A review of Eysenbach, G., 2011. Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact. Journal of Medical Internet Research, 13(4), p.e12
The document discusses using semantic web technologies like SIOC and FOAF to help journalists integrate user-generated social media content into news stories. It describes how these ontologies can connect disparate online communities and metadata to aid in navigating, verifying, and reusing social data. The project aims to explore customizing SIOC for journalism and extending vocabularies like Schema.org to semantically enrich social content for news gathering and reporting.
What your hairstyle says about your political preferences, and why you should...Benjamin Heitmann
Recent developments in the area of social networking have lead to prominent users leaving facebook due to privacy concerns.
In order to really understand what motivated facebook to implement these controversial changes, you have to look at the future of recommender systems. I will introduce my current research in the areas of multi-source, cross-domain and privacy enabled user profiling and recommendation,
and show how it relates to current developments in the social networking space.
The document summarizes the Oxford e-Social Science Project (OeSS), which aimed to identify challenges and solutions related to emerging digital research infrastructure and practices. The project occurred in two phases from 2005-2012, studying issues like privacy, ethics, and how researchers access data and collaborate in networked environments. It highlights both opportunities and challenges of networked institutions and individual researchers, and calls for a focus on implications for research quality rather than just technical innovation.
An architecture for privacy-enabled user profile portability on the Web of DataBenjamin Heitmann
Presentation at the Heterogeneous Recommendation Workshop at the ACM Recommender Systems Conference 2010.
Providing relevant recommendations requires access to user profile data. Current social networking ecosystems allow third party services to request user authorisation for accessing profile data, thus enabling cross-domain recommendation. However these ecosystems create user lock-in and social networking data silos, as the profile data is neither portable nor interoperable. We argue that innovations in reconciling heterogeneous data sources must be also be matched by innovations in architecture design and recommender methodology. We present and qualitatively evaluate an architecture for privacy-enabled user profile portability, which is based on technologies from the emerging Web of Data (FOAF, WebIDs and the Web Access Control vocabulary). The proposed architecture enables the creation of a universal “private by default” ecosystem with interoperability of user profile data. The privacy of the user is protected by allowing multiple data providers to host their part of the user profile. This provides an incentive for more users to make profile data from different domains available for recommendations.
Lessons and requirements from a decade of deployed Semantic Web appsBenjamin Heitmann
The document summarizes lessons learned from analyzing over 100 Semantic Web applications from challenge competitions over the past decade. It finds that while standards like RDF, OWL and SPARQL are widely used, there remain gaps in publishing and updating Linked Data. Most applications require human intervention for data integration due to noisy RDF data. There is also a mismatch between graph-based data models and relational/object-oriented components. The document recommends addressing these issues through more guidelines, libraries, and software frameworks to improve the software engineering process for building Semantic Web applications.
Semantic, Cognitive, and Perceptual Computing – three intertwined strands of ...Amit Sheth
Keynote at Web Intelligence 2017: http://webintelligence2017.com/program/keynotes/
Video: https://youtu.be/EIbhcqakgvA Paper: http://knoesis.org/node/2698
Abstract: While Bill Gates, Stephen Hawking, Elon Musk, Peter Thiel, and others engage in OpenAI discussions of whether or not AI, robots, and machines will replace humans, proponents of human-centric computing continue to extend work in which humans and machine partner in contextualized and personalized processing of multimodal data to derive actionable information.
In this talk, we discuss how maturing towards the emerging paradigms of semantic computing (SC), cognitive computing (CC), and perceptual computing (PC) provides a continuum through which to exploit the ever-increasing and growing diversity of data that could enhance people’s daily lives. SC and CC sift through raw data to personalize it according to context and individual users, creating abstractions that move the data closer to what humans can readily understand and apply in decision-making. PC, which interacts with the surrounding environment to collect data that is relevant and useful in understanding the outside world, is characterized by interpretative and exploratory activities that are supported by the use of prior/background knowledge. Using the examples of personalized digital health and a smart city, we will demonstrate how the trio of these computing paradigms form complementary capabilities that will enable the development of the next generation of intelligent systems. For background: http://bit.ly/PCSComputing
Physical-Cyber-Social Computing involves the integration of observations from physical sensors, knowledge and experiences from cyber systems, and social interactions from people. This will allow machines to understand contexts, correlate multi-domain data, and provide personalized solutions by leveraging background knowledge spanning physical, cyber, and social domains. Semantic computing plays a key role in bridging differences between domains to derive insights. The vision is for systems that can proactively initiate information needs with minimal human involvement.
Implementing Semantic Web applications: reference architecture and challengesBenjamin Heitmann
Best paper award at the workshop for Semantic Web enabled software engineering 2009, at the International Semantic Web Conference 2009.
Full paper at: http://ceur-ws.org/Vol-524/swese2009_2.pdf
Summary of the slides and the paper:
* an empirical analysis of 98 Semantic Web applications based on an architectural analysis and an application functionality questionnaire
* a reference architecture for Semantic Web applications
* the main challenges of implementing Semantic Web technologies and their effect on an example application
* approaches for mitigating the challenges
The document discusses using semantic web technologies like SIOC and FOAF to help journalists integrate user-generated social media content into news stories. It describes how these ontologies can connect disparate online communities and metadata to aid in navigating, verifying, and reusing social data. The project aims to explore customizing SIOC for journalism and extending vocabularies like Schema.org to semantically enrich social content for news gathering and reporting.
What your hairstyle says about your political preferences, and why you should...Benjamin Heitmann
Recent developments in the area of social networking have lead to prominent users leaving facebook due to privacy concerns.
In order to really understand what motivated facebook to implement these controversial changes, you have to look at the future of recommender systems. I will introduce my current research in the areas of multi-source, cross-domain and privacy enabled user profiling and recommendation,
and show how it relates to current developments in the social networking space.
The document summarizes the Oxford e-Social Science Project (OeSS), which aimed to identify challenges and solutions related to emerging digital research infrastructure and practices. The project occurred in two phases from 2005-2012, studying issues like privacy, ethics, and how researchers access data and collaborate in networked environments. It highlights both opportunities and challenges of networked institutions and individual researchers, and calls for a focus on implications for research quality rather than just technical innovation.
An architecture for privacy-enabled user profile portability on the Web of DataBenjamin Heitmann
Presentation at the Heterogeneous Recommendation Workshop at the ACM Recommender Systems Conference 2010.
Providing relevant recommendations requires access to user profile data. Current social networking ecosystems allow third party services to request user authorisation for accessing profile data, thus enabling cross-domain recommendation. However these ecosystems create user lock-in and social networking data silos, as the profile data is neither portable nor interoperable. We argue that innovations in reconciling heterogeneous data sources must be also be matched by innovations in architecture design and recommender methodology. We present and qualitatively evaluate an architecture for privacy-enabled user profile portability, which is based on technologies from the emerging Web of Data (FOAF, WebIDs and the Web Access Control vocabulary). The proposed architecture enables the creation of a universal “private by default” ecosystem with interoperability of user profile data. The privacy of the user is protected by allowing multiple data providers to host their part of the user profile. This provides an incentive for more users to make profile data from different domains available for recommendations.
Lessons and requirements from a decade of deployed Semantic Web appsBenjamin Heitmann
The document summarizes lessons learned from analyzing over 100 Semantic Web applications from challenge competitions over the past decade. It finds that while standards like RDF, OWL and SPARQL are widely used, there remain gaps in publishing and updating Linked Data. Most applications require human intervention for data integration due to noisy RDF data. There is also a mismatch between graph-based data models and relational/object-oriented components. The document recommends addressing these issues through more guidelines, libraries, and software frameworks to improve the software engineering process for building Semantic Web applications.
Semantic, Cognitive, and Perceptual Computing – three intertwined strands of ...Amit Sheth
Keynote at Web Intelligence 2017: http://webintelligence2017.com/program/keynotes/
Video: https://youtu.be/EIbhcqakgvA Paper: http://knoesis.org/node/2698
Abstract: While Bill Gates, Stephen Hawking, Elon Musk, Peter Thiel, and others engage in OpenAI discussions of whether or not AI, robots, and machines will replace humans, proponents of human-centric computing continue to extend work in which humans and machine partner in contextualized and personalized processing of multimodal data to derive actionable information.
In this talk, we discuss how maturing towards the emerging paradigms of semantic computing (SC), cognitive computing (CC), and perceptual computing (PC) provides a continuum through which to exploit the ever-increasing and growing diversity of data that could enhance people’s daily lives. SC and CC sift through raw data to personalize it according to context and individual users, creating abstractions that move the data closer to what humans can readily understand and apply in decision-making. PC, which interacts with the surrounding environment to collect data that is relevant and useful in understanding the outside world, is characterized by interpretative and exploratory activities that are supported by the use of prior/background knowledge. Using the examples of personalized digital health and a smart city, we will demonstrate how the trio of these computing paradigms form complementary capabilities that will enable the development of the next generation of intelligent systems. For background: http://bit.ly/PCSComputing
Physical-Cyber-Social Computing involves the integration of observations from physical sensors, knowledge and experiences from cyber systems, and social interactions from people. This will allow machines to understand contexts, correlate multi-domain data, and provide personalized solutions by leveraging background knowledge spanning physical, cyber, and social domains. Semantic computing plays a key role in bridging differences between domains to derive insights. The vision is for systems that can proactively initiate information needs with minimal human involvement.
Implementing Semantic Web applications: reference architecture and challengesBenjamin Heitmann
Best paper award at the workshop for Semantic Web enabled software engineering 2009, at the International Semantic Web Conference 2009.
Full paper at: http://ceur-ws.org/Vol-524/swese2009_2.pdf
Summary of the slides and the paper:
* an empirical analysis of 98 Semantic Web applications based on an architectural analysis and an application functionality questionnaire
* a reference architecture for Semantic Web applications
* the main challenges of implementing Semantic Web technologies and their effect on an example application
* approaches for mitigating the challenges
Reality mining aims to map an organization's cognitive infrastructure by capturing detailed data on human networks using sensors. It analyzes conversations, topics, locations and relationships between individuals to infer expertise, social networks and how communication may change. This could help with applications like knowledge management, team formation and understanding global influences in an organization. However, it also raises privacy concerns that would need to be addressed.
Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Inte...Amit Sheth
Ora Lassila and Amit Sheth, "Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Interoperability", Invited Talk at ONC-HHS Invitational Workshop on Next Generation Interoperability for Health, Washington DC, January 19-20, 2011.
Knowledge Will Propel Machine Understanding of Big DataAmit Sheth
1) Amit Sheth presented on how knowledge can help machines better understand big data.
2) He discussed challenges like understanding implicit entities, analyzing drug abuse forums, and understanding city traffic using sensors and text.
3) Sheth argued that knowledge graphs and ontologies can help interpret diverse data types and provide contextual understanding to help solve real-world problems.
Enabling Case-Based Reasoning on the Web of Data (How to create a Web of Exp...Benjamin Heitmann
Presentation at the "Reasoning from experiences on the Web" workshop (WebCBR 2010) at the International Conference on Case Based Reasoning 2010.
Abstract:
While Case-based reasoning (CBR) has successfully been deployed on the Web, its data models are typically inconsistent with existing information infrastructure and standards. In this paper, we examine how
CBR can operate on the emerging Web of Data, with mutual benefits. The
expense of knowledge engineering and curating a case base can be reduced
by using Linked Data from the Web of Data. While Linked Data provides experiential data from many different domains, it also contains inconsistencies, missing data and noise which provide challenges for logic-based reasoning. CBR is well suited to provide alternative and robust reasoning approaches. We introduce (i) a lightweight CBR vocabulary which is
suited for the open ecosystem of the emerging Web of Data, and provide
(ii) a detailed example of a case base using data from multiple sources. We
propose that for the first time the Web of Data provides data and a real
context for open CBR systems.
This is a brief a brief review of current multi-disciplinary and collaborative projects at Kno.e.sis led by Prof. Amit Sheth. They cover research in big social data, IoT, semantic web, semantic sensor web, health informatics, personalized digital health, social data for social good, smart city, crisis informatics, digital data for material genome initiative, etc. Dec 2015 edition.
This tutorial presents tools and techniques for effectively utilizing the Internet of Things (IoT) for building advanced applications, including the Physical-Cyber-Social (PCS) systems. The issues and challenges related to IoT, semantic data modelling, annotation, knowledge representation (e.g. modelling for constrained environments, complexity issues and time/location dependency of data), integration, analy- sis, and reasoning will be discussed. The tutorial will de- scribe recent developments on creating annotation models and semantic description frameworks for IoT data (e.g. such as W3C Semantic Sensor Network ontology). A review of enabling technologies and common scenarios for IoT applications from the data and knowledge engineering point of view will be discussed. Information processing, reasoning, and knowledge extraction, along with existing solutions re- lated to these topics will be presented. The tutorial summarizes state-of-the-art research and developments on PCS systems, IoT related ontology development, linked data, do- main knowledge integration and management, querying large- scale IoT data, and AI applications for automated knowledge extraction from real world data.
Related: Semantic Sensor Web: http://knoesis.org/projects/ssw
Physical-Cyber-Social Computing: http://wiki.knoesis.org/index.php/PCS
This document summarizes four knowledge management processes used by Defence Research & Development Canada (DRDC): monitoring the environment, producing intelligence, mobilizing knowledge, and integration. It describes DRDC's environmental monitoring process which involves acquiring external data through 10 pathways, including monitoring cyberspace, media, research, literature, conferences, communities of practice, soliciting practitioners, reviewing experiences, individual discovery, and receiving unsolicited information. Each pathway requires different support services to filter and analyze the acquired information and detect patterns of interest.
Quantified Self Ideology: Personal Data becomes Big DataMelanie Swan
A key contemporary trend emerging in big data science is the quantified self: individuals engaged in the deliberate self-tracking of any kind of biological, physical, behavioral, or transactional information, as n=1 individuals or in groups. The quantified self is one dimension of the bigger trend to integrate and apply a variety of personal information streams including big health data (genome, transcriptome, environmentome, diseasome), quantified self data streams (biosensor, fitness, sleep, food, mood, heart rate, glucose tracking, etc.), traditional data streams (personal and family health history, prescription history) and IOT (Internet of things) activity data streams (smart home, smart car, environmental sensors, community data). This talk looks at how personal data and group data are becoming big data as individuals and communities share, collaborate, and work with large personalized data sets using novel discovery methods such as anomaly detection and exception reporting, longitudinal baseline analysis, episodic triggers, and hierarchical machine learning.
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...Amit Sheth
Amit Sheth's Keynote at Semantic Web Technologies for Science and Engineering Workshop (held in conjunction with ISWC2003), Sanibel Island, FL, October 20, 2003.
Social computing tools for collaboration: perceptions of opportunity and riskHazel Hall
This document summarizes a presentation by Dr. Hazel Hall on the perceptions of opportunity and risk regarding social computing tools for collaboration. The presentation focused on establishing the main opportunities and risks of social computing tools as perceived by information and knowledge management professionals. It discussed research conducted on the scale of implementation of these tools in organizations, as well as attitudes toward the tools. Overall, the information and knowledge management community recognized the value of social computing tools but cited the biggest risk as poor implementation management failing to capitalize on opportunities.
Building a community of edupreneurs in learning technologies. Keynote presentation at Future Learning Lab, University of Adger, Kristiansand, Norway by Martha G Russell, Executive Director, mediaX at Stanford University.
This is a version of series of talks given at NCSA-UIUC's director seminar, IBM Almaden, HP Labs, DERI-Galway, City Univ of Dublin, and KMI-Open University during Aug-Oct 2010 (replaces earlier keynote version). It deals with couple of items of the vision outlined at http://bit.ly/4ynB7A
A video of this presentation: http://www.ncsa.illinois.edu/News/Video/2010/sheth.html
Link to this talk as http://bit.ly/CHE-talk
One application, multiple platforms. This application will enable the users to control their home appliances and smart devices from their mobile or tablet, and also share information and communicate with their friends and family through this application. Based on the electricity usage, each users will receive a social score and will be ranked among their friends and their neighbors, who are using the same platforms anonymously.
Online Communities in Citizen Science & BirdCamsAndrea Wiggins
This document discusses online citizen science communities and bird cams. It describes how citizen science involves members of the public engaging in real-world scientific research through crowdsourcing and collaboration. It then focuses on how bird cams, which livestream nests and feeders, have emerged as online communities where people can observe and discuss bird activity in real-time. While most viewers never chat, many read discussions. Bird cams present unexpected outcomes like self-organizing social groups and emotional engagement. Sustainability relies on donations, merchandise, and fundraising by chat participants.
The machine in the ghost: a socio-technical perspective...Cliff Lampe
This document discusses sociotechnical systems and the challenges of collaboration between researchers studying these systems and practitioners. It defines sociotechnical systems as the interrelation between technological and human systems. It argues that truly understanding these systems requires combining the theories and techniques of multiple fields including social science, computer science, and engaging with practitioners. However, bringing these different groups together is difficult due to differences in culture, goals, and incentives between academics and practitioners. It provides some strategies for encouraging collaboration, such as phenomena-based research, workshops, funding incentives, and mixed academic/practitioner events and project partnerships.
The document discusses challenges and opportunities for data management in citizen science projects. It identifies developing data management plans, establishing data policies, developing supporting cyberinfrastructure or technology platforms, and ensuring data quality as key issues. A survey of citizen science projects found the greatest dissatisfaction with processes for sharing data and presenting results, but that data management planning was better than average. Top priorities for improvement included tools for analyzing, visualizing, documenting and describing data, as well as training. The presentation calls on USGS to lead by example in promoting data sharing, developing clear and reusable policies and platforms, and demonstrating best practices for data quality.
This dissertation explores the social context and influences on the early adoption and use of mobile devices. It examines how social influences can help explain the adoption and use of smartphones. The research questions focus on the extent that social influences and competing forces can explain early adoption and use. Four articles are presented that use case studies and social network approaches to analyze how social networks, norms, and opinion leaders shape individual adoption decisions. Conceptual frameworks are developed to analyze adoption through multilevel research examining the interplay between individual and group levels.
The document lists different animals including cat, mouse, dog, horse, and bird. It then repeats listing cat, dog, mouse, bird, and horse. The document ends mentioning exercise and specifically listing bird and horse again along with mentioning cat and mouse.
Reality mining aims to map an organization's cognitive infrastructure by capturing detailed data on human networks using sensors. It analyzes conversations, topics, locations and relationships between individuals to infer expertise, social networks and how communication may change. This could help with applications like knowledge management, team formation and understanding global influences in an organization. However, it also raises privacy concerns that would need to be addressed.
Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Inte...Amit Sheth
Ora Lassila and Amit Sheth, "Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Interoperability", Invited Talk at ONC-HHS Invitational Workshop on Next Generation Interoperability for Health, Washington DC, January 19-20, 2011.
Knowledge Will Propel Machine Understanding of Big DataAmit Sheth
1) Amit Sheth presented on how knowledge can help machines better understand big data.
2) He discussed challenges like understanding implicit entities, analyzing drug abuse forums, and understanding city traffic using sensors and text.
3) Sheth argued that knowledge graphs and ontologies can help interpret diverse data types and provide contextual understanding to help solve real-world problems.
Enabling Case-Based Reasoning on the Web of Data (How to create a Web of Exp...Benjamin Heitmann
Presentation at the "Reasoning from experiences on the Web" workshop (WebCBR 2010) at the International Conference on Case Based Reasoning 2010.
Abstract:
While Case-based reasoning (CBR) has successfully been deployed on the Web, its data models are typically inconsistent with existing information infrastructure and standards. In this paper, we examine how
CBR can operate on the emerging Web of Data, with mutual benefits. The
expense of knowledge engineering and curating a case base can be reduced
by using Linked Data from the Web of Data. While Linked Data provides experiential data from many different domains, it also contains inconsistencies, missing data and noise which provide challenges for logic-based reasoning. CBR is well suited to provide alternative and robust reasoning approaches. We introduce (i) a lightweight CBR vocabulary which is
suited for the open ecosystem of the emerging Web of Data, and provide
(ii) a detailed example of a case base using data from multiple sources. We
propose that for the first time the Web of Data provides data and a real
context for open CBR systems.
This is a brief a brief review of current multi-disciplinary and collaborative projects at Kno.e.sis led by Prof. Amit Sheth. They cover research in big social data, IoT, semantic web, semantic sensor web, health informatics, personalized digital health, social data for social good, smart city, crisis informatics, digital data for material genome initiative, etc. Dec 2015 edition.
This tutorial presents tools and techniques for effectively utilizing the Internet of Things (IoT) for building advanced applications, including the Physical-Cyber-Social (PCS) systems. The issues and challenges related to IoT, semantic data modelling, annotation, knowledge representation (e.g. modelling for constrained environments, complexity issues and time/location dependency of data), integration, analy- sis, and reasoning will be discussed. The tutorial will de- scribe recent developments on creating annotation models and semantic description frameworks for IoT data (e.g. such as W3C Semantic Sensor Network ontology). A review of enabling technologies and common scenarios for IoT applications from the data and knowledge engineering point of view will be discussed. Information processing, reasoning, and knowledge extraction, along with existing solutions re- lated to these topics will be presented. The tutorial summarizes state-of-the-art research and developments on PCS systems, IoT related ontology development, linked data, do- main knowledge integration and management, querying large- scale IoT data, and AI applications for automated knowledge extraction from real world data.
Related: Semantic Sensor Web: http://knoesis.org/projects/ssw
Physical-Cyber-Social Computing: http://wiki.knoesis.org/index.php/PCS
This document summarizes four knowledge management processes used by Defence Research & Development Canada (DRDC): monitoring the environment, producing intelligence, mobilizing knowledge, and integration. It describes DRDC's environmental monitoring process which involves acquiring external data through 10 pathways, including monitoring cyberspace, media, research, literature, conferences, communities of practice, soliciting practitioners, reviewing experiences, individual discovery, and receiving unsolicited information. Each pathway requires different support services to filter and analyze the acquired information and detect patterns of interest.
Quantified Self Ideology: Personal Data becomes Big DataMelanie Swan
A key contemporary trend emerging in big data science is the quantified self: individuals engaged in the deliberate self-tracking of any kind of biological, physical, behavioral, or transactional information, as n=1 individuals or in groups. The quantified self is one dimension of the bigger trend to integrate and apply a variety of personal information streams including big health data (genome, transcriptome, environmentome, diseasome), quantified self data streams (biosensor, fitness, sleep, food, mood, heart rate, glucose tracking, etc.), traditional data streams (personal and family health history, prescription history) and IOT (Internet of things) activity data streams (smart home, smart car, environmental sensors, community data). This talk looks at how personal data and group data are becoming big data as individuals and communities share, collaborate, and work with large personalized data sets using novel discovery methods such as anomaly detection and exception reporting, longitudinal baseline analysis, episodic triggers, and hierarchical machine learning.
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...Amit Sheth
Amit Sheth's Keynote at Semantic Web Technologies for Science and Engineering Workshop (held in conjunction with ISWC2003), Sanibel Island, FL, October 20, 2003.
Social computing tools for collaboration: perceptions of opportunity and riskHazel Hall
This document summarizes a presentation by Dr. Hazel Hall on the perceptions of opportunity and risk regarding social computing tools for collaboration. The presentation focused on establishing the main opportunities and risks of social computing tools as perceived by information and knowledge management professionals. It discussed research conducted on the scale of implementation of these tools in organizations, as well as attitudes toward the tools. Overall, the information and knowledge management community recognized the value of social computing tools but cited the biggest risk as poor implementation management failing to capitalize on opportunities.
Building a community of edupreneurs in learning technologies. Keynote presentation at Future Learning Lab, University of Adger, Kristiansand, Norway by Martha G Russell, Executive Director, mediaX at Stanford University.
This is a version of series of talks given at NCSA-UIUC's director seminar, IBM Almaden, HP Labs, DERI-Galway, City Univ of Dublin, and KMI-Open University during Aug-Oct 2010 (replaces earlier keynote version). It deals with couple of items of the vision outlined at http://bit.ly/4ynB7A
A video of this presentation: http://www.ncsa.illinois.edu/News/Video/2010/sheth.html
Link to this talk as http://bit.ly/CHE-talk
One application, multiple platforms. This application will enable the users to control their home appliances and smart devices from their mobile or tablet, and also share information and communicate with their friends and family through this application. Based on the electricity usage, each users will receive a social score and will be ranked among their friends and their neighbors, who are using the same platforms anonymously.
Online Communities in Citizen Science & BirdCamsAndrea Wiggins
This document discusses online citizen science communities and bird cams. It describes how citizen science involves members of the public engaging in real-world scientific research through crowdsourcing and collaboration. It then focuses on how bird cams, which livestream nests and feeders, have emerged as online communities where people can observe and discuss bird activity in real-time. While most viewers never chat, many read discussions. Bird cams present unexpected outcomes like self-organizing social groups and emotional engagement. Sustainability relies on donations, merchandise, and fundraising by chat participants.
The machine in the ghost: a socio-technical perspective...Cliff Lampe
This document discusses sociotechnical systems and the challenges of collaboration between researchers studying these systems and practitioners. It defines sociotechnical systems as the interrelation between technological and human systems. It argues that truly understanding these systems requires combining the theories and techniques of multiple fields including social science, computer science, and engaging with practitioners. However, bringing these different groups together is difficult due to differences in culture, goals, and incentives between academics and practitioners. It provides some strategies for encouraging collaboration, such as phenomena-based research, workshops, funding incentives, and mixed academic/practitioner events and project partnerships.
The document discusses challenges and opportunities for data management in citizen science projects. It identifies developing data management plans, establishing data policies, developing supporting cyberinfrastructure or technology platforms, and ensuring data quality as key issues. A survey of citizen science projects found the greatest dissatisfaction with processes for sharing data and presenting results, but that data management planning was better than average. Top priorities for improvement included tools for analyzing, visualizing, documenting and describing data, as well as training. The presentation calls on USGS to lead by example in promoting data sharing, developing clear and reusable policies and platforms, and demonstrating best practices for data quality.
This dissertation explores the social context and influences on the early adoption and use of mobile devices. It examines how social influences can help explain the adoption and use of smartphones. The research questions focus on the extent that social influences and competing forces can explain early adoption and use. Four articles are presented that use case studies and social network approaches to analyze how social networks, norms, and opinion leaders shape individual adoption decisions. Conceptual frameworks are developed to analyze adoption through multilevel research examining the interplay between individual and group levels.
The document lists different animals including cat, mouse, dog, horse, and bird. It then repeats listing cat, dog, mouse, bird, and horse. The document ends mentioning exercise and specifically listing bird and horse again along with mentioning cat and mouse.
Community Engagement towards HIV Prevention for Women Rouzeh Eghtessadi
Community engagement is essential for HIV prevention research, policy, and practice. It enhances understanding and support for research, facilitates ethical recruitment, and prepares communities for new technologies. Community is defined as groups infected and affected by HIV. Effective engagement includes mapping communities, participatory dialogue at all stages, building relationships and capacity, and disseminating learning. Tools include defining spheres of influence, advisory boards, information sessions, and participatory research. Future approaches should strengthen communities' roles in informing research, implementing technologies, and sharing best practices through two-way communication platforms.
The UPF-Hungary 2011 Activity report summarizes their participation in several European conferences in locations like London, Geneva, Oslo, Berlin, and Vienna. It describes their involvement in interreligious programs through visiting Buddhist temples and inaugurating an interreligious chapel. It also outlines their cultural programs including concerts and exhibitions, as well as community building programs and training sessions. International conferences and meetings were also attended.
Content: Hvad er en konge uden en strategi?Jan Godsk
Content kan stort set aldrig stå alene. Selv det bedste spil eller en Oskar-vindende spillefilm vil fungere mere effektivt som marketing-værktøj, hvis der er bundet andre strategisk gennemtænkt, tiltag i halen på dem.
Dublin is the capital city of Ireland. It is located on the east coast of the island along the River Liffey. Dublin has a population of over 1.3 million people and is a center for culture, education, and commerce in Ireland.
An introduction-to-windows-powershell-1193007253563204-3Louis Kolivas
This document provides an introduction and overview of Windows PowerShell. It discusses what PowerShell is used for, how PowerShell works using verbs and nouns, and how to interact with and "hack" PowerShell to customize it. The document contains an agenda outlining these topics and includes examples of PowerShell commands and scripts.
This document summarizes a webinar on building cross-platform mobile apps with Xamarin.Forms. It discusses advantages of using Xamarin.Forms like shared code, includes over 40 UI elements, layouts and controls, data binding, MVVM architecture, custom renderers and dependency services. It also provides an agenda and case study example. Attendees are informed that any questions can be asked during the session and the recording will be shared afterwards.
Multi-Source Provenance-Aware User Interest Profiling on the Social Semantic WebFabrizio Orlandi
This document discusses improving user interest profiling techniques by leveraging linked data, the provenance of data, and the social semantic web. It aims to address challenges like information isolation across social media sites and the lack of provenance on the web of data. Key research questions focus on how to extract and aggregate user information from social media following linked data principles, the role of provenance for user profiling, and how to use the web of data and semantic technologies to enrich profiles. The work aims to represent user profiles interoperably and adapt profiling algorithms to different social media and data origins.
Closing the Loop - From Citizen Sensing to Citizen ActuationDavid Crowley
The document discusses using citizen sensing and actuation to close the loop in building energy management. It describes an experiment where sensors monitored energy usage in a building and tweets were sent to occupants requesting they check for unused energy consumption and turn things off. This reduced average daily energy usage by 23.86% during the experiment weeks. Open issues discussed include applying this approach more broadly while addressing challenges involving emerging web technologies, human task management, privacy and applicability to critical infrastructure.
WikiSym2012 Deletion Discussions in Wikipedia: Decision Factors and Outcomesjodischneider
This document summarizes a study on deletion discussions in Wikipedia. The study analyzed 72 deletion discussions from a single day to understand the factors that contribute to deletion decisions and their outcomes. It found that four main factors—notability, sources, maintenance, and bias—accounted for 91% of comments and influenced 70% of discussions. Notability was sometimes overridden by other concerns like ensuring comprehensive coverage of a topic. The study aims to help newcomers, debate closers, and readers better understand Wikipedia's criteria for deletion.
The document discusses technology-mediated social participation and outlines the goals and challenges of the Summer Social Webshop. It summarizes that the Webshop aims to (1) clarify national priorities, (2) develop research questions around social participation, and (3) promote novel research methodologies to influence national policy and increase educational opportunities. It also notes key challenges include malicious attacks, privacy violations, lack of trust, and failure to be universally accessible.
EDF2013: Keynote Stefan Decker: Big Data In Ireland - Linked Data and beyondEuropean Data Forum
Keynote of Stefan Decker, Professor for Digital Enterprise & Director of DERI, National University of Ireland, Galway, at the European Data Forum 2013, 9 April 2013 in Dublin, Ireland: Big Data In Ireland - Linked Data and beyond
OBJECTIVES: Translational research focuses on the bench-to-bedside information transfer process — getting the information from researchers into the hands of clinical decision makers. At the same time, researchers who manage international research collaborations could benefit from increased knowledge and awareness of online collaboration tools to support these projects. Our goal was to support both needs through building awareness and skills with online and social media.
METHODS: The Library developed a curricula targeted specifically to academic researchers focusing on collaboration technologies and online tools to support the research process. The curricula will provide instruction at three levels: gateway, bridge, and mastery tools. The goal of Level One is to persuade researchers of the utility of online social tools. To develop the program, input was solicited from researchers identified as leaders in this area as well as focus groups of students to discover which tools are already being used.
RESULTS: Training is being provided on those tools identified as most likely to engage researchers (Google Docs, Skype, online scheduling, Adobe Connect, citation sharing tools). The curricula is being delivered as workshops duplicated as podcasts and in other online media.
CONCLUSIONS: Online and social media are practical tools for supporting distance collaborations relatively inexpensively while offering the added benefit of placing selected information in online spaces that facilitate discovery and discussion with clinical care providers, thus supporting the fundamental research processes at the same time as promoting bench-to-bedside information transfer.
Online resources and Information and Communication Technology (ICT) have revolutionized the research process. They provide access to vast amounts of information, enable collaboration, and facilitate the dissemination of research findings. In this presentation, we will explore a variety of websites and tools that can aid researchers in their quest for knowledge.
Online resources and Information and Communication Technology (ICT) have revolutionized the research process. They provide access to vast amounts of information, enable collaboration, and facilitate the dissemination of research findings. In this presentation, we will explore a variety of websites and tools that can aid researchers in their quest for knowledge.
This approach has become increasingly important in today's digital age due to the abundance of information available online and the capabilities of technology. Let's explore on the key aspects of online resources and ICT are used in research
This document discusses social networks, social media, and their relationship to trading. It defines social media as web-based platforms that allow people to interact online through user-generated content. Social networks are described as relationships and information flows between entities within a network. The document outlines why social media matters for businesses and trading due to its interactive nature, speed of information sharing, and ability to amplify messages. It then reviews several academic studies that found correlations between social media content, sentiment and stock market movements. The document concludes by discussing tools for sentiment analysis, machine readable news, and corporate social media monitoring.
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.
Turning social disputes into knowledge representations DERI reading group 201...jodischneider
A reading group presentation about Turning social disputes into knowledge representations, based primarily on two papers:
Toni and Torroni. Bottom-up Argumentation. In: First International Workshop on the Theory and Applications of Formal Argumentation 2011 (TAFA), 16-22 July, 2011, Barcelona, Spain. http://www.doc.ic.ac.uk/~ft/PAPERS/tafaPT.pdf
Benn, Buckingham Shum, Domingue, and Mancini. Ontological Foundations for Scholarly Debate Mapping Technology. In: 2nd International Conference on Computational Models of Argument (COMMA '08), 28-30 May, 2008, Toulouse, France. http://oro.open.ac.uk/11939/
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
AIIM New England Social Networking PresentationDoug Cornelius
This document discusses social networking for business use. It defines social networks and their value in allowing analysis of relationships rather than just individual attributes. It then covers various aspects of implementing social networking in a business context, including available functionality, ensuring a culture of trust among users, integrating different systems rather than having information silos, establishing appropriate governance, and the infrastructure required. Recommendations focus on taking an iterative approach and balancing controls with allowing open sharing of information.
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
The document discusses three potential divides that may emerge in big data research: 1) between developed and developing countries, 2) between academic and commercial sector researchers, and 3) between researchers with strong computational skills versus those with less computational skills. It provides examples of methods used in different country/region contexts and notes a critique of big data research around issues like changing definitions of knowledge, misleading claims of objectivity/accuracy, and new digital divides around data access.
This document discusses the future of social health and knowledge management via social media. It addresses challenges for connecting people, finding and sharing health information, and ensuring interoperability across systems. The document suggests that future health information environments will need to be open, collaborative platforms that can adapt to changing needs and behaviors. Governance will be dispersed across many individual actors interacting in parallel. The overall system behavior will emerge from decentralized decisions rather than centralized control.
1. Digital Enterprise Research Institute www.deri.ie
Twitter and research impact
Marie Boran
Copyright 2011 Digital Enterprise Research Institute. All rights reserved.
Enabling networked knowledge
2. Digital Enterprise Research Institute www.deri.ie
A review of: Eysenbach, G., 2011. Can Tweets Predict
Citations? Metrics of Social Impact Based on Twitter and
Correlation with Traditional Metrics of Scientific Impact.
Journal of Medical Internet Research, 13(4), p.e12.
Enabling networked knowledge
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3. A little background…
Digital Enterprise Research Institute www.deri.ie
Impact Factor as a
measure of scientific
impact:
The Good, the Bad and the
Ugly.
Enabling networked knowledge
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4. Sick of Impact Factor?
Digital Enterprise Research Institute www.deri.ie
Imperial College London researcher Stephen Curry: „the
stupid, it burns.”
http://occamstypewriter.org/scurry/2012/08/13/sick-of-
impact-factors/
“dependency on a valuation system that is
grounded in falsity.”
“we need to find ways to attach to each piece of work the
value that the scientific community places on it though
use and citation.”
Enabling networked knowledge
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5. What are altmetrics?
Digital Enterprise Research Institute www.deri.ie
Alternative web-based social metrics
Scientometrics from online social activity centred around
scholar‟s work
Self-publishing: blogging, uploading, tweeting, sharing
Impact measured via: articles viewed, shared, downloaded,
„retweeted‟, „liked‟, etc.
“Scholars are moving their everyday work to the web.
Online reference managers Zotero and Mendeley each
claim to store over 40 million articles (making them
substantially larger than PubMed); as many as a third of
scholars are on Twitter, and a growing number tend
scholarly blogs. These new forms reflect and transmit
scholarly impact […] That hallway conversation about a
recent finding has moved to blogs and social networks–
now, we can listen in.
- Altmetrics.org manifesto A ”
From: altmetrics.org/manifesto
Enabling networked knowledge
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6. Eysenbach (2011)
Digital Enterprise Research Institute www.deri.ie
Study objectives:
Feasibility of measuring social
impact/public attention to scholarly
articles through social media
Relation between dynamics, timing
of tweets about a scholarly article
(aka tweetations) and journal
citations
Evaluating accuracy of resulting
metrics in predicting highly cited
articles
Journal of Medical Internet Research top articles, ranked by
tweets
Enabling networked knowledge
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7. Methods
Digital Enterprise Research Institute www.deri.ie
Journal of Medical Internet Research
Highly-cited, open access journal
Articles published between issues 3/2009 and 2/2010
Thomson Reuters 3-year impact factor of 4.7
Citation counts (SCOPUS and Google Scholar)
Twitter citations or „tweetation” – must mention journal article
URL
Only tweets with URLs linking directly to the journal article are
captured. Does not count links to blogs or newspaper articles
mentioning research.
Note: Eysenbach is the editor-in-chief and publisher of JMIR
Enabling networked knowledge
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8. Methods (cont‟d)
Digital Enterprise Research Institute www.deri.ie
Tweets captured: all sent and archived
by JMIR between July 24, 2008 and
November 20, 2011
Classification: “highly-cited” articles -
top 25th percentile of each issue (by
citation counts)
“highly-tweeted” - top 25th percentile
(ranked by tweetations)
Adjusted for increasing popularity of
Twitter over time & older articles have
higher citations.
Enabling networked knowledge
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9. Results
Digital Enterprise Research Institute www.deri.ie
55 articles
4208 tweetations
Average 14 tweetations per article
Majority of tweets published on or day
after article published (see graph)
First 30 days: “network propagation
phase”
30+: “sporadic tweetation phase”
Observed 80/20 rule (Pareto principle)
Highly tweeted articles 11 times more
likely to be highly cited than less-tweeted
articles
75% of highly tweeted articles were
highly cited in comparison to 7% of less-
tweeted articles
Enabling networked knowledge
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10. Results (cont‟d)
Digital Enterprise Research Institute www.deri.ie
Citation and tweetation patterns
Scopus and Google Scholar citations tested for agreement
Eysenbach observed “distribution […] typically observed for citations”
Enabling networked knowledge
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11. Findings
Digital Enterprise Research Institute www.deri.ie
First systematic, prospective, longitudinal article and journal-level
investigation of how mention (citations or tweetations) of scholarly
articles in social media accumulate over time
First study correlating altmetrics to citations
Online buzz around articles is measurable
Tweets are “surprisingly accurate” predictors of future journal
citations
Enabling networked knowledge
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12. Limitations
Digital Enterprise Research Institute www.deri.ie
Via Scienceblogs.com
Complementary, *not* a replacement for Impact Factor
“Tweetations” as buzz, attentiveness, social impact
Enabling networked knowledge
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13. Conclusions
Digital Enterprise Research Institute www.deri.ie
Proposes “twimpact factor” (twn) as metric of impact in social media, where
n is cumulative number of tweetations within n days after publication
“The cumulative number of tweetations by day 7 (perhaps as early as day
3), could be used as a diagnostic test to predict highly cited articles.”
Tweetations as proxies for social impact of scientific research
Can be applied to other social media and non-scholarly articles to measure
issue impact on social media user population
+ =
Twitter + metrics = wider perspective on research impact
Enabling networked knowledge
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14. Related research
Digital Enterprise Research Institute www.deri.ie
• Priem, J. & Costello, K.L., 2010. How and
why scholars cite on Twitter. Proceedings
of the 73rd ASIST Annual Meeting, 47(1),
p.1-4.
• Priem, J. & Hemminger, B.M., 2010.
Scientometrics 2.0: Toward new metrics of
scholarly impact on the social Web. First
Monday, 15(7)
Enabling networked knowledge
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Designed by Garfield to help research libraries choose journal subscriptions but has come into much criticism in recent years due to its perceived limitations and loopholes. Authors citing themselves to boost citation rate, cross-citation where journals purposely cite papers from the other to boost overall impact factor of both journals. If detected these journals are suspended. Has been variously called wrong or a “mis-measure” or as Imperial College London researcher Stephen Curry: “the stupid, it burns.”
Eysenbach’s study looks at one particular platform – Twitter – and is concerned with the correlation between citation of scholarly articles on this platform and traditional metrics of citation in peer-reviewed journals. He doesn’t deal with metrics outside article-level such as Slideshare views, Likes, blog entries etc.
roughly 80% of the effects come from 20% of the causes
Left: Zipf plot for JMIR articles 3/2000-12/2009 (n=405), with number of citations (y-axis) plotted against the ranked articles. Right: Zipf plot showing the number of tweetationsor Twitter citations in the first week (tw7) to all JMIR articles (n=206) published between April 3 2009 and nov 15 2011 plotted against ranked articles. Eg top tweeted article for 97 tweetations, the 10th article for 43 tweetations, the 102th ranked got 9 tweetations.
should be primarily seen as metrics for social impact (buzz, attentiveness, or popularity) and as a tool for researchers, journal editors, journalists, and the general public to filter and identify hot topics.