Ernst & Young implemented a knowledge management strategy through its Centre for Business Knowledge (CBK). The CBK acted as the central hub that filtered and disseminated knowledge across the organization. It recognized the need to exchange knowledge both internally and externally. E&Y also emphasized teamwork through various forums and social platforms. If advising Cap Gemini, the consultant would recommend integrating E&Y's CBK model through an integration merger strategy. This would combine the strengths of both companies' knowledge management practices while reducing redundant costs and encouraging innovation.
Interface Between Six Sigma and Knowledge Managementsachinmgadekar21
The Slideshow involves
Details about Six Sigma
Details about Knowledge Management
How we interface the Power of Six Sigma and Knowledge Management to succed with the Organizational Goal/
This document introduces the concept of knowledge management. It discusses how knowledge management connects people who have knowledge with those who need it. It also describes how knowledge management provides value by facilitating knowledge creation, retention, and transfer to help organizations learn faster than their competitors and stimulate innovation. Finally, it outlines some common approaches to knowledge management, including using social tools, communities of practice, and networking to share both explicit and tacit knowledge across different levels from personal to organizational.
Modeling Framework to Support Evidence-Based DecisionsAlbert Simard
Describes a framework for modelling in a regulatory environment founded on sound scientific and knowledge management concepts. It includes 1) demand (isue-driven) and supply (model driven) approaches to modelling, 2) balancing modeler, manager, and user perspectives, 3) documentation to demonstrate due diligence, and a 700-term glossary.
The document discusses knowledge management (KM) and its benefits. KM is defined as enabling individuals and teams to collectively create, share, and apply knowledge to achieve objectives. Benefits include reduced time-to-market, increased revenue and profit margins. Examples show companies saving billions through KM. Knowledge is formed from data and information, and can be explicit or tacit. Tacit knowledge is stored in people's minds while explicit knowledge is written down. KM tools and communities of practice help capture and share knowledge.
Describes four levels of knowledge capture: eliciting from individuals, harvesting from communities, gathering from networks, and exploring cyberspace.
This document discusses data, information, knowledge, and information management. It defines data as unorganized raw facts and information as organized data that has meaning. Knowledge is understanding gained through experience and study. Information management is defined as managing organizational processes and systems for acquiring, creating, organizing, distributing, and using information. It also discusses challenges of information management like the digital information explosion and how information management allows organizations to store, protect, and optimize information.
The document discusses the concept of "Ba", a shared space for knowledge creation proposed by Japanese philosophers. It provides three types of Ba - physical, virtual, and mental. Ba exists at different levels from individual to organization and beyond. Knowledge is also categorized into explicit and tacit forms. The SECI model is presented as a framework for knowledge conversion between tacit and explicit through socialization, externalization, combination, and internalization processes. Examples of companies applying Ba concepts such as dedicated teams and cross-functional groups at Toshiba and Maekawa are outlined.
Ernst & Young implemented a knowledge management strategy through its Centre for Business Knowledge (CBK). The CBK acted as the central hub that filtered and disseminated knowledge across the organization. It recognized the need to exchange knowledge both internally and externally. E&Y also emphasized teamwork through various forums and social platforms. If advising Cap Gemini, the consultant would recommend integrating E&Y's CBK model through an integration merger strategy. This would combine the strengths of both companies' knowledge management practices while reducing redundant costs and encouraging innovation.
Interface Between Six Sigma and Knowledge Managementsachinmgadekar21
The Slideshow involves
Details about Six Sigma
Details about Knowledge Management
How we interface the Power of Six Sigma and Knowledge Management to succed with the Organizational Goal/
This document introduces the concept of knowledge management. It discusses how knowledge management connects people who have knowledge with those who need it. It also describes how knowledge management provides value by facilitating knowledge creation, retention, and transfer to help organizations learn faster than their competitors and stimulate innovation. Finally, it outlines some common approaches to knowledge management, including using social tools, communities of practice, and networking to share both explicit and tacit knowledge across different levels from personal to organizational.
Modeling Framework to Support Evidence-Based DecisionsAlbert Simard
Describes a framework for modelling in a regulatory environment founded on sound scientific and knowledge management concepts. It includes 1) demand (isue-driven) and supply (model driven) approaches to modelling, 2) balancing modeler, manager, and user perspectives, 3) documentation to demonstrate due diligence, and a 700-term glossary.
The document discusses knowledge management (KM) and its benefits. KM is defined as enabling individuals and teams to collectively create, share, and apply knowledge to achieve objectives. Benefits include reduced time-to-market, increased revenue and profit margins. Examples show companies saving billions through KM. Knowledge is formed from data and information, and can be explicit or tacit. Tacit knowledge is stored in people's minds while explicit knowledge is written down. KM tools and communities of practice help capture and share knowledge.
Describes four levels of knowledge capture: eliciting from individuals, harvesting from communities, gathering from networks, and exploring cyberspace.
This document discusses data, information, knowledge, and information management. It defines data as unorganized raw facts and information as organized data that has meaning. Knowledge is understanding gained through experience and study. Information management is defined as managing organizational processes and systems for acquiring, creating, organizing, distributing, and using information. It also discusses challenges of information management like the digital information explosion and how information management allows organizations to store, protect, and optimize information.
The document discusses the concept of "Ba", a shared space for knowledge creation proposed by Japanese philosophers. It provides three types of Ba - physical, virtual, and mental. Ba exists at different levels from individual to organization and beyond. Knowledge is also categorized into explicit and tacit forms. The SECI model is presented as a framework for knowledge conversion between tacit and explicit through socialization, externalization, combination, and internalization processes. Examples of companies applying Ba concepts such as dedicated teams and cross-functional groups at Toshiba and Maekawa are outlined.
This document provides an overview of the CTA's approach to knowledge management, including their knowledge ecosystems approach. It discusses definitions of knowledge management and different models for organizing knowledge. The CTA uses a framework for knowledge management intervention that focuses on communication management, information management, ICT strategy, knowledge management, and organizational learning. Their approach emphasizes building strong foundations through assessing culture, structure, competencies and developing a strategy. It also focuses on strengthening enablers like communication and technology infrastructure. Finally, it discusses developing knowledge management processes like research, content curation, sharing, and learning.
Knowledge management and knowledge sharingAtef Mannaa
This document provides an overview of knowledge management and knowledge sharing by reviewing relevant literature. It discusses definitions of knowledge, distinguishing it from information and data. Tacit and explicit knowledge are described, as are individual, group, and organizational knowledge. Models of knowledge creation and management are examined, including distinguishing different types of knowledge and their interaction. Knowledge management is discussed as focusing on managing existing explicit knowledge or building new knowledge, and the role of information technology versus behavioral aspects are addressed.
Law Firm Knowledge Management, An IntroductionConnie Crosby
An introduction to law firm knowledge management by Connie Crosby and Stephanie Barnes, presented at lawTechCamp 2012 in Toronto on May 12, 2012.
Slide 14 (the Knowledge Management Technology graph) is further discussed here: http://www.slaw.ca/2012/06/11/km-101-more-on-technology-complexity/
This document outlines InfoAxon's approach to knowledge management, which focuses on bringing together technology, processes, and practices to achieve connections, context, and culture. It discusses moving from traditional static knowledge storage to more dynamic knowledge repositories and networks. InfoAxon's roadmap includes developing collaborative document management, workflow-based social knowledge management solutions, and semantic knowledge management with semantic search and repositories. The document also describes InfoAxon's knowledge management solutions for the development sector, including a knowledge sharing platform for the United Nations.
Knowledge management and learning organizationRajan Neupane
Knowledge management and learning organizations were discussed. Knowledge was defined as representing reality based on adequate grounds. Knowledge management focuses on people who create and use knowledge, and the processes and technologies for knowledge creation, storage, and access. A learning organization is one where people continually expand their capacity to achieve desired results through shared visions and mental models, team learning, and personal mastery. Key benefits of knowledge management and learning organizations include competitive advantage through innovation and avoiding reinventing solutions.
Knowledge Management basics; an introduction, covering definitions of knowledge and knowledge management, the three enablers of people, process and technology, the two routes of connect and collect, and the two motivators of push and pull. From http://www.knoco.com
This document discusses capturing tacit knowledge and discusses various methods for doing so. It defines tacit knowledge as knowledge that resides in people's minds and is difficult to articulate, consisting of insights, intuitions, and flashes of inspiration. It then discusses why tacit knowledge is crucial for organizations, as clients pay for solutions not just information. It explores various methods for capturing tacit knowledge, such as knowledge repositories, communities of practice, and enterprise knowledge portals. The document also discusses using single experts versus multiple experts to capture knowledge and outlines key challenges and advantages to tacit knowledge capture.
The document discusses knowledge management (KM), including definitions, objectives, challenges, and importance. KM involves connecting people who have knowledge with those who need it through processes, communities, and technology. It aims to leverage organizational knowledge and expertise to improve performance. Failure to share knowledge across boundaries can have serious consequences, as shown by disasters that may have been prevented with better communication.
Knowledge management (KM) refers to a multi-disciplinary approach to achieving organizational objectives by effectively utilizing knowledge. KM involves people management, process management, information management, and explicit and tacit forms of knowledge. The key components of a KM system include knowledge generation, identification, delivery, and storage as well as a supportive culture, skills, leadership, structure, and technology. Benefits of KM include increased collaboration, reduced loss of intellectual capital, decreased costs, improved productivity, and greater innovation.
This document provides an overview of knowledge management. It defines knowledge management as the process of systematically managing and leveraging knowledge within an organization to transform information and intellectual assets into enduring value. Knowledge management involves enabling individuals and groups to capture, store, create, share and apply knowledge to better achieve organizational objectives. The document discusses how knowledge is created, stored, shared, and discusses the difference between knowledge management and traditional document management systems. It also provides an example of an initial document assessment conducted at the Wasson Center to analyze controlled versus uncontrolled documents and gather input on document needs through a survey.
Converting Tacit Knowledge Into Explict November 2010Nitin Potdar
This document discusses methods for capturing tacit knowledge and integrating it into knowledge management systems. It defines explicit and tacit knowledge, noting that tacit knowledge is more personal and difficult to formalize. It explores challenges in articulating and sharing tacit knowledge due to cultural and trust issues. The document recommends socialization, externalization, combination, and internalization as modes for transferring tacit knowledge within an organization. It also provides tips for individual and organizational discipline to systematically capture and share tacit knowledge through documentation, meetings, and mentorship.
Knowledge management (KM) refers to a multidisciplinary approach to achieving organizational objectives by making the best use of knowledge. KM focuses on acquiring, creating, sharing, and organizing knowledge to support important processes. Related to intellectual capital, KM is driven by knowledge-based needs, technology opportunities, intra-organizational changes, human resource collaboration, process improvements, and economic potential. Effective KM integration can enhance decision-making, performance, and competitiveness through structured knowledge application.
This document discusses the evolution of knowledge management (KM) from KM 1.0 to KM 3.0. KM 1.0 focused on collecting knowledge, KM 2.0 focused on sharing knowledge using social media tools, and KM 3.0 focuses on using existing knowledge to help employees do their jobs. The key difference between KM 2.0 and 3.0 is that 3.0 recognizes the need to filter out irrelevant information. Effective KM requires a cultural shift towards openly sharing knowledge and making KM part of employees' regular work.
Managing Tacit And Explicit Knowledge Ratnakarsharmaratnakar_sharma
Knowledge Management is an integrated approach to identifying, capturing, managing and sharing an organization\'s information assets like documents, database, other repositories and employee\'s expertise. It is a conscious strategy of getting the right knowledge to the right people at the right time so they can make the right decisions.
Effective management of knowledge is important because knowledge can create commercial value only when it is put into action. Knowledge is fortunately a process that can be nurtured in organizations.
This presentation explains Tacit and Explicit, the two forms, the knowledge comes from in.
Knowledge management ppt @ bec doms mba genralBabasab Patil
The document discusses key concepts related to knowledge management including:
- Knowledge resides in people's heads in both explicit and tacit forms.
- Technology acts as a conduit to enable knowledge sharing but does not drive knowledge management.
- Knowledge management involves capturing, organizing, accessing, and leveraging knowledge and embraces learning organizations.
- A knowledge management system is one component that supports knowledge management goals along with leadership, organization, and learning.
Tacit knowledge is hard to communicate but can be shared in discussions, storytelling, and personal interactions. This presentation points out a wide variety of tools, methods, and approaches that help surface it.
Knowledge management (KM) refers to identifying and leveraging the collective knowledge in a company to help it compete. KM is a discipline focused on systematically managing the generation, acquisition, exchange, distribution, and utilization of knowledge, intellectual capital and intangible assets to improve organizational performance. Effective KM enhances business performance by designing tools, processes, systems, structures and cultures to improve the creation, sharing and application of critical knowledge.
FORCE11: Future of Research Communications and e-ScholarshipMaryann Martone
FORCE11 is a grassroots organization that aims to accelerate scholarly communications and e-scholarship through technology, education, and community engagement. It was founded in 2011 in Dagstuhl, Germany and is open to anyone with a stake in modernizing scholarly communication. FORCE11 envisions a future where scholarly information is part of an open, universal network and new forms of publication are created to take advantage of this. However, the current scholarly publishing system is inefficient and fragmented. FORCE11 works to address this by developing new authoring, publishing, and reward systems that incentivize open sharing and reuse of scholarly artifacts online.
The document discusses the Future of Research Communications and E-Scholarship (FORCE11), a grassroots organization aimed at accelerating scholarly communications through technology, education, and community. FORCE11 was founded in 2011 in Germany and aims to modernize scholarly publishing using new forms of publication, markup, and reward systems. It acts as a platform bringing together diverse stakeholders to discuss issues and work on shared goals like data citation principles. The organization sees a future where knowledge is openly networked and scholarly objects are more diverse and linked.
This document provides an overview of the CTA's approach to knowledge management, including their knowledge ecosystems approach. It discusses definitions of knowledge management and different models for organizing knowledge. The CTA uses a framework for knowledge management intervention that focuses on communication management, information management, ICT strategy, knowledge management, and organizational learning. Their approach emphasizes building strong foundations through assessing culture, structure, competencies and developing a strategy. It also focuses on strengthening enablers like communication and technology infrastructure. Finally, it discusses developing knowledge management processes like research, content curation, sharing, and learning.
Knowledge management and knowledge sharingAtef Mannaa
This document provides an overview of knowledge management and knowledge sharing by reviewing relevant literature. It discusses definitions of knowledge, distinguishing it from information and data. Tacit and explicit knowledge are described, as are individual, group, and organizational knowledge. Models of knowledge creation and management are examined, including distinguishing different types of knowledge and their interaction. Knowledge management is discussed as focusing on managing existing explicit knowledge or building new knowledge, and the role of information technology versus behavioral aspects are addressed.
Law Firm Knowledge Management, An IntroductionConnie Crosby
An introduction to law firm knowledge management by Connie Crosby and Stephanie Barnes, presented at lawTechCamp 2012 in Toronto on May 12, 2012.
Slide 14 (the Knowledge Management Technology graph) is further discussed here: http://www.slaw.ca/2012/06/11/km-101-more-on-technology-complexity/
This document outlines InfoAxon's approach to knowledge management, which focuses on bringing together technology, processes, and practices to achieve connections, context, and culture. It discusses moving from traditional static knowledge storage to more dynamic knowledge repositories and networks. InfoAxon's roadmap includes developing collaborative document management, workflow-based social knowledge management solutions, and semantic knowledge management with semantic search and repositories. The document also describes InfoAxon's knowledge management solutions for the development sector, including a knowledge sharing platform for the United Nations.
Knowledge management and learning organizationRajan Neupane
Knowledge management and learning organizations were discussed. Knowledge was defined as representing reality based on adequate grounds. Knowledge management focuses on people who create and use knowledge, and the processes and technologies for knowledge creation, storage, and access. A learning organization is one where people continually expand their capacity to achieve desired results through shared visions and mental models, team learning, and personal mastery. Key benefits of knowledge management and learning organizations include competitive advantage through innovation and avoiding reinventing solutions.
Knowledge Management basics; an introduction, covering definitions of knowledge and knowledge management, the three enablers of people, process and technology, the two routes of connect and collect, and the two motivators of push and pull. From http://www.knoco.com
This document discusses capturing tacit knowledge and discusses various methods for doing so. It defines tacit knowledge as knowledge that resides in people's minds and is difficult to articulate, consisting of insights, intuitions, and flashes of inspiration. It then discusses why tacit knowledge is crucial for organizations, as clients pay for solutions not just information. It explores various methods for capturing tacit knowledge, such as knowledge repositories, communities of practice, and enterprise knowledge portals. The document also discusses using single experts versus multiple experts to capture knowledge and outlines key challenges and advantages to tacit knowledge capture.
The document discusses knowledge management (KM), including definitions, objectives, challenges, and importance. KM involves connecting people who have knowledge with those who need it through processes, communities, and technology. It aims to leverage organizational knowledge and expertise to improve performance. Failure to share knowledge across boundaries can have serious consequences, as shown by disasters that may have been prevented with better communication.
Knowledge management (KM) refers to a multi-disciplinary approach to achieving organizational objectives by effectively utilizing knowledge. KM involves people management, process management, information management, and explicit and tacit forms of knowledge. The key components of a KM system include knowledge generation, identification, delivery, and storage as well as a supportive culture, skills, leadership, structure, and technology. Benefits of KM include increased collaboration, reduced loss of intellectual capital, decreased costs, improved productivity, and greater innovation.
This document provides an overview of knowledge management. It defines knowledge management as the process of systematically managing and leveraging knowledge within an organization to transform information and intellectual assets into enduring value. Knowledge management involves enabling individuals and groups to capture, store, create, share and apply knowledge to better achieve organizational objectives. The document discusses how knowledge is created, stored, shared, and discusses the difference between knowledge management and traditional document management systems. It also provides an example of an initial document assessment conducted at the Wasson Center to analyze controlled versus uncontrolled documents and gather input on document needs through a survey.
Converting Tacit Knowledge Into Explict November 2010Nitin Potdar
This document discusses methods for capturing tacit knowledge and integrating it into knowledge management systems. It defines explicit and tacit knowledge, noting that tacit knowledge is more personal and difficult to formalize. It explores challenges in articulating and sharing tacit knowledge due to cultural and trust issues. The document recommends socialization, externalization, combination, and internalization as modes for transferring tacit knowledge within an organization. It also provides tips for individual and organizational discipline to systematically capture and share tacit knowledge through documentation, meetings, and mentorship.
Knowledge management (KM) refers to a multidisciplinary approach to achieving organizational objectives by making the best use of knowledge. KM focuses on acquiring, creating, sharing, and organizing knowledge to support important processes. Related to intellectual capital, KM is driven by knowledge-based needs, technology opportunities, intra-organizational changes, human resource collaboration, process improvements, and economic potential. Effective KM integration can enhance decision-making, performance, and competitiveness through structured knowledge application.
This document discusses the evolution of knowledge management (KM) from KM 1.0 to KM 3.0. KM 1.0 focused on collecting knowledge, KM 2.0 focused on sharing knowledge using social media tools, and KM 3.0 focuses on using existing knowledge to help employees do their jobs. The key difference between KM 2.0 and 3.0 is that 3.0 recognizes the need to filter out irrelevant information. Effective KM requires a cultural shift towards openly sharing knowledge and making KM part of employees' regular work.
Managing Tacit And Explicit Knowledge Ratnakarsharmaratnakar_sharma
Knowledge Management is an integrated approach to identifying, capturing, managing and sharing an organization\'s information assets like documents, database, other repositories and employee\'s expertise. It is a conscious strategy of getting the right knowledge to the right people at the right time so they can make the right decisions.
Effective management of knowledge is important because knowledge can create commercial value only when it is put into action. Knowledge is fortunately a process that can be nurtured in organizations.
This presentation explains Tacit and Explicit, the two forms, the knowledge comes from in.
Knowledge management ppt @ bec doms mba genralBabasab Patil
The document discusses key concepts related to knowledge management including:
- Knowledge resides in people's heads in both explicit and tacit forms.
- Technology acts as a conduit to enable knowledge sharing but does not drive knowledge management.
- Knowledge management involves capturing, organizing, accessing, and leveraging knowledge and embraces learning organizations.
- A knowledge management system is one component that supports knowledge management goals along with leadership, organization, and learning.
Tacit knowledge is hard to communicate but can be shared in discussions, storytelling, and personal interactions. This presentation points out a wide variety of tools, methods, and approaches that help surface it.
Knowledge management (KM) refers to identifying and leveraging the collective knowledge in a company to help it compete. KM is a discipline focused on systematically managing the generation, acquisition, exchange, distribution, and utilization of knowledge, intellectual capital and intangible assets to improve organizational performance. Effective KM enhances business performance by designing tools, processes, systems, structures and cultures to improve the creation, sharing and application of critical knowledge.
FORCE11: Future of Research Communications and e-ScholarshipMaryann Martone
FORCE11 is a grassroots organization that aims to accelerate scholarly communications and e-scholarship through technology, education, and community engagement. It was founded in 2011 in Dagstuhl, Germany and is open to anyone with a stake in modernizing scholarly communication. FORCE11 envisions a future where scholarly information is part of an open, universal network and new forms of publication are created to take advantage of this. However, the current scholarly publishing system is inefficient and fragmented. FORCE11 works to address this by developing new authoring, publishing, and reward systems that incentivize open sharing and reuse of scholarly artifacts online.
The document discusses the Future of Research Communications and E-Scholarship (FORCE11), a grassroots organization aimed at accelerating scholarly communications through technology, education, and community. FORCE11 was founded in 2011 in Germany and aims to modernize scholarly publishing using new forms of publication, markup, and reward systems. It acts as a platform bringing together diverse stakeholders to discuss issues and work on shared goals like data citation principles. The organization sees a future where knowledge is openly networked and scholarly objects are more diverse and linked.
eReearch Symposium workshop on Open ResearchFabiana Kubke
The document discusses a workshop held in New Zealand to explore the meaning and feasibility of open research in the country's context. It explores views on the value of open research and how to implement related principles through actionable tasks. Challenges identified include infrastructure support, cultural shifts, incentives, and collaboration between different stakeholders. Specific near-term actions proposed are building researcher networks, identifying advocates, raising awareness through events and social media, and developing a document on open research for relevant stakeholders.
NISO Two Day Virtual Conference:
Using the Web as an E-Content Distribution Platform:
Challenges and Opportunities
Oct 21-22, 2014
Maryann Martone, Ph.D., Professor of Neuroscience, University of California, San Diego
ELPUB 2018 Feminist Open Science workshopLeslie Chan
This was the slides for the workshop on Feminist Open Science presented at ELPUB2018 in Toronto. Notes for the session is available here: https://docs.google.com/document/d/1zr51nZ4VRjVNLixeRc_4SPa-liSALADLTbJ1RUJYcpo/edit
"This workshop will centre on how current discourse around Open Science has tended to focus on the creation of new technological platforms and tools to facilitate sharing and reuse of a wide range of research outputs, but has largely avoided tackling many important issues related to inclusion of a diversity of perspectives in science. We believe a feminist perspective can help to surface these issues, particularly with regard to the need for inclusive infrastructure, which are especially important as Open Science increasingly becomes part of government agendas and policies. We expect that researchers, practitioners and policy makers interested in Open Science will benefit from this workshop to think about issues of inclusivity in Open Science that are not receiving sufficient attention. We expect participants who attend this workshop will gain awareness about relevant resources and work that has been done by feminist technoscience scholars to expand the perspectives of Open Science. We hope that participants will take away new possibilities for their work that they may not have considered before. For policy makers, this workshop will be particularly relevant to help think about how evidence for Open Science should be assessed from a more feminist inclusive standpoint. The workshop will also present results from a two-day workshop on Feminist Open Science that will take place prior to the ELPUB workshop, with the intent of soliciting feedback and collaboration."
This document discusses strategies for governments to leverage "networked individuals" through citizen sourcing and collaborative network organizations (CNOs). It outlines how the wisdom of crowds can outperform small groups by bringing diverse viewpoints and rapid information sharing. Case studies of distributed problem solving networks are presented. The document argues that well-managed networked individuals through CNOs can provide direct expertise to governments, if leaders focus on activities over tools, start small with scalable designs, and cultivate bottom-up collaboration. However, it also notes reasons why governments may be hesitant to utilize CNOs due to risks of losing control and commitment.
1) The document discusses how open data and interoperability can drive innovation by empowering people and communities through access to government data.
2) Key points include how open data can meet regulatory needs, communicate with citizens, and spur new economic development and innovation.
3) An open data ecosystem is created by gathering and connecting data, infrastructure, developers, and communities to empower choices and change behavior.
Big data and Digital Transformations in the HumanitiesMartin Wynne
The document discusses the opportunities and challenges of digital humanities research using large datasets. It outlines how new infrastructure initiatives have lowered barriers to digital research but that interoperability, sharing, and sustainability of resources remain difficult. The humanities risk becoming less relevant if new forms of data-driven research are not embraced, but care must be taken to avoid an overly empirical view that diminishes qualitative analysis. Achieving provisional standards and categories could promote shared infrastructure while still allowing traditional humanities criticism.
Open Access and Research Communication: The Perspective of Force11Maryann Martone
Presentation at the National Federation of Advanced Information Services Workshop: Open Access to Published Research: Current Status and Future Directions, Philadelphia, PA USA November 22, 2013
The document discusses digital curation and open educational resources (OER) in three key areas:
1) It outlines how OER can promote social justice through affordable and accessible education for all.
2) It explains that digital curation involves collecting, preserving, and providing access to digital information and research data throughout its lifecycle at the individual, institutional, and societal levels.
3) It argues that teaching digital literacy skills, such as critical thinking, collaboration, and cultural understanding, is important for effective use of OER and digital curation.
California Ocean Science Trust " Building a Sustainable Knowledge Base for ...Tom Moritz
"Building a Sustainable Knowledge Base for the Marine Protected Areas Monitoring Enterprise" a presentation to the California Ocean Science Trust, Oakland, California March 16, 2010
Future Flight Fridays: Public Trust in Future FlightKTN
‘Public Acceptance’ can be a challenging theme for Future Flight consortia to approach. Hear from Professor Edmond Awad on the ‘Moral Machine’, Professor Susan Molyneux-Hodgson discussing responsible innovation and technical democracy and Professor Sarah Hartley on moving from public acceptance to knowledge co-production.
This session will focus on:
- What ‘public acceptance’ means, and key challenges consortia face around public trust and acceptance of new technologies in the context of the Future of Flight
- Research areas and approaches to understanding barriers of public trust and acceptance of future of flight challenge proposals
- Potential Tools for public engagement and data collection, drawing a picture on the public perception of ethical implications, trust, and responsibility
- Areas such as the Ethics of Technology; Responsible Innovation; Interdisciplinary collaboration; Public Engagement and Computational Social Science
This document discusses Ben Shneiderman's research on facilitating social participation through information visualization and social media. It outlines his vision to increase social participation in areas like e-commerce, health, education and government through developing theories of how social media networks evolve and increasing participation. It also discusses providing scalable technology infrastructure that protects privacy and security while enabling social participation. The document provides examples of Shneiderman's research projects on visualizing social networks and increasing participation through tools like NodeXL and strategies for community managers.
Sourcing Lecture 5 Crowdsourcing and Social MediaFrank Willems
Crowdsourcing and social media can be leveraged for change management. The document discusses crowdsourcing, social networks, and the principles of leveraging these tools. It covers how to develop a crowdsourcing strategy by considering the people, objectives, relationship approach, and technology. Social media can support crowdsourcing efforts by facilitating communication and gathering data and trends. Change management must consider different generations' characteristics and change preferences when utilizing these tools.
Lecture 5 2011 2012 crowdsourcing and social mediaFrank Willems
Here are my assessments of the objectives of the examples provided:
- Wikipedia is focused on energizing and embracing. It aims to connect enthusiastic contributors to share and improve information, integrating their ideas.
- Lego is focused on embracing. It aims to integrate the ideas of its community into improving its products.
- The fishermen community is focused on supporting. It aims to help fishermen help and support each other by sharing knowledge and data.
- Iens is focused on listening. It aims to listen to its community for research and better understanding of restaurant customers.
- The gardenbird counting is focused on energizing. It aims to connect enthusiastic amateur birdwatchers to supercharge data collection about bird movements.
Research into Practice case study 2: Library linked data implementations an...Hazel Hall
The document summarizes a presentation given by Dr. Diane Pennington and Laura Cagnazzo on library linked data implementations and perceptions. The presentation discussed the evolution of the semantic web and linked open data principles. It provided an overview of a study on the status and perceptions of linked data among European national libraries and Scottish libraries. The study found lack of awareness and expertise to be challenges for implementation. Benefits included improved data visibility and opportunities for collaboration. Recommendations focused on training, collaboration, and developing implementation guidelines and case studies.
How Data is Transforming Health and SocietyJeanne Holm
Open data refers to data that can be freely used, shared, and modified by anyone for any purpose. Many sectors benefit from open data including healthcare, financial services, government, and non-profits. Open data is estimated to create $3 trillion in economic growth annually in the US by powering innovation. The open data movement aims to provide transparency and allow people to make better decisions by democratizing access to data.
Data for Good: How Data is Transforming Business and SocietyJeanne Holm
From high tech to rural Uganda, the data that companies and governments share is being used around the world by all kinds of people to make life better.
The document discusses open satellite data and geospatial information systems (GIS). It notes that satellites gather high-fidelity, real-time data about locations and conditions on Earth, oceans, atmosphere and socioeconomic factors. Examples are given of how such data has been used for applications like analyzing global climate change, earthquake activity, earth and ocean science, helping with disasters through early warnings, and creating a multi-billion dollar weather and GPS industry. The document advocates for open data and citizen science, including crowdsourcing to solve food security challenges and correcting data. It asks what GIS data is needed in Uganda and suggests ways to utilize and explore such open data.
Connections between big data and open data. Includes a case study of Data.gov and the ways that companies, charities, and others are using open data to improve the lives of people around the planet.
Data.gov provides access to over 400,000 datasets from 180 US agencies and organizations in easy to use formats. It encourages developers to build innovative applications using open data and drives knowledge sharing and innovation globally and across 18 communities. Data.gov is migrating its platform to the open source Open Government Platform to improve search capabilities, enable application statistics tracking, and allow federated searching of agency and local government catalogs. The presentation calls for continued collaboration to securely share and link government data and empower communities and businesses to use data to address global issues.
Using Data.gov Communities to Drive Innovation and Collaboration aims to foster communities on Data.gov around priority topics to connect innovators, industry, academia, and government. Communities are public spaces that present data from multiple organizations on a single topic. Examples include Health, Energy, Education, and Ocean communities. Agencies are encouraged to lead or contribute to communities, engage their networks, and sponsor challenges to drive innovation using government data.
Knowledge Sharing and Social Media at NASAJeanne Holm
This represents work done while I was serving as the Chief Knowledge Architect at NASA's Jet Propulsion Laboratory using social media to encourage collaboration inside and outside the agency
The document discusses how open data and knowledge sharing can drive innovation. It provides examples of how government data from sources like NASA, NOAA, and Health and Human Services have been used by developers to create applications that improve lives. Open data initiatives like Data.gov and Health.Data.gov aim to gather data, connect communities of developers and experts, and encourage the creation of technologies and visualizations that empower citizens. The ultimate goal is to fuel innovation and economic opportunities through making vast amounts of government data openly available.
The document discusses the goals and progress of Data.gov, a US government platform that provides access to government data. It aims to 1) gather data from agencies and make it openly available, 2) connect developers, scientists and citizens to find solutions, 3) provide infrastructure based on standards, and 4) encourage apps and visualizations using the data. Since 2009, Data.gov has grown from 47 to over 400,000 datasets and driven the creation of hundreds of applications and visualizations that have improved lives. The document outlines plans to further open data internationally and drive innovation.
A presentation on knowledge sharing, innovation, and open government data presented to the University of Adelaide MBA program during Dr. David Pender's class
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
5. Generations Share
Differently
• 1930-50’s era generation
– Focus on society
– Friendships are forged through adversity
• 1960-70’s era generation
– Focus on community
– Friendships forged through identification with a cause
• 1980-90’s era generation
– Focus on the individual
– Friendships forged through individual goal accomplishment
• 2000’s era generation
– Focus on common interests
– Friendships are created or thrive virtually…
5
6. Trust and Reciprocity
• Trust can be built on
• Personal experience
• “I know you”
• Shared experience
• “We both worked on the
same project”
• Transfer of trust
• “We know the same person
who trusts us”
• Shared values
• “We agree to operate by the
same rules”
6
8. Creating an Opportunity
• Knowledge management activities provide the
chance to look across an organization, regardless
of boundaries, and find opportunities to make a
difference…
NASA’s Knowledge Management goal
Knowledge management is getting the right information to the right
people at the right time, and helping people create knowledge and
share and act upon information in ways that will measurably improve
the performance of an organization and its partners.
8
9. Why Is KM Critical to NASA?
• We are constantly challenged to document and integrate
our lessons learned to effectively manage the risk involved
in space exploration and human space flight
• By its nature, NASA’s employees have specialized
knowledge
• The workforce in the Agency is aging
• Our goal is to share knowledge with each other and with
the public
9
10. The Situation: Critical Knowledge is
Locked in Employees’ Heads
Content
Documents
Drawings
Reports
20%
People
Employee knowledge
Know-how
Skills
Experience
80%
63% of
employees
complain of the
difficulty in
accessing
undocumented
knowledge as a
major problem
10
11. KM Critical Success Factors
Training,
Services,
Strategic Tools
Supporting
Services
Culture
Knowledge
Management
Access Methods,
Building Blocks,
Standards,
Service Bases
IT
Infrastructure
Ownership,
Sharing and Use,
Incentives and Rewards
Knowledge
Architecture
Knowledge Resources,
Repositories, Content,
Context, Directories,
Interoperability
11
12. Key Areas for NASA’s KM Strategy
Sustain NASA’s knowledge across
missions and generations
Identify and capture the information that
exists across the Agency
Help people find, organize, and share
the knowledge we already have
Efficiently manage NASA’s knowledge
resources
• Increase collaboration and to facilitate
knowledge creation and sharing
– Develop techniques and tools to enable
teams and communities to collaborate
across the barriers of time and space
12
16. Learning Process Occurs Behind All Components: Embed lessons into tools and communities
Center Lessons Learned
Expertise
Locator
Interagency/Aerospace
Lessons Learned
NASA Lessons Learned
NASA
Community Portals
Collaborative Tools
Competency
Management
System
Exploration Systems
Project Environment
Metasearch
Feedback
Document and Data Repositories
Advanced
Engineering
Tools
Training
Policies and
Procedures
Feedback
Responsibility Areas
NASA Engineering Network—Blue
Agency Resources—Green
16
17. Knowledge Management Roadmap
Modeling Expert Knowledge
Capturing Knowledge
Integrating Distributed Knowledge
Sharing Knowledge
• Adaptive knowledge infrastructure
is in place
• Knowledge resources identified
and shared appropriately
• Timely knowledge gets to the right
person to make decisions
• Intelligent tools for authoring
through archiving
• Cohesive knowledge development
between NASA, its partners, and
customers
• Instrument design is semi-automatic
based on knowledge repositories
• Mission software auto-instantiates
based on unique mission parameters
• KM principals are part of culture and
supported by layered COTS products
• Remote data management allows
spacecraft to self-command
Enables seamless integration of
systems throughout the world
and with robotic spacecraft
Enables sharing of essential
knowledge to complete
Agency tasks
• MarsNet
• Mars Exploration Rovers
• Space Interferometry Mission
2003
2007
• Knowledge gathered anyplace
from hand-held devices using
standard formats on interplanetary
Internet
• Expert systems on spacecraft
analyze and upload data
• Autonomous agents operate
across existing sensor and
telemetry products
• Industry and academia supply
spacecraft parts based on
collaborative designs derived from
NASA’s knowledge system
• Systems model experts’ patterns
and behaviors to gather
knowledge implicitly
• Seamless knowledge exchange
with robotic explorers
• Planetary explorers contribute to
their successor’s design from
experience and synthesis
• Knowledge systems collaborate
with experts for new research
Enables real-time capture of tacit
knowledge from experts on
Earth and in permanent
outposts
Enables capture of knowledge at the
point of origin, human or robotic,
without invasive technology
•
•
•
•
• Interstellar missions
• Permanent lunar and
Martian colonies
Mars robotic outposts
Comet Nucleus Sample Return
Saturn Ring Observer
Terrestrial Planet Finder
• Europa Lander/Submersible
• Titan Organics: Lander/Aerobot
• Neptune Orbiter/Triton Observer
2010
2025
18. Defining the Competitive Edge
• Historically, innovation and breakthrough ideas and
technologies occur at the edges and boundaries of
networks
• Thomas Kuhn’s The Structure of Scientific
Revolutions describes such radical innovation as a
paradigm shift
– Astronomy: Ptolemy to Copernicus
– Biology: Creation to Darwinian evolution
– Politics: English monarchy to Magna Carta
• Where will your innovation occur?
18
29. Our Modes of Communication
Keep Changing
• YouTube is now second largest
search engine in the world
• 1.5 million pieces of content
shared daily on Facebook
• 250 million visitors each month
to YouTube and Facebook
• Mobile devices will be world’s
primary connection tool to the
Internet in 2020
29
30. Citizens and Businesses Need…
• Government to provide more and
better information for
– Transparency
– Economic growth
– Education and learning
30
31. Why Do Agencies
Share Data?
• Meet regulatory compliance
• Better communicate with citizens and
stakeholders
31
32. Why Do Countries Share Data?
• Create new economic development
• Kickstart innovation
32
34. Open Government Initiative
• Transparency promotes
accountability
• Participation allows
people to contribute ideas
• Collaboration encourages
cooperation within
government and with
industry
34
36. Project Open Data
• Open source
government policy,
technical guidance,
and software
• Citizen contributions
to policy, code, and
content
• http://project-opendata.github.io/
36
37. Data.gov
• Provides instant access
to ~400,000 datasets in
easy to use formats
• Contributions from 172
agencies, UN, and World
Bank
• Encourage development
of innovative applications
• Drive innovation and
knowledge use across
the globe
37
40. Creating a Data Ecosystem
1. Gather data
–
from many places and give it freely
2. Connect the community
–
to collaborate through social media, events,
and platforms
3. Provide an infrastructure
–
built on standards and interoperability
4. Encourage technology developers
–
to create apps, maps, and visualizations
that empower people’s choices
5. Gather more data
–
and connect more people
“A Strategy for American
Innovation” published
September 2009
40
42. Creating Community
• Communities are public-facing
spaces that present data,
information, and subject matter
knowledge about a single topic
from many organizations in one
place
– The topics for communities can be
chosen based on priorities from the
public, departments based on their
mission, or issues of national
importance
42
43. Creating a Shared Vision
• These questions help to guide early discussions
1. Vision: What will the community connection and collaboration
look like in the future?
2. Leaders: Who will help to lead the community?
3. Participants: Who will participate?
4. Outcome: What are the expected outcomes, metrics, and
measurements that will show success? How will this
community work to improve the lives of citizens?
5. Functionality: What types of activities will be conducted on the
site (forums, blogs, wikis, ranking, rating, challenges, or apps)?
6. Content: What content should be displayed
7. Interactivity: What ways will the community interact with the
leaders, with each other, and with the public?
43
44. Agriculture Drives Innovation
and Saves Lives
• Food.Data.gov connects
farmers with innovators,
industry, academia, and
governments around the
world
• Coordinated with the G8
and African leaders
Farmers’ Markets
iCow
44
45. Data.gov for the Economy
• NOAA’s data helped build
weather-related business
• When the Department of
Defense released satellite
data…private industry
created affordable GPS
devices!
• Together these open data
services empower $100B
data-driven industries
45
50. USAID Food Security Challenge
• Kat Townsend at USAID had a
great idea
– Develop apps to increase food
security
– “Crowdsourcing the questions
and crowdsourcing the
solutions”
– Three Ideation Jams Code-athon and a Data Palooza
– 10,000 data entries corrected
with 145 volunteers in 16 hours
with 85% accuracy
– http://idea.usaid.gov/g8
50
54. Weather Underground
• Severe weather
warnings allow people to
react appropriately to
threats
• Internationalization:
MeteoAlarm (EUMetNet)
• Need shared models
and standards
• www.wunderground.com
54
60. Powered Through Advanced
Technologies
• Provides developers tools and raw
data formats to develop new
capabilities
• Partnership with
– W3C: eGov Community Group +
activities, standards, and
recommendations
– RPI for research in semantic web and
open linked data
• Data hosted in the cloud
• Open source platform
• Builds on ontologies developed in
specific areas
60
61. US Open Government Action Plan
• In September 2011, President
Obama announced at the UN
General Assembly…
– Contribute Data.gov as a platform
(Government of India and the U.S.)
– Foster communities on Data.gov
• Health, energy, and law plus new
communities in education, research
and development, and public safety
• In September 2012, President
Obama reported these actions
delivered
61
62. Open Government Platform (OGPL)
• Open source co-developed by Governments
of India, US, and Canada
• Data.gov is running on OGPL (as is India,
Ghana, and more in development)
• Coordinating with open data providers,
platforms, W3C, World Bank, CKAN, and
open source developers worldwide
• Public comments and tracker on Github
• Drupal and CKAN operational code available
• Email, Github, Facebook, Drupal.org, and
Twitter for discussion
– https://github.com/opengovtplatform
– http://www.opengovplatform.org
62
64. A Global
Movement Has
Begun to Provide
Transparency and
Democratization
of Data
Don’t see your site?
Update via @usdatagov
64
65. The Path Ahead
•
•
•
•
Bring data up and out of government to the public
Make data accessible and linked
Create communities to understand and apply data
Connect and collaborate with small businesses,
industry, and academia to drive innovation
• Continue to develop OGPL with community
development
• Share with others to understand global issues
We need to securely architect our systems
for interoperability and openness from conception.
—Digital Government
65
Kat TownsendDevelop apps to increase food security“The best way for people to have impact if for people to learn from their peers”“Crowdsourcing the questions and crowdsourcing the solutions”Three Ideation Jams leading to a Code-a-thon and a Data Paloozahttp://idea.usaid.gov/g8
This is just the beginning.Host ideation jams to do more with the dataNot just a one-off. The map will be updated.Excited to see how lives are improved from the data release
John CelenzaSevere weather warnings allow people to react appropriately to threatsInternationalization: MeteoAlarm (EUMetNet)Need shared models and standardshttp://www.wunderground.com/
Raise your hand if you’ve ever saved a life? Congratulations!Raise your hand if you’ve ever written a line of code? You are a potential lifesaver.
Two emergency room doctors in Colorado50,000 patients over 25 years7,000,000 patients in 2 years100 employees and adding more
Most popular types of datasets: geography and environment, health and nutrition, and national security and veterans affairs