well as research data will be particularly highly recognized and will significantly influence Open Access and Open Data developments in Germany.
I will outline the current situation in Germany – players and their interactions in terms of Open Access and Open Data – and present two initiatives and their work in detail. One of them, the KII process, will show the official site, the other one will show the grassroots site of the story.
CeRDI Research RUN Vietnam Agriculture GroupHelen Thompson
Federation University's Centre for eResearch and Digital Innovation (CeRDI) is participating in the Regional University Network (RUN) Vietnam Agriculture Group. This presentation provides some background on CeRDI initiatives in eResearch.
Areas of focus include capacity building and engagement, research collaborations around soil management, water resources, land use, crop productivity, climate change and adaption, biodiversity, participatory GIS and citizen science.
Major technology and research trends link to ubiquitous high-speed broadband, the petabyte age, open data policies and the opportunities for Universities and particularly regional universities to play a significant role in generating insight from data.
Mobile technologies… App development and responsive design – for student and staff recruitment, engagement, knowledge transfer
3d and visualisation technologies… Massive innovation and research opportunities
Opening talk at the "Interdisciplinary Data Resources to Address the Challenges of Urban Living” Workshop at the Urban Big Data Centre, University of Glasgow, 4 April 2016
Social Science Landscape for Web ObservatoriesDavid De Roure
1. The document discusses big data for social science research and the role of web observatories.
2. It notes that big data does not respect disciplinary boundaries and enables new types of research questions using real-time social media data at large scales.
3. Web observatories aim to facilitate interdisciplinary social research using computational analysis of online data through infrastructure for data access, curation, analysis and sharing of results.
The document discusses open data and open access in Tanzania. It provides an overview of open data concepts, initiatives in Tanzania including the government open data portal and projects by the Tanzania dLab at the University of Dar es Salaam to enhance the data ecosystem. Some of the challenges to open data mentioned include lack of standards. The document also outlines achievements in open access in Tanzania through initiatives by EIFL and COTUL to establish institutional repositories and draft open access policies and build capacity at universities.
Digital humanities involves the intersection of digital technologies and humanities research. It can include building digital collections and tools for authoring, analyzing, and managing research. Digital humanities centers typically offer resources like databases, tools for analysis, and training. They serve as hubs for innovation and experimentation in applying new technologies to answer humanities questions. Debates include whether digital humanities should apply technologies or critically examine their impact, and whether databases can support narrative scholarship. Visualizations are increasingly important in digital humanities for exploring subjects like ancient cities in new ways.
OKCon 2008 - Lessons from Environmental informationMuki Haklay
The presentation covers several areas of open information and access to environmental information, starting with a short overview of the background, followed by some examples of environmental information over the internet from the past 14 years, then a few examples of recent development, and a discussion of the work that we’ve been carrying out at UCL recently. Finally, there are observations on access to information in the environmental field .
The document discusses open data initiatives and tools for data sharing. It describes projects from the EDINA National Data Centre, DISC-UK DataShare project which investigated legal and technical issues around research data sharing, and tools for visualizing and sharing numeric and spatial data online like Many Eyes, Gapminder and OpenStreetMap. It also covers barriers to data sharing, harnessing collective intelligence through open science, and citizens contributing geographic data through tools like geograph.
The document discusses citizen science and its potential synergies with Earth observation (EO) data. It describes OpenStreetMap as an example of citizen science, noting its open data license and global community of contributors. The document advocates cross-fertilization between citizen science and EO to better leverage billions of intelligent sensors. It also discusses recent EO developments like the Digital Earth concept, geospatial web, big data platforms, and the potential of artificial intelligence to harness these new capabilities for studying the Earth.
Putting Data to Work: Moving science forward together beyond where we thought...Erin Robinson
This document discusses how putting data to work through community. It outlines the traditional approach of individual science projects versus a community approach. The traditional approach involves scientists independently finding, accessing, analyzing and publishing data. The community approach advocates opening this process up through shared infrastructure and standards to allow more collaborative data reuse. It provides examples of communities like the air quality community that have worked to develop interoperable standards and services. Overall, it argues that a community approach where data and standards are shared can lead to more open science and greater data reuse.
Seminar at CSAIL, MIT, Cambridge, Mass. Date: Friday October 30, 2015. Time: 4:00 pm - 5:00 pm, Location: D463 (Star)
Abstract:
Today we are witnessing several shifts in scholarly practice, in and across multiple disciplines, as researchers embrace digital techniques to tackle established research questions in new ways and new questions afforded by digital and digitized collections, approaches, and technologies. Pervasive adoption of technology, coupled with the co-creation of new social processes, has created a new and complex space for scholarship where citizens both generate and analyse data as they interact at the intersection of the physical and digital. Drawing on a background in distributed computing, and adopting the lens of Social Machines, this talk discusses current activity in digital scholarship, framing it in its interdisciplinary settings.
Bio:
David De Roure is Professor of e-Research at University of Oxford, Director of the Oxford e-Research Centre, and chairs Oxford’s Digital Humanities research programme. He previously directed the Digital Social Research programme for the UK Economic and Social Research Council, and serves as a strategic advisor in new forms of data and realtime analytics. Trained in electronics and computer science, his career has involved interdisciplinary collaborations in chemistry, astrophysics, bioinformatics, social computing, digital libraries, and sensor networks. His personal research is in Computational Musicology, Web Science, and Internet of Things. He is a frequent speaker and writer on digital research and the future of scholarly communications. URL: http://www.oerc.ox.ac.uk/people/dder
The document discusses open data and its potential to create economic, environmental, and social value by allowing people to generate insights and ideas. It defines open data as data that anyone is free to use, reuse, and redistribute, with some attribution requirements. The Open Data Institute is presented as catalyzing the evolution of open data culture to realize this potential, with a team that includes experts in open data, linked data, government transparency, and commercial technology.
This document discusses the opportunities and challenges presented by big data for social sciences research. New forms of data from social media, tracking, and internet-connected devices allow researchers to study social processes as they unfold in real-time at large scales. However, analyzing this data requires new computational skills and infrastructure. Researchers must also consider new methods and address issues like reproducibility, ethics, and access to ensure quality results. Overall, big data has the potential to transform social sciences by enabling the study of phenomena in new ways, but significant challenges around data, skills, and research practices must be overcome.
Keynote talk given during the 9th Conf. on Artificial Intelligence in Security and Defence, AISD2019, Beirut, 26th-29th March,
2019
----
Open data in disaster management
The UN General Assembly defined in February 2017 a disaster as “A serious disruption of the functioning of a community or a society at any scale due to hazardous events interacting with conditions of exposure, vulnerability and capacity, leading to one or more of the following human, material, economic and environmental losses and impacts. It is deeply intertwined with the broader concept of risks, defined by the European commission as a “combination of the probability of occurrence of a hazard generating harm in a given scenario and the severity of that harm.”
Managing these uncertainties requires a large spectrum of data coming from different sources, government being one of the most important. Open Government Data (OGD) is a philosophy and a set of policies that promotes transparency, accountability and value creation by making government data available to all. According to the OGD 8 principles, defined in 2007, Sebastopol, California, these data should be: complete, primary, timely, accessible, machine processable, non-discriminatory, non-proprietary, license-free.
One goal of Open Government Data is to rise the interest of third-parties stakeholders and their (open) innovation capabilities, Open Data is providing trusted information which is important in a troubled context, with a lot of rumors (see also the emergence of fake news). As governments are among the largest data creators and providers, OGD is a central issue for disaster management or risk mitigation, for example through the provision of costly and/or rare data, like data related to infrastructures, weather data or satellite imagery. By definition, OGD is contributing to remove the data silos created by the different information systems of different bodies of government, administration or external stakeholders, allowing a cross-boundary information sharing. It is also a tool to improve cooperation among stakeholders in case of emergency. All of this is of paramount importance regarding disaster management.
Through a set of use cases, this talk will highlight (1) how OGD has been or could be used during the whole of the disaster management cycle, from prevention and preparedness, emergency management, response, and recovery; (2) its current or potential benefits and possible improvements through its linkage with other sources of information, structured and unstructured, such social media and crowdsourcing ; and (3) its identified barriers regarding data availability and quality, organizational readiness, multi-stakeholders involvement, and cooperation.
Supercomputer Earth: The Future of Civilization (& Africa\'s part in it)Christian Heller
The document discusses the evolution of technology and intelligence over the past 500,000 years, from early language to modern computing networks and the world wide web. It describes how Web 2.0 has enabled greater participation and new ways of sharing information. The growth of global supercomputing power through more connected human intelligence and improvements in artificial systems is also covered. Africa's opportunity to "leapfrog" older technologies and directly adopt newer, decentralized approaches is presented as a way for the continent to play a role in and benefit from this continued technological progress.
This paper describes the principles, methods and strategies for the design of everyday objects that embody data – or Data Objects. The work presented in the paper connects the fields of industrial design and data physicalisation to introduce the concept of using data as a design material. To support the
creative synthesis of Data Objects the paper provides a literature review, methods and guidance on the creation of Data Objects alongside examples - and possible opportunities, challenges, and future scenarios - for the practice, use and the study of Data Objects.
Keywords: Big Data; Design Principles; Design Methods; Speculative Design; Design Activism.
New forms of data for the social sciences: Smarter cities, more efficient organisations, and healthier communities. Wednesday 3rd November 2015, UCL, London, United Kingdom
Big Data for the Social Sciences - David De Roure - Jisc Digital Festival 2014Jisc
The analysis of government data, data held by business, the web, social science survey data will support new research directions and findings. Big Data is one of David Willetts’ 8 great technologies, and in order to secure the UK’s competitive advantage new investments have been made by the Economic Social Science Research Council ( ESRC) in Big Data, for example the Business Datasafe and Understanding Populations investments. In this session the benefits of the use of Big Data in social science , and the ESRCs Big Data strategy will be explained by Professor David De Roure.of the Oxford e-Research Centre and advisor to the ESRC.
Keynote talk at the Web Science Summer School, Singapore, 8 December 2014. Today we see the rise of Social Machines, like Twitter, Wikipedia and Galaxy Zoo—where communities identify and solve their own problems, harnessing commitment, local knowledge and embedded skills, without having to rely on experts or governments.
The Social Machines paradigm provides a lens onto the interacting sociotechnical systems of our hybrid digital-physical world, citizen-centric and at scale—emphasising empowerment and sociality in a world of pervasive technology adoption and automation.
This talk will present the Social Machines paradigm as an approach to social media analytics and a rethinking of our scholarly practices and knowledge infrastructure.
for getting the library resources fro the libraries entire world, the important tool is Library catalogues. every can browse all most all the world literature through WorldCat fro the INTERNET.
1) The document discusses social machines, which are computational systems involving both human and machine participants working together. Examples mentioned include Wikipedia and citizen science projects.
2) Key aspects of social machines are discussed, including their collaborative and open nature, use of stories and narratives, and focus on empowering human participants.
3) Sustainability of social machines over time is an important challenge, as maintaining volunteer participation can be difficult, as seen with the declining contributor numbers on Wikipedia. Designing social machines to be reactive and allow for improvisation may help with long-term sustainability.
From Open Data to Open Science, by Geoffrey BoultonLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Geoffrey Boulton, University of Edinburgh & CODATA
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
Scholarship in a connected world: New ways to know, new ways to showDerek Keats
The document discusses how libraries and scholarship are changing in a digital world of abundance rather than scarcity. It covers four key areas: ubiquitous computing, the social academic, research data, and free and open versus secret science. The author argues that libraries must adapt to this new environment by embracing new technologies, facilitating social and open sharing of knowledge, helping with research data management, and promoting open access over secret science.
Big data provides opportunities for social science research by enabling new ways to answer existing questions and allowing entirely new questions to be asked. Large and diverse datasets can be analyzed from various sources like social media, sensors, and citizen science. This allows researchers to study big populations and questions in real time. Challenges include interdisciplinary collaboration, ensuring data and tools are open and reusable, and developing infrastructure to support analysis of large and diverse datasets.
e-infrastructures supporting open knowledge circulation - OpenAIRE FranceJean-François Lutz
This document discusses e-infrastructures that support open access to scientific knowledge and data. It notes that science is becoming more collaborative globally and data-driven. E-infrastructures provide crucial enabling technologies for open data sharing, scientific workflows, and virtual collaborations. Future steps include further promoting open access policies and ensuring the long-term preservation and reuse of publicly-funded research outputs and data.
Big data and the dark arts - Jisc Digital Media 2015Jisc
There still remains a certain misunderstanding by the very definition of "big data" and the perceived hype around the term. This workshop clarified the concepts and give examples of relevant big data projects.
This document discusses the potential for developing a knowledge network by leveraging metadata from scientific endeavors. It begins by outlining some of the limitations of traditional metadata approaches. It then proposes that metadata could be structured as a graph using semantic triples to represent relationships between people, institutions, projects, and other elements. This liberalized metadata approach could help reduce complexity while providing a more comprehensive view of scientific activities and outputs. The document advocates for establishing common standards, developing tools to extract and aggregate metadata, and creating services and repositories to enable discovery, analysis, and visualization of the knowledge network. The goal is to facilitate research by providing integrated access to information on scientific data, publications, actors and their relationships.
Understanding the Big Picture of e-ScienceAndrew Sallans
E-science involves large-scale collaborative research enabled by new technologies like high-speed networks and cheap data storage. It produces massive amounts of complex data from areas like climate modeling, particle physics experiments, biomedical research grids, and citizen science projects. This represents a major change for research that requires new infrastructure, expertise, and approaches. Universities like UVA are responding by establishing research computing support services in their libraries to help scientists with the computational and data aspects of e-science throughout the research lifecycle.
Find out how to partner with us for the RDA 6th Plenary in Paris, 23- 25 September 2015! Join us for an international event gathering industry and academic experts, world leaders involved in the data ecosystem !
Codes, Clouds & Constellations: Open Science in the Data DecadeLizLyon
This document summarizes a presentation by Liz Lyon about open science challenges and opportunities in the data decade. It discusses issues around data sharing, attribution, and participation from individual researchers to large institutions. New technologies enable large-scale data sharing through cloud computing but also raise issues around privacy, standards, and crediting contributions. Institutions are developing strategies to support open science through new data management structures, cross-campus collaborations, and integrating data skills into education.
Media, information and the promise of new technologies in Knowledge Transfer ...maudelfin
This document discusses knowledge transfer practices and the role of new technologies. It covers different knowledge systems like communities of practice and academia. It also examines knowledge transfer spaces like workshops and digital repositories. Finally, it discusses key message formats, open data, and licensing regimes like Creative Commons that enable open sharing of information.
This document discusses managing research data for open science based on the UK experience. It outlines key aspects of open science such as making research more open, global, collaborative and closer to society. The document discusses mandates for open research data from funding bodies in the UK and EU, including stipulations in Horizon 2020 and requirements from EPSRC. It defines what constitutes research data and examines challenges around research data management, including technology issues, people issues, policy issues and resources. The importance of data skills training for researchers and data professionals is also covered.
The wider environment of open scholarship – Jisc and CNI conference 10 July ...Jisc
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Why we care about research data? Why we share?Richard Ferrers
An introduction to why ANDS cares about research data. ANDS, the Australian National Data Service, encourages researchers to share data. This presentation explains why.
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Removing Barriers to Data Sharing: the Research Data Alliance
1. Removing Barriers to Data Sharing:
the Research Data Alliance
Amy L. Nurnberger
0000-0002-5931-072X
RDA Organiza=onal Advisory Board, Co-chair
Columbia University, Research Data Manager
@DataAtCU
Internet2 – 2016 TechEx
Miami, FL
28 September 2016
WWW.RD-ALLIANCE.ORG
@RESDATALL
This work is licensed under a Crea=ve Commons AOribu=on 4.0 Interna=onal License.
4. World-wide Efforts Focusing on Infrastructure to
Support Research Data Sharing, Access, Use
Science, Humanities, Arts
Communities
E-Infrastructure professionals,
data analysts, data center staff, …
Data
Scientists
Libraries, Archives,
Repositories, Museums
WWW.RD-ALLIANCE.ORG
@RESDATALL
5. Institutional Data
Sharing Practice
Data Access and Distribution
Policy
Data
Discovery Tools
Common
Metadata Standards
Digital Object
Identifiers
Data Citation
Standards
Data
Analytics Algorithms
Data
Preservation Practice
Data Scientists and
Expert Support
Sustainable
Economic Models
Curation Practice and
Policy
Auditing, Certification and
Reporting Practice
Many Infrastructure Building Blocks
Needed to Accelerate Progress
Data Use and
Re-use
Data Discovery and
Data Sharing
Research Dissemination and
Reproducibility
Data Access (now) and
Preservation (later)
WWW.RD-ALLIANCE.ORG
@RESDATALL
8. … So much to gain from collaboration …
Why a Research Data
Alliance?
WWW.RD-ALLIANCE.ORG
@RESDATALL
9. “We are taking our work beyond Europe's borders, to reach
global scale. To make the scientific resources of the world work
together, interoperating and open to discovery. For example we
are working with partners like the US and Australia in the
Research Data Alliance to make scientific progress broader,
deeper and more workable”.
Neelie Kroes, Vice-President of the European Commission responsible
for the Digital Agenda - Open Access to science and data = cash and
economic bonanza, 19 November 2013
… So much to gain from collaboration …
Why a Research Data
Alliance?
WWW.RD-ALLIANCE.ORG
@RESDATALL
10. Researchers and innovators openly share data across
technologies, disciplines, and countries to address the grand
challenges of society.
What RDA is about:
WWW.RD-ALLIANCE.ORG
@RESDATALL
11. Researchers and innovators openly share data across
technologies, disciplines, and countries to address the grand
challenges of society.
… building the social and technical bridges that enable global open sharing of data…
Researchers, scien>sts, data prac>>oners & informa>on technologists
from around the world are invited to work together to achieve the vision
What RDA is about:
WWW.RD-ALLIANCE.ORG
@RESDATALL
12. Reality bikes: “There is no reason to think that
collaborators have common goals”
Bicycle slide
Used courtesy Mark Parsons
WWW.RD-ALLIANCE.ORG
@RESDATALL
14. Dynamics of infrastructure
Edwards et al. 2007. Understanding infrastructure dynamics, tensions and
design
Infrastructures become “ubiquitous, accessible, reliable, and
transparent” as they mature
Systems → Networks → Inter-networks
◦ “system-building, characterized by the deliberate and successful
design of technology-based services”
◦ “technology transfer across domains and loca=ons results in
varia=ons on the original design, as well as the emergence of
compe=ng systems.”
◦ Finally, a “process of consolidaFon characterized by gateways that
allows dissimilar systems to be liked into networks”
Used courtesy Mark Parsons
WWW.RD-ALLIANCE.ORG
@RESDATALL
21. Call for Adop[on of RDA
Outputs
If you are interested in
adop0ng one of these
outputs, please contact
enquiries@rd-alliance.org
or visit
h;ps://rd-alliance.org/
recommenda0ons-and-
outcomes/become-rda-
adopter
WWW.RD-ALLIANCE.ORG
@RESDATALL
22. Africa
3% Asia
9%
Australasia
5%
Europe
48%
North America
34%
South America
1%
Total RDA Community Members: 4345
from 111 countries
Who is RDA?
Type
Members
(Sept. 2016)
Press & Media 27
Policy/Funding Agency 64
Large Enterprise 99
IT Consultancy/Development 143
Small and Medium Enterprise 249
Other 235
Government/Public Services 671
Academia/Research 2857
TOTAL 4345
www.rd-alliance.org/about-rda
392
989
1272
1654
2046
2402
2634
2877 3122 3431
3694
4016
4273
4345
May -
July
Aug -
Oct
Nov -
Jan
Feb -
Apr
May -
July
Aug -
Oct
Nov -
Jan
Feb -
Apr
May -
July
Aug -
Oct
Nov -
Jan
Feb-
Apr
May -
July
Aug -
Oct
WWW.RD-ALLIANCE.ORG
@RESDATALL
24. The value for Organiza[onal
Members
Image, stature, and effecFveness among peers
• Recognized as developers and adopters of standards and
protocols
• Increased influence for their work on data
interoperability in their sectors, markets, and
geographies
• Speaking with influence to na=onal and interna=onal
funding agencies
• Member of world community that shares goals and
addresses common issues
WWW.RD-ALLIANCE.ORG
@RESDATALL
25. The value for Organiza[onal
Members
Network effects
• Networking opportunity to share and promote best
prac=ces and promote standard adop=on when
appropriate
• Access to collegial consultancy resources when
developing a data management strategy for a new
project
• Interac=ng with other Organisa=onal Members (OMs) in
the OA sessions at RDA Plenaries
WWW.RD-ALLIANCE.ORG
@RESDATALL
26. The value for Organiza[onal
Members
OrganizaFonal and technical interacFons
• Having a voice inside RDA, providing advice on the needs
of their sectors and the problems faced in data exchange
• Ability to provide feedback on RDA ac=vi=es, and suggest
future direc=ons and next steps, by commen=ng on
group forma=ons and outputs
• Providing advice to the RDA Council through the
Organisa=onal Advisory Board
• Access on a regular basis to publica=on of RDA
Founda=on budget and financial status
WWW.RD-ALLIANCE.ORG
@RESDATALL
30. hjps://rd-alliance.org/plenaries
RDA 10th Plenary Mee[ng
Montreal, Canada
Roger-Gaudry pavilion, Université de Montréal by Colocho, CC By SA 3.0, cropped
Montréal, Canada
Hosted by
With the support of Research Data
Canada
31. Removing Barriers to
Data Sharing: the
Research Data Alliance
WWW.RD-ALLIANCE.ORG/
@RESDATALL
RDA Global
Email - enquiries@rd-alliance.org
Web - www.rd-alliance.org
Twitter - @resdatall
LinkedIn - www.linkedin.com/in/
ResearchDataAlliance
Slideshare - http://www.slideshare.net/
ResearchDataAlliance
Facebook - https://www.facebook.com/pages/
Research-Data-Alliance/459608890798924
RDA Europe
Email - info@europe.rd-alliance.org
Web - europe.rd-alliance.org
Twitter - @RDA_Europe
RDA US
Email - http://us.rd-alliance.org/contact-us
Web - us.rd-alliance.org
Twitter - @RDA_US
Amy L. Nurnberger
ANURNBERGER@COLUMBIA.EDU
Thanks to all those in
RDA who lent slides!
RDA IN A NUTSHELL
MARK PARSONS
JUAN BICARREGUI
33. What does RDA do?
Members come together through self-formed, volunteer, focussed Working
Groups, exploratory Interest Groups to exchange knowledge, share
discoveries, discuss barriers and poten0al solu0ons, explore and define
policies and test as well as harmonise standards to enhance and facilitate
global data sharing.
RDA members collaborate together regionally and with the global RDA
community to tackle numerous infrastructure challenges related to:
v Reproducibility
v Data preserva=on
v Best prac=ces for domain
repositories
v Curriculum development
v Data cita=on
v Data type registries
v Metadata
v and so many more!
www.rd-alliance.org/about-rda
WWW.RD-ALLIANCE.ORG
@RESDATALL
34. Who Can Join RDA?
◦ Any individual or organiza>on, regardless of profession or discipline,
with an interest in reducing the barriers to data sharing and
exchange and who agrees to RDA’s guiding principles of:
◦ Openness
◦ Consensus
◦ Balance
◦ Harmoniza>on
◦ Community-driven
◦ Non-profit and technology-neutral
Membership is free @ hjp://www.rd-alliance.org/user/register
www.rd-alliance.org/about-rda
WWW.RD-ALLIANCE.ORG
@RESDATALL
35. Geeng involved
Individuals
P Observers
P Contributors
P Drivers
Organisa=ons
P Insight
P Adopt
P Drive
Na=onal level
ü Coordina=on & Knowledge
Exchange, Strategy & / or
Implementa=on
• Members
• WGs-IGs-BoFs
• Requests for
Comments
• Plenaries
• Member
• WGs-IGs-BoFs
• RfCs
• H2020 projects
• Adop>on /
Uptake
• Papers & Events
• Mee>ngs & Fora
• Training & Workshops
• Uptake pilots
www.rd-alliance.org/get-involved.html
WWW.RD-ALLIANCE.ORG
@RESDATALL
36. Why Join RDA?
Individual RDA Member Benefits
◦ Contribute to accelera>on of data
infrastructure development
◦ Work and share experiences with
collaborators throughout the world
◦ Access to extraordinary network of
colleagues with various levels of
experience, perspec>ves and prac>ces
◦ Gain greater exper>se in data science
regardless of whether one is a student,
early or seasoned career professional
◦ Enhance the quality and effec>veness of
personal work and ac>vi>es
◦ Improve one’s compe>>ve advantage
professionally and posi>oning oneself for
leadership within the broader research
community
OrganizaFonal RDA Member
Benefits
◦ Provide an organiza>onal perspec>ve on the
work of RDA and ability to influence RDA’s
direc>on
◦ Assist in implementa>on of RDA Outputs
◦ Par>cipate in all RDA Organiza>onal Forums
◦ Receive regular updates on the work of the
RDA
◦ Aend Organiza>onal Assembly mee>ngs and
vote on proposed policies for considera>on by
the RDA Council and for members of the
Organiza>onal Advisory Board
◦ Provide advice to the Council through the
Organiza>onal Advisory Board
◦ Be recognized on the RDA Website and at RDA
Mee>ngs as a supporter of data
interoperability
www.rd-alliance.org/get-involved.html
WWW.RD-ALLIANCE.ORG
@RESDATALL
37. RDA Plenary 6 (Paris) – 23- 25
Sept 2015
§ RDA deliverables presented:
§ Repository Audit and Certification DSA–WDS
§ RDA/WDS Publishing Data Bibliometrics
§ RDA/WDS Publishing Data Services
§ RDA/WDS Publishing Data Workflows
§ 7 Adoption cases: Deep Carbon Observatory, Platform for
Experimental Collaborative Ethnography, Datafed.net, the Materials
Innovation Infrastructure, EUDAT Collaborative Data Infrastructure,
German Climate Computing Center (DKRZ) & Common Language
Resources and Technology Infrastructure (CLARIN)
§ Focus on enterprise & climate change:
§ 20 enterprises showcased solutions
§ 3 climate change data challenge winners – Biovel, Plume Labs,
Vizonomy
§ Focus on emerging professionals :
§ RDA/EU sponsored 12 European Early Career Researchers and
Scientists & RDA/US sponsored 8 Fellowship winners
www.rd-alliance.org/plenaries/rda-sixth-plenary-mee[ng-paris-france
Theme: “Enterprise Engagement
with a focus on Climate Change”
700 attendees from 40+ countries &
hosted by Cap Digital – France
Co-located conferences:
1. eInfrastructures & RDA for Data
Intensive Science
2. Persistent Identifiers: Enabling
Services for Data Intensive
Research
WWW.RD-ALLIANCE.ORG
@RESDATALL
38. 7 RDA Recommendations/outputs presented:
§ Repository Audit and Certification DSA–WDS
§ RDA/WDS Publishing Data Bibliometrics
§ RDA/WDS Publishing Data Services
§ RDA/WDS Publishing Data Workflows
§ Wheat Data Interoperability Recommendations
§ RDA/CODATA Summer Schools in Data Science and Cloud
Computing in the Developing World Interim Recommendations
§ Brokering Governance Interim Recommendations
§ 11 adoption presentations
www.rd-alliance.org/plenaries/rda-seventh-plenary-mee[ng-tokyo-japan
• 30 interna=onal speakers over
5 plenary sessions
• 7 outputs & 11 adop=on cases
• 8 Working Group mee=ngs
• 25 Interest Group mee=ngs
• 10 Birds of a Feather
• 9 Joint mee=ngs
• 2 Organisa=onal Member
mee=ngs
• RDA for Newcomers Mee=ng
357 aZendees
from 33
countries
WWW.RD-ALLIANCE.ORG
@RESDATALL