the practical reuse of social media data and how it can create better user experience. Combining Google’s Social Graph API with open data sources like RSS and Microformats to provide a wealth information about your users.
With some of the newer HTML5 API’s it is now possible to redesign how your web pages interact with the desktop. Web pages are too often little islands that fail to interact well with the wider user interface of our devices. This talk will explain the new Drag/Drop and File APIs, demonstrating how to make web pages more equal in the world of applications.
the practical reuse of social media data and how it can create better user experience. Combining Google’s Social Graph API with open data sources like RSS and Microformats to provide a wealth information about your users.
With some of the newer HTML5 API’s it is now possible to redesign how your web pages interact with the desktop. Web pages are too often little islands that fail to interact well with the wider user interface of our devices. This talk will explain the new Drag/Drop and File APIs, demonstrating how to make web pages more equal in the world of applications.
A short overview of the Terms of Service you agree to when using Google Search. Created to meet the requirements of the NET303 unit at Curtin University.
Living in the Cloud: Hosting Data & Apps Using the Google InfrastructurePamela Fox
In the modern web, the user rules. Nearly every successful web app has to worry about scaling to an exponentially growing user base and giving those users multiple ways of interacting with their data. Pamela Fox, Maps API Support Engineer & Developer advocate, provides an overview of two technologies - Google App Engine and the Google Data APIs - that aim to make web development and data portability easier.
Living in the Cloud: Hosting Data & Apps Using the Google Infrastructureguest517f2f
In the modern web, the user rules. Nearly every successful web app has to worry about scaling to an exponentially growing user base and giving those users multiple ways of interacting with their data. Pamela Fox, Maps API Support Engineer & Developer advocate, provides an overview of two technologies - Google App Engine and the Google Data APIs - that aim to make web development and data portability easier.
Social Semantic Web on Facebook Open Graph protocol and Twitter AnnotationsMyungjin Lee
This Presentation show what the Social Semantic Web is and how Facebook Open Graph protocol and Twitter Annotations colligate with the Social Semantic Web.
Living in the Cloud: Hosting Data & Apps Using the Google Infrastructureguest517f2f
In the modern web, the user rules. Nearly every successful web app has to worry about scaling to an exponentially growing user base and giving those users multiple ways of interacting with their data. This talk will provide an overview of two technologies that aim to make web development and data portability easier: Google App Engine and the Google Data APIs.
This talk was presented by Pamela Fox, who works on the Google Developer Relations team as the Maps API Support Engineer.
A short overview of the Terms of Service you agree to when using Google Search. Created to meet the requirements of the NET303 unit at Curtin University.
Living in the Cloud: Hosting Data & Apps Using the Google InfrastructurePamela Fox
In the modern web, the user rules. Nearly every successful web app has to worry about scaling to an exponentially growing user base and giving those users multiple ways of interacting with their data. Pamela Fox, Maps API Support Engineer & Developer advocate, provides an overview of two technologies - Google App Engine and the Google Data APIs - that aim to make web development and data portability easier.
Living in the Cloud: Hosting Data & Apps Using the Google Infrastructureguest517f2f
In the modern web, the user rules. Nearly every successful web app has to worry about scaling to an exponentially growing user base and giving those users multiple ways of interacting with their data. Pamela Fox, Maps API Support Engineer & Developer advocate, provides an overview of two technologies - Google App Engine and the Google Data APIs - that aim to make web development and data portability easier.
Social Semantic Web on Facebook Open Graph protocol and Twitter AnnotationsMyungjin Lee
This Presentation show what the Social Semantic Web is and how Facebook Open Graph protocol and Twitter Annotations colligate with the Social Semantic Web.
Living in the Cloud: Hosting Data & Apps Using the Google Infrastructureguest517f2f
In the modern web, the user rules. Nearly every successful web app has to worry about scaling to an exponentially growing user base and giving those users multiple ways of interacting with their data. This talk will provide an overview of two technologies that aim to make web development and data portability easier: Google App Engine and the Google Data APIs.
This talk was presented by Pamela Fox, who works on the Google Developer Relations team as the Maps API Support Engineer.
A web-based editing tool (developed with GWT and Ext-GWT) for semantic annotation of RESTful web services, developed during my 4 months training at KMI - Open University - Milton Keynes - UK.
Illuminated Hacks -- Where 2.0 101 Tutorialmikel_maron
Some of my favorite hacks
for the pleasure of your hacking sensibility
with the hopeful outcome of illuminating
best practices of putting your website on the geoweb
and hinting at the means
to get exactly what you need.
cause I likes the hacks.
hacks are rad.
From User Needs to Community Health: Mining User Behaviour to Analyse Online ...Matthew Rowe
Invited keynote talk at the 1st Workshop of Quality, Motivation and Coordination of Open Collaboration @ the International Conference on Social Informatics 2013
Attention Economics in Social Web SystemsMatthew Rowe
Slides from a Highwire Digital Futures Seminar that I gave at Lancaster University on 25th October 2012 covering Attention Economics in Social Web Systems
Using Behaviour Analysis to Detect Cultural Aspects in Social Web SystemsMatthew Rowe
Presented at:
-Aston Business School, Birmingham, UK. 2011
-Keynote presentation at Detecting and Exploiting Cultural Diversity on the Social Web Workshop, 20th Annual Conference on Information and Knowledge Management 2011
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Integrating and Interpreting Social Data from Heterogeneous Sources
1. Integrating and Interpreting Social Data from Heterogeneous Sources Matthew Rowe Organisations, Information and Knowledge Group University of Sheffield SuvodeepMazumdar Department of Information Studies University of Sheffield
2. Outline Information overload Increase in social data publication Interlinking social data Metadata Generation Integrating Social Data Application: Interpreting Social Data Cumbrian Floods Use Case Interacting with Social Data Conclusions
3. Information Overload Masses of social data are published every day E.g. 50 million tweets (600 per second) http://blog.twitter.com 22million Facebook users in the UK http://www.clickymedia.co.uk/2009/10/uk-facebook-user-statistics-october-2009/ Too much information to deal with! Social data is multi-faceted: Provenance Topic Geo Trend services (e.g. trendistic, blogpulse): Focus on majority consensus Need to listen in to a specific topic Concentrate on a single source/platform Do not consider geo facet
4.
5.
6. Interlinking Social Data Consider multi-faceted nature of social data: Allows fine-grained analysis Show geo-localised social data Relevant past social data Solution: Interlink social data from heterogeneous sources Use semantics! Consistent data interpretation
7. Metadata Generation Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post and itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance
8. Metadata Generation <photo id="949406913" media="photo"> <owner nsid="54948696@N00”/> <title>DSC00171.JPG</title> <description></description> <dates posted="1205398307" taken="2009-01-09 09:16:31" lastupdate="1257421561" /> <tags> <tag id="24539622-2330113101-400" author="54948696@N00" raw="arctic">arctic</tag> <tag id="24539622-2330113101-401" author="54948696@N00" raw="monkeys">monkeys</tag> </tags> <location latitude="53.4813" longitude="-2.2392" place_id="R8vDw_abBpSzUA"> <locality place_id="R8vDw_abBpSzUA" woeid="27872">Manchester</locality> <region place_id="pn4MsiGbBZlXeplyXg" woeid="24554868">England</region> <country place_id="DevLebebApj4RVbtaQ" woeid="23424975">United Kingdom</country> </location> </photo> Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post and itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status>
9. Metadata Generation Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post and itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status>
10. Metadata Generation <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status> Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post/itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <http://twitter.com/mattroweshow/9774519667> rdf:typesioc:Post ; rdf:typeitr:LocalizedResource ;
11. Metadata Generation <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status> Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post/itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <http://twitter.com/mattroweshow/9774519667> rdf:typesioc:Post ; rdf:typeitr:LocalizedResource ; sioc:content "Writing up our Geovation work for #lupas2010." ; dcterms:subject "lupas2010" ;
12. Metadata Generation <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status> Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post/itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <http://twitter.com/mattroweshow/9774519667> rdf:typesioc:Post ; rdf:typeitr:LocalizedResource ; sioc:content "Writing up our Geovation work for #lupas2010." ; dcterms:subject "lupas2010" ; itr:has_Localization _:a2 . _:a2 rdf:typegml:Geometry ; gml:pos "53.3833,-1.4722" .
13. Metadata Generation <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status> Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post/itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <http://twitter.com/mattroweshow/9774519667> rdf:typesioc:Post ; rdf:typeitr:LocalizedResource ; sioc:content "Writing up our Geovation work for #lupas2010." ; dcterms:subject "lupas2010" ; dcterms:created "2010-2-28 12:22:47.0" ; itr:has_Localization _:a2 . _:a2 rdf:typegml:Geometry ; gml:pos "53.3833,-1.4722" .
14. Metadata Generation <status> <created_at>Sun Feb 28 12:22:47 +0000 2010</created_at> <id>9774519667</id> <text>Writing up our Geovation work for #lupas2010.</text> <truncated>false</truncated> <in_reply_to_status_id></in_reply_to_status_id> <in_reply_to_user_id></in_reply_to_user_id> <favorited>false</favorited> <in_reply_to_screen_name></in_reply_to_screen_name> <geo xmlns:georss="http://www.georss.org/georss"> <georss:point>53.3833,-1.4722</georss:point> </geo> </status> Web 2.0 platforms return data using: Proprietary formats; Heterogeneous data schemas Need to link data together from disparate sources A social data fragment = a single piece of social data E.g. A tweet, an image, a video Lift each social data fragment to RDF: Create an instance of sioc:Post/itr:LocalizedResource Assign it a URI Assign the content to the instance (topic) Use hashtags of the microblog Create an instance of gml:Geometry (geo) Capture geo facet Assign timestamp of fragment creation (provenance) Using dc:created Assign the fragment to its owner (provenance) Create foaf:Person instance <http://twitter.com/mattroweshow> rdf:typefoaf:Person ; rdf:typeitr:LocalizedResource ; foaf:name "Matthew Rowe" ; foaf:homepage <http://www.dcs.shef.ac.uk/~mrowe> ; <http://twitter.com/mattroweshow/9774519667> rdf:typesioc:Post ; rdf:typeitr:LocalizedResource ; sioc:content "Writing up our Geovation work for #lupas2010." ; dcterms:subject "lupas2010" ; dcterms:created "2010-2-28 12:22:47.0" ; sioc:hasCreator <http://twitter.com/mattroweshow> ; itr:has_Localization _:a2 . _:a2 rdf:typegml:Geometry ; gml:pos "53.3833,-1.4722" .
15. Integrated Social Data Triplify social data from multiple platforms Flickr XML response -> RDF Picassa XML response -> RDF Use common semantics Can perform SPARQL queries PREFIX dcterms:<http://purl.org/dc/terms> SELECT ?item WHERE { ?item dcterms:subject "iranelections" . ?item dcterms:created ?date } ORDER BY DESC(?date) PREFIX dcterms:<http://purl.org/dc/terms> PREFIX itr:<http://www.dcs.shef.ac.uk/~gregoire/interaction/ns#> PREFIX gml:<http://www.opengis.net/gml/> SELECT DISTINCT ?post ?tag WHERE { ?post dcterms:subject ?tag . ?post itr:has_Localization ?geo . ?geo gml:pos "53.4813,-2.2392" }
16. Interpreting Social Data Cumbrian Use Case UK region suffered worst floods in centuries Observe the effects in social data Rise in publication Fine-grained geocoded social data Dataset: Microblogs from 200 Cumbrian Twitter users Published during 2009 3513 microblogs Produced 475,043 triples Images from Flickr taken in Cumbria 6663 images Produced 182,304
17. Interacting with Social Data Built a visualisation application to analyse social data fragments http://www.dcs.shef.ac.uk/~suvodeep/ViziSocial Filter by date Lower slider Fine-grained focus Zoom in Tag cloud Shows fragment topics Window controls tag cloud topics Markers contain number of fragments
18. Conclusions Consistent interpretation of social data Across heterogeneous sources Application Allows analyses of social data To fine-grained detail Utilises multiple facets of social data Requires metadata Issue of scalability Future Work Adapting to real time data acquisition Focussing on South Yorkshire region at present Assess scalability issue