Experience from 10 months of University Linked Data Mathieu d'Aquin
Experience from 10 months of University Linked Data at the Open University:
1. The Open University exposed its public data as linked open data to make the data more discoverable, reusable, and integrated with other datasets.
2. Exposing data as linked data provides benefits like increased transparency, data reuse internally and externally, and reduced costs of managing the university's public data.
3. Other UK universities have since followed the Open University's example in exposing their data as linked data.
LUCERO - Building the Open University Web of Linked DataMathieu d'Aquin
Presentation at the "IET Technology Coffee Morning" at the open university - see http://cloudworks.ac.uk/cloudscape/view/2263
Linked Data at the Open University: From Technical Challenges to Organization...Mathieu d'Aquin
The document discusses how the Knowledge Media Institute at the Open University in the UK has developed a linked data platform, called data.open.ac.uk, to provide open access to various types of data from across the university, including course information, research publications, podcasts, videos, and more. It describes some of the technical and organizational challenges in developing the platform, and highlights how it has enabled new uses of the university's data and inspired innovation both within the university and more broadly in open education.
The document discusses using the Semantic Web as a knowledge base for artificial intelligence applications. It describes how the Semantic Web publishes data on the web in a standardized, linked format. This vast amount of distributed knowledge could be mined by AI in various ways, such as linking data mining to find patterns, using reasoning to analyze and understand raw data, and assessing agreement between ontologies. The Semantic Web represents a large, collaborative base of formally represented knowledge that provides many opportunities for future AI research and applications.
This document discusses linked data and semantic web technologies. It describes Mathieu d'Aquin, a research fellow at the Knowledge Media Institute of the Open University who works on semantic web, linked data, and knowledge technologies. It then provides an overview of key concepts in the semantic web and linked data, including using URIs to identify entities on the web, representing data as graphs using RDF, and linking data across the web. Examples are given of how linked data can be queried and used in applications.
Semantic Web, Linked Data and Education: A Perfect Fit?Mathieu d'Aquin
This document discusses how semantic web technologies like linked data are a perfect fit for education. It provides examples of how the Open University has applied linked data to connect educational resources and data from across the university. Linked data allows for flexibility, accessibility, and the ability to combine and interpret different sources of knowledge. However, challenges remain around representing rich metadata about educational purpose and interpreting resources in an educational context.
Interpreting Data Mining Results with Linked Data for Learning AnalyticsMathieu d'Aquin
Interpreting Data Mining Results with Linked Data for Learning Analytics:Motivation, Case Study and Directions
Presentation at the LAK 2013 conference - 10-04-2013
Linking Universities - A broader look at the application of linked data and s...Mathieu d'Aquin
This document discusses applying linked data and semantic web technologies at universities. It provides examples of how the Open University in the UK publishes various types of data as linked open data, including course information, research publications, podcasts and videos. This enables new applications for resource discovery, social networking and supporting research activities. The document also outlines challenges in linking educational data across institutions and supporting new research methodologies through linked data approaches.
Linked Data for Federation of OER Data & RepositoriesStefan Dietze
An overview over different alternatives and opportunities of using Linked Data principles and datasets for federated access to distributed OER repositories. The talk was held at the ARIADNE/GLOBE convening (http://ariadne-eu.org/content/open-federations-2013-open-knowledge-sharing-education) at LAK 2013, Leuven, Belgium on 8 April 2013
Data4Ed - How data sharing, curation and analytics support innovation in educ...Mathieu d'Aquin
This document discusses how data sharing, curation, and analytics can support innovation in education. It describes how the Open University connects data across different systems like its library catalog, course catalog, and research repositories using semantic technologies and linked data. This integrated data allows for applications like simple maps of university buildings, course recommendations, learning analytics, and personal analytics. Challenges include data heterogeneity, access, and curation. Lessons from smart cities are discussed, like flexible data infrastructures that allow diversity. The goal is supporting the entire learning lifecycle by making rich data available and answering questions like "how can I become X?".
Online Learning and Linked Data: An IntroductionEUCLID project
This document provides an overview of online learning and linked data. It discusses linked data principles, massive open online courses (MOOCs), and using iBooks and SocialLearn for education. Linked data follows principles of using URIs, HTTP URIs, providing useful RDF information, and linking to related resources. MOOCs allow large-scale open access online courses from top universities. iBooks and SocialLearn demonstrate using new media and Web 2.0 technologies to support open educational resources and learning paths.
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the WebStefan Dietze
This document discusses enabling discovery and search of linked data and knowledge graphs. It presents approaches for dataset recommendation including using vocabulary overlap and existing links between datasets. It also discusses profiling datasets to create topic profiles using entity extraction and ranking techniques. These recommendation and profiling approaches aim to help with discovering relevant datasets and entities for a given topic or task.
Analysing & Improving Learning Resources Markup on the WebStefan Dietze
Talk at WWW2017 on LRMI adoption, quality and usage. Full paper here: http://papers.www2017.com.au.s3-website-ap-southeast-2.amazonaws.com/companion/p283.pdf.
Should We Expect a Bang or a Whimper? Will Linked Data Revolutionize Scholar Authoring and Workflow Tools?
Jeff Baer, Senior Director of Product Management, Research Development Services, Proquest
Information Extraction and Linked Data CloudDhaval Thakker
The document discusses Press Association's semantic technology project which aims to generate a knowledge base using information extraction and the Linked Data Cloud. It outlines Press Association's operations and workflow, and how semantic technologies can be used to develop taxonomies, annotate images, and extract entities from captions into an ontology-based knowledge base. The knowledge base can then be populated and interlinked with external datasets from the Linked Data Cloud like DBpedia to provide a comprehensive, semantically-structured source of information.
Retrieval, Crawling and Fusion of Entity-centric Data on the WebStefan Dietze
Stefan Dietze gave a keynote presentation covering three main topics:
1) Challenges in entity retrieval from heterogeneous linked datasets and knowledge graphs due to diversity and lack of standardization.
2) Approaches for enabling discovery and search through dataset recommendation, profiling, and entity retrieval methods that cluster entities to address link sparsity.
3) Going beyond linked data to exploit semantics embedded in web markup, with case studies in data fusion for entity reconciliation and retrieval.
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)Stefan Dietze
This document discusses linking educational data as linked open data. It describes several existing educational linked data projects and datasets, including SmartLink, mEducator, and the Linked Education Graph. The Linked Education Graph integrates datasets from various sources into a single RDF dataset with over 6 million resources and 97 million triples. The document outlines challenges in linking educational data and introduces the LinkedUp project which aims to further adoption of linked data in education through an open data competition and infrastructure to integrate and query educational datasets.
Keynote on software sustainability given at the 2nd Annual Netherlands eScience Symposium, November 2014.
Based on the article
Carole Goble ,
Better Software, Better Research
Issue No.05 - Sept.-Oct. (2014 vol.18)
pp: 4-8
IEEE Computer Society
http://www.computer.org/csdl/mags/ic/2014/05/mic2014050004.pdf
http://doi.ieeecomputersociety.org/10.1109/MIC.2014.88
http://www.software.ac.uk/resources/publications/better-software-better-research
This slideset introduces the LAK Dataset and Challenge, held at the Learning Analytics & Knowledge (LAK) conference in Leuven, Belgium, April 2013. Further information about the dataset and submissions is available at http://ceur-ws.org/Vol-974/ as well as http://www.solaresearch.org/events/lak/lak-data-challenge/.
Linked Data for Knowledge Discovery: IntroductionMathieu d'Aquin
This document summarizes the LD4KD 2015 workshop, which brought together researchers from the linked data and knowledge discovery communities. The workshop included two paper presentations, a demo session, and discussions on opportunities and challenges at the intersection of linked data and knowledge discovery. Some opportunities discussed were using linked data as input for knowledge discovery due to its large, global scale and ability to be extended and enriched. Challenges discussed included dealing with linked data as a graph structure, its distributed and incomplete nature, and ensuring its quality and reducing bias. The goal of the workshop was to further understanding and develop practical tools to address these challenges.
Open science can contribute to AI trustworthiness. This talk is a categorization of scientific data platforms, and a framing of AI trustworthiness with pointers to open science contributions.
Learning Analytics & Linked Data – Opportunities, Challenges, ExamplesStefan Dietze
Linked data provides opportunities for learning analytics and education by serving as a large body of openly available educational resources and data and by promoting interoperability through semantic web principles. It can help integrate isolated educational platforms and facilitate recommender systems. Example applications include integrating biomedical resources and analyzing datasets in a unified "Linked Education Graph". Techniques like entity enrichment through knowledge bases help disambiguate and correlate educational resources.
The document describes the SFX framework for context-sensitive reference linking, which allows a user accessing a citation to be redirected to an appropriate full text or service based on their context. The framework uses an OpenURL standard to pass citation metadata from a link source to a parsing server, which then sends the metadata to a linking server to determine the most relevant services and create dynamic links to them based on the user's access and the available library collections and resources. The goal is to provide context-sensitive services to users based on their access and the cited item metadata rather than relying on pre-computed static links.
A open science presentation focusing on the benefits to be gained and basic practices to follow. This was given on behalf of FOSTER at the Open Science Boos(t)camp event at KU Leuven on 24th October 2014.
Interlinking Standardized OpenStreetMap Data and Citizen Science Data in the ...Werner Leyh
Abstract. The aim of this work is to explore the opportunities offered by
semantic standardization to interlink primary “spatial data” (GI) from “Open-
StreetMap” (OSM) with repositories of the “Linked Open Data Cloud” (LOD).
Research in natural sciences can generate vast amounts of spatial data, where
Wikidata could be considered as the central hub between more detailed natural
science hubs on the spatial semantic web. Wikidata is a world readable and
writable community-driven knowledge base. It offers the opportunity to collaboratively
construct an open access knowledge graph that spans biology,
medicine, and all other domains of knowledge. In this study, we discuss
the opportunities and challenges provided by exploring Wikidata as a central
integration facility by interlink it with OSM, a popular, community driven
collection of free geographic data. This is empowered by the reuse of terms
and properties from commonly understood controlled vocabularies that
represent their respective well-identified knowledge domains.
URL: https://www.springerprofessional.de/en/interlinking-standardized-openstreetmap-data-and-citizen-science/13302088
DOI: https://doi.org/10.1007/978-3-319-60366-7_9
Werner Leyh, Homero Fonseca Filho
University of São Paulo (USP), São Paulo, Brazil
[email protected]
Linking Universities - A broader look at the application of linked data and s...Mathieu d'Aquin
This document discusses applying linked data and semantic web technologies at universities. It provides examples of how the Open University in the UK publishes various types of data as linked open data, including course information, research publications, podcasts and videos. This enables new applications for resource discovery, social networking and supporting research activities. The document also outlines challenges in linking educational data across institutions and supporting new research methodologies through linked data approaches.
Linked Data for Federation of OER Data & RepositoriesStefan Dietze
An overview over different alternatives and opportunities of using Linked Data principles and datasets for federated access to distributed OER repositories. The talk was held at the ARIADNE/GLOBE convening (http://ariadne-eu.org/content/open-federations-2013-open-knowledge-sharing-education) at LAK 2013, Leuven, Belgium on 8 April 2013
Data4Ed - How data sharing, curation and analytics support innovation in educ...Mathieu d'Aquin
This document discusses how data sharing, curation, and analytics can support innovation in education. It describes how the Open University connects data across different systems like its library catalog, course catalog, and research repositories using semantic technologies and linked data. This integrated data allows for applications like simple maps of university buildings, course recommendations, learning analytics, and personal analytics. Challenges include data heterogeneity, access, and curation. Lessons from smart cities are discussed, like flexible data infrastructures that allow diversity. The goal is supporting the entire learning lifecycle by making rich data available and answering questions like "how can I become X?".
Online Learning and Linked Data: An IntroductionEUCLID project
This document provides an overview of online learning and linked data. It discusses linked data principles, massive open online courses (MOOCs), and using iBooks and SocialLearn for education. Linked data follows principles of using URIs, HTTP URIs, providing useful RDF information, and linking to related resources. MOOCs allow large-scale open access online courses from top universities. iBooks and SocialLearn demonstrate using new media and Web 2.0 technologies to support open educational resources and learning paths.
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the WebStefan Dietze
This document discusses enabling discovery and search of linked data and knowledge graphs. It presents approaches for dataset recommendation including using vocabulary overlap and existing links between datasets. It also discusses profiling datasets to create topic profiles using entity extraction and ranking techniques. These recommendation and profiling approaches aim to help with discovering relevant datasets and entities for a given topic or task.
Analysing & Improving Learning Resources Markup on the WebStefan Dietze
Talk at WWW2017 on LRMI adoption, quality and usage. Full paper here: http://papers.www2017.com.au.s3-website-ap-southeast-2.amazonaws.com/companion/p283.pdf.
Should We Expect a Bang or a Whimper? Will Linked Data Revolutionize Scholar Authoring and Workflow Tools?
Jeff Baer, Senior Director of Product Management, Research Development Services, Proquest
Information Extraction and Linked Data CloudDhaval Thakker
The document discusses Press Association's semantic technology project which aims to generate a knowledge base using information extraction and the Linked Data Cloud. It outlines Press Association's operations and workflow, and how semantic technologies can be used to develop taxonomies, annotate images, and extract entities from captions into an ontology-based knowledge base. The knowledge base can then be populated and interlinked with external datasets from the Linked Data Cloud like DBpedia to provide a comprehensive, semantically-structured source of information.
Retrieval, Crawling and Fusion of Entity-centric Data on the WebStefan Dietze
Stefan Dietze gave a keynote presentation covering three main topics:
1) Challenges in entity retrieval from heterogeneous linked datasets and knowledge graphs due to diversity and lack of standardization.
2) Approaches for enabling discovery and search through dataset recommendation, profiling, and entity retrieval methods that cluster entities to address link sparsity.
3) Going beyond linked data to exploit semantics embedded in web markup, with case studies in data fusion for entity reconciliation and retrieval.
Open Educational Data - Datasets and APIs (Athens Green Hackathon 2012)Stefan Dietze
This document discusses linking educational data as linked open data. It describes several existing educational linked data projects and datasets, including SmartLink, mEducator, and the Linked Education Graph. The Linked Education Graph integrates datasets from various sources into a single RDF dataset with over 6 million resources and 97 million triples. The document outlines challenges in linking educational data and introduces the LinkedUp project which aims to further adoption of linked data in education through an open data competition and infrastructure to integrate and query educational datasets.
Keynote on software sustainability given at the 2nd Annual Netherlands eScience Symposium, November 2014.
Based on the article
Carole Goble ,
Better Software, Better Research
Issue No.05 - Sept.-Oct. (2014 vol.18)
pp: 4-8
IEEE Computer Society
http://www.computer.org/csdl/mags/ic/2014/05/mic2014050004.pdf
http://doi.ieeecomputersociety.org/10.1109/MIC.2014.88
http://www.software.ac.uk/resources/publications/better-software-better-research
This slideset introduces the LAK Dataset and Challenge, held at the Learning Analytics & Knowledge (LAK) conference in Leuven, Belgium, April 2013. Further information about the dataset and submissions is available at http://ceur-ws.org/Vol-974/ as well as http://www.solaresearch.org/events/lak/lak-data-challenge/.
Linked Data for Knowledge Discovery: IntroductionMathieu d'Aquin
This document summarizes the LD4KD 2015 workshop, which brought together researchers from the linked data and knowledge discovery communities. The workshop included two paper presentations, a demo session, and discussions on opportunities and challenges at the intersection of linked data and knowledge discovery. Some opportunities discussed were using linked data as input for knowledge discovery due to its large, global scale and ability to be extended and enriched. Challenges discussed included dealing with linked data as a graph structure, its distributed and incomplete nature, and ensuring its quality and reducing bias. The goal of the workshop was to further understanding and develop practical tools to address these challenges.
Open science can contribute to AI trustworthiness. This talk is a categorization of scientific data platforms, and a framing of AI trustworthiness with pointers to open science contributions.
Learning Analytics & Linked Data – Opportunities, Challenges, ExamplesStefan Dietze
Linked data provides opportunities for learning analytics and education by serving as a large body of openly available educational resources and data and by promoting interoperability through semantic web principles. It can help integrate isolated educational platforms and facilitate recommender systems. Example applications include integrating biomedical resources and analyzing datasets in a unified "Linked Education Graph". Techniques like entity enrichment through knowledge bases help disambiguate and correlate educational resources.
The document describes the SFX framework for context-sensitive reference linking, which allows a user accessing a citation to be redirected to an appropriate full text or service based on their context. The framework uses an OpenURL standard to pass citation metadata from a link source to a parsing server, which then sends the metadata to a linking server to determine the most relevant services and create dynamic links to them based on the user's access and the available library collections and resources. The goal is to provide context-sensitive services to users based on their access and the cited item metadata rather than relying on pre-computed static links.
A open science presentation focusing on the benefits to be gained and basic practices to follow. This was given on behalf of FOSTER at the Open Science Boos(t)camp event at KU Leuven on 24th October 2014.
Interlinking Standardized OpenStreetMap Data and Citizen Science Data in the ...Werner Leyh
Abstract. The aim of this work is to explore the opportunities offered by
semantic standardization to interlink primary “spatial data” (GI) from “Open-
StreetMap” (OSM) with repositories of the “Linked Open Data Cloud” (LOD).
Research in natural sciences can generate vast amounts of spatial data, where
Wikidata could be considered as the central hub between more detailed natural
science hubs on the spatial semantic web. Wikidata is a world readable and
writable community-driven knowledge base. It offers the opportunity to collaboratively
construct an open access knowledge graph that spans biology,
medicine, and all other domains of knowledge. In this study, we discuss
the opportunities and challenges provided by exploring Wikidata as a central
integration facility by interlink it with OSM, a popular, community driven
collection of free geographic data. This is empowered by the reuse of terms
and properties from commonly understood controlled vocabularies that
represent their respective well-identified knowledge domains.
URL: https://www.springerprofessional.de/en/interlinking-standardized-openstreetmap-data-and-citizen-science/13302088
DOI: https://doi.org/10.1007/978-3-319-60366-7_9
Werner Leyh, Homero Fonseca Filho
University of São Paulo (USP), São Paulo, Brazil
[email protected]
Linked Data in a University Context: Publication, Applications and Beyond
The Open University (OU) is exposing its data as linked open data to make it more transparent, reusable and discoverable both internally and externally. This includes data about courses, research outputs, library resources and more. By linking its data to other university and external datasets, the OU aims to create new applications and make existing processes more efficient. Other universities in the UK and worldwide are now following the OU's example in publishing institutional data as linked open data.
CrossRef How-to: A Technical Introduction to the Basics of CrossRef, Chuck Ko...Crossref
This presentation has been updated. Please use the following link: http://www.slideshare.net/CrossRef/introduction-to-crossref-webinar
Open (linked) bibliographic data edmund chamberlain (university of cambridge)RDTF-Discovery
The document discusses the Cambridge University Library's decision to expose its bibliographic data as open linked data through the COMET (Cambridge Open METadata) project in order to share data with other institutions, gain insights from analyses of the data, and explore the potential of linked open data for libraries. Some challenges mentioned include choosing an open license, mapping data to RDF vocabularies, and using triplestores to publish and link the data. Future plans include encouraging other libraries to adopt similar approaches and expanding the types of library data exposed through linked open data.
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...Carole Goble
Presented at the FAIR Data in Practice Symposium, 16 may 2023 at BioITWorld Boston. https://www.bio-itworldexpo.com/fair-data. The ELIXIR European research Infrastructure for life science data is an inter-governmental organizations coordinating, integrating and sustaining FAIR data and software resources across its 23 nations. To help advise users, data stewards, project managers and service providers, ELIXIR has developed complementary community-driven, open knowledge resources for guiding FAIR Research Data Management (RDMkit) and providing FAIRification recipes (FAIRCookbook). 150+ people have contributed content so far, including representatives of the pharmaceutical industry.
This document discusses exposing humanities research data as linked open data to make it more accessible and connectable. It describes the benefits of following linked data principles by putting data online in a standard format, making it addressable through URIs, and linking it to other data. As an example, it outlines how the Reading Experience Database was connected to the web of data, allowing relationships to be represented between experiences, people, documents, and other metadata. Overall, the document argues that representing research as linked data provides opportunities for reuse, linking to other resources, and deriving new insights from the connections between data.
Digital Identity is fundamental to collaboration in bioinformatics research and development because it enables attribution, contribution, publication to be recorded and quantified.
However, current models of identity are often obsolete and have problems capturing both small contributions "microattribution" and large contributions "mega-attribution" in Science. Without adequate identity mechanisms, the incentive for collaboration can be reduced, and the utility of collaborative social tools hindered.
Using examples of metabolic pathway analysis with the taverna workbench and myexperiment.org, this talk will illustrate problems and solutions to identifying scientists accurately and effectively in collaborative bioinformatics networks on the Web.
The document discusses the Cambridge University Library's decision to expose its bibliographic data as open linked data through the COMET (Cambridge Open METadata) project. Some of the challenges addressed are licensing, mapping data to RDF vocabularies, and using triplestores. The benefits expected include understanding linked data capabilities, limitations of MARC, and opportunities for future development using linked open data.
Scott Edmunds slides for class 8 from the HKU Data Curation (module MLIM7350 from the Faculty of Education) course covering open science and data publishing
Linked Data at the OU - the story so farEnrico Daga
The document discusses the Open University's use of linked open data and their data.open.ac.uk platform. It provides an overview of linked data principles and the data.open.ac.uk platform. Key services of the Open University rely on data.open.ac.uk to support users in various ways such as the student help center and OpenLearn platform. While linked data is useful for centralized data publishing, it does not replace traditional data management and requires developers to integrate it with existing workflows.
Eureka Research Workbench: A Semantic Approach to an Open Source Electroni...Stuart Chalk
Scientists are looking for ways to leverage web 2.0 technologies in the research laboratory and as a consequence a number of approaches to web-based electronic notebooks are being evaluated. In this presentation I discuss the Eureka Research Workbench, an electronic laboratory notebook built on semantic technology and XML. Using this approach the context of the information recorded in the laboratory can be captured and searched along with the data itself. A discussion of the current system is presented along with the next planned development of the framework and long-term plans relative to linked open data. Presented at the 246th American Chemical Society Meeting in Indianapolis, IN, USA on September 12th, 2013.
LOCAH Project and Considerations of Linked Data ApproachesAdrian Stevenson
Presentation given at JISC 'Managing Research Data International Workshop', Birmingham, UK. 29th March 2011
http://www.jisc.ac.uk/whatwedo/programmes/mrd/rdmevents/mrdinternationalworkshop.aspx
A presentation by Gordon Dunsire.
Delivered at the Cataloguing and Indexing Group Scotland (CIGS) Linked Open Data (LOD) Conference which took place Fri 21 September 2012 at the Edinburgh Centre for Carbon Innovation.
This document summarizes a presentation about transforming the web together through open data and standards. It discusses the World Wide Web Consortium (W3C) and its role in developing open web standards. It provides examples of linked open data projects including data.gov and mashups of government data. Specific open data portals for cities like Chicago are highlighted. Semantic web technologies like RDF, RDFa, and SPARQL are referenced as working groups at W3C. Links are included to further resources on linked open data basics and news portals. The presentation concludes with mentioning Peter Mika from Yahoo discussing open data.
This document provides an introduction to the Semantic Web and Linked Open Data. It discusses how standards like RDF, XML, and OWL allow machines to better understand the meaning of data on the web. It describes how ontologies provide a vocabulary to define relationships between resources. The document outlines the benefits of publishing data as Linked Open Data using these standards, including making data more interoperable and accessible to both humans and machines. Examples are given of biomedical research projects that use Semantic Web technologies to integrate and link different types of data.
Talk delivered at YOW! Developer Conferences in Melbourne, Brisbane and Sydney Australia on 1-9 December 2016.
Abstract: Governments collect a lot of data. Data on air quality, toxic chemicals, laws and regulations, public health, and the census are intended to be widely distributed. Some data is not for public consumption. This talk focuses on open government data — the information that is meant to be made available for benefit of policy makers, researchers, scientists, industry, community organisers, journalists and members of civil society.
We’ll cover the evolution of Linked Data, which is now being used by Google, Apple, IBM Watson, federal governments worldwide, non-profits including CSIRO and OpenPHACTS, and thousands of others worldwide.
Next we’ll delve into the evolution of the U.S. Environmental Protection Agency’s Open Data service that we implemented using Linked Data and an Open Source Data Platform. Highlights include how we connected to hundreds of billions of open data facts in the world’s largest, open chemical molecules database PubChem and DBpedia.
WHO SHOULD ATTEND
Data scientists, software engineers, data analysts, DBAs, technical leaders and anyone interested in utilising linked data and open government data.
The document provides an introduction to the Semantic Web, including:
- The Semantic Web extends the current web by giving information well-defined meaning so computers and people can better work together.
- It aims to make data easier for machines to publish, share, find and understand through smarter data rather than just smarter machines.
- Examples of Semantic Web applications include Bio2RDF, which provides structured data about genes, and the BBC publishing semantic metadata about musical artists.
Linked Data Platform specification aims to define a set of HTTP protocol extensions for accessing, updating, creating and deleting resources from servers that expose their resources as Linked Data. This presentation looks at how the Linked Data Platform can be used for application integration.
A factorial study of neural network learning from differences for regressionMathieu d'Aquin
The document describes a factorial study that trained neural networks to perform regression tasks using differences between cases rather than raw data. It varied factors like the amount of training data, number of epochs, number of similar cases used to determine differences, and whether original features were included with differences. The study found that learning from differences generally required similar data amounts but converged faster. Adding original features was not always beneficial but never significantly hurt performance. The best settings depended on the specific task. Learning from differences showed potential but has limitations like difficulty scaling to large datasets.
Recentrer l'intelligence artificielle sur les connaissancesMathieu d'Aquin
The document appears to contain rules for assigning values to variables (x[n]) based on logical conditions. It includes 14 rules using comparisons of the variable values, logical operators, and numeric values. It also reports the training and test accuracies of the rules as 92.13% and 89.3% respectively.
This document summarizes Mathieu d'Aquin's career path and research interests. It notes that he has worked at LORIA in Nancy, France from 2002-2006, at the Knowledge Media Institute at the Open University in Milton Keynes, UK from 2006-2017, and at the Data Science Institute at NUI Galway in Ireland from 2017-2021. His research has focused on using knowledge-driven and hybrid data-driven/knowledge-driven approaches to understand data provenance, content, and results from data analysis in order to achieve intelligent data understanding.
Unsupervised learning approach for identifying sub-genres in music scoresMathieu d'Aquin
This document discusses an unsupervised learning approach to identify sub-genres in music scores. It explores different ways of representing musical features like pitch and timing in vector formats that can be analyzed using clustering algorithms. Evaluating different feature representations on a sample of folk tunes, the best results were obtained using a combined weighting of pitch, timing, beats extracted from audio files. This approach shows potential for applications like music information retrieval, studying musical genres and connections between tunes.
Knowledge engineering remains relevant for developing knowledge-based systems and representing knowledge on the semantic web and in knowledge graphs. It also has applications in data science for understanding the relationships between data, models, and techniques. Recent work has applied knowledge engineering to explain data patterns, propagate data policies, and make technological artifacts more accessible to non-experts. The field can help scale and integrate tools for knowledge curation, explanation, and knowledge-driven data access and interpretation.
This document discusses the need to study data science as a discipline through examining the processes, techniques, and outputs. It presents data science as consisting of iterative steps like forming hypotheses, collecting and analyzing data, and extracting results. Ontologies and platforms are proposed as tools to systematically describe datasets, licenses, models, and tasks. Case studies examine modeling data flows and understanding patterns in large data science systems. The document argues for an interdisciplinary approach and using techniques like science fiction to ensure data science is developed and applied responsibly through considering social and ethical implications.
This document discusses dealing with open domain data and recent examples. It begins by explaining that typical knowledge systems are closed domain, while open domain systems can answer unknown questions. It then discusses early work using the Watson ontology and Semantic Web to build open domain question answering. A core assumption was that the Semantic Web would know everything if it continued growing, which did not occur. However, recent projects like AFEL have shown the Semantic Web and DBpedia can represent data from many domains and be used for tasks like detecting topics in activity streams, explaining patterns in data, and finding biases. While applications using open domain linked data are still limited, the ability to represent diverse data in a single graph remains important.
This document discusses web analytics and personal analytics for learning. It describes how web analytics can analyze user activities on websites and online systems. Personal analytics can help users improve their behavior by self-tracking. Learning analytics analyze student activities and data from university systems to provide recommendations and applications like vital signs dashboards for doctors. The goal of analytics for everyday learning (AFEL) is to create theory-backed methods and tools that support self-directed learners in making effective use of online resources according to their goals. A scenario is described of a learner who uses an AFEL dashboard to track her progress on different topics and set goals to focus more on areas she is weaker in, like statistics. Challenges discussed include collecting integrated personal data
Learning Analytics: understand learning and support the learnerMathieu d'Aquin
The document discusses learning analytics, which is defined as the measurement, collection, analysis, and reporting of data about learners and their contexts for the purpose of understanding and optimizing learning and the environments where it occurs. It provides examples of how learning analytics can be used for prediction, exploration, and interpretation of learning data. It also discusses challenges in recognizing and measuring learning using data from open, unconstrained online environments. Finally, it presents a cognitive model of learning and knowledge construction that involves constructive friction as the driving force behind learning.
The AFEL Project aims to create tools to support self-directed learners by analyzing data from their online activities. It collects browsing history and social media data to identify topics of interest and measure progress. Indicators show how learners engage with different topics over time. Learners can set goals which are checked against their daily activities. Recommendations guide further learning based on indicators and goals. The project developed a data platform, visual analytics tools, and a mobile app to help learners optimize their use of online resources for informal learning.
Assessing the Readability of Policy Documents: The Case of Terms of Use of On...Mathieu d'Aquin
This document summarizes a study that assessed whether the readability of terms of use documents from various websites is adapted to the education levels of their target audiences. It finds that readability is often not well-adapted, using two main methods: analyzing over 1500 terms of use with the SMOG readability index and comparing typical education levels of website audiences in different countries. Results show mismatches between document complexity and user education levels for many US and India-based sites. The study concludes readability assessment is useful but has limitations when applied broadly.
This document discusses using data to support self-directed learning. It presents a simple model of online learning involving people, resources, topics, and organizations. A scenario is described of a learner named Jane who uses an online dashboard to view her learning activities and progress across different topics. The dashboard helps Jane realize she has been procrastinating on topics she enjoys less, like statistics, and set goals to focus more on those areas. Challenges discussed include recognizing and measuring learning in open online environments. The document also references a cognitive model of learning as a co-evolutionary process driven by "constructive friction," and identifies indicators of learning like coverage of topics.
Towards an “Ethics in Design” methodology for AI research projects Mathieu d'Aquin
The document proposes an "Ethics in Design" methodology for AI research projects. It argues that current ethics debates focus too much on technical data protection and not broader societal impacts. The methodology calls for a reflective, dialectic process involving data scientists and social scientists throughout a project's lifecycle to identify ethical issues, minimize risks, and increase positive societal impact. It explores applying this approach to two case studies and outlines principles of being dialectic, reflective, creative, and all-encompassing. The document concludes by advocating adopting these guidelines and collaborating across fields to further develop ethics methodologies.
AFEL: Towards Measuring Online Activities Contributions to Self-Directed Lear...Mathieu d'Aquin
The document describes how Jane, a 37-year-old administrative assistant, uses the AFEL platform to track and improve her self-directed online learning activities related to her hobbies, career development, and math skills. Jane connects data from her browsing history, Facebook, and MOOCs to the AFEL dashboard. By reviewing her dashboard daily, Jane realizes she has been procrastinating on statistics and sets goals to focus more on it. The dashboard will now remind Jane of her goals and recommend additional learning activities.
From Knowledge Bases to Knowledge Infrastructures for Intelligent SystemsMathieu d'Aquin
1) The document discusses how knowledge representation and ontologies have evolved from closed knowledge bases for specific domains to open knowledge infrastructures that can handle large amounts of diverse data and information at scale.
2) It provides examples of how ontologies and semantic technologies are being used to build intelligent systems that can search, integrate, and automatically process and analyze large datasets.
3) Going forward, ontologies will play an important role in populating knowledge from data and dialog, enabling the automatic exploitation of data by autonomous agents, and enhancing data analytics and mining through semantic representation of datasets, tools, and policies.
Data analytics beyond data processing and how it affects Industry 4.0Mathieu d'Aquin
The document discusses how data analytics is moving beyond just data processing to affect Industry 4.0. It summarizes the research areas and industry partnerships of the Insight Centre for Data Analytics in NUI Galway, including linked data, machine learning, and media analytics. Key applications discussed are monitoring energy consumption using stream processing and event detection, predicting future behavior through machine learning, and detecting and classifying anomalies to inform predictive maintenance decisions.
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
#StandardsGoals for 2025: Standards & certification roundup - Tech Forum 2025BookNet Canada
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, transcript, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
Procurement Insights Cost To Value Guide.pptxJon Hansen
Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
- Accessing the console
- Locating and interpreting log files
- Accessing the data folder within the browser’s cache (using OPFS)
- Understand the difference between single- and multi-user scenarios
- Utilizing Client Clocking
Vaibhav Gupta BAML: AI work flows without Hallucinationsjohn409870
Shipping Agents
Vaibhav Gupta
Cofounder @ Boundary
in/vaigup
boundaryml/baml
Imagine if every API call you made
failed only 5% of the time
boundaryml/baml
Imagine if every LLM call you made
failed only 5% of the time
boundaryml/baml
Imagine if every LLM call you made
failed only 5% of the time
boundaryml/baml
Fault tolerant systems are hard
but now everything must be
fault tolerant
boundaryml/baml
We need to change how we
think about these systems
Aaron Villalpando
Cofounder @ Boundary
Boundary
Combinator
boundaryml/baml
We used to write websites like this:
boundaryml/baml
But now we do this:
boundaryml/baml
Problems web dev had:
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
Reuse components? Good luck.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
Reuse components? Good luck.
Iteration loops took minutes.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
Reuse components? Good luck.
Iteration loops took minutes.
Low engineering rigor
boundaryml/baml
React added engineering rigor
boundaryml/baml
The syntax we use changes how we
think about problems
boundaryml/baml
We used to write agents like this:
boundaryml/baml
Problems agents have:
boundaryml/baml
Problems agents have:
Strings. Strings everywhere.
Context management is impossible.
Changing one thing breaks another.
New models come out all the time.
Iteration loops take minutes.
boundaryml/baml
Problems agents have:
Strings. Strings everywhere.
Context management is impossible.
Changing one thing breaks another.
New models come out all the time.
Iteration loops take minutes.
Low engineering rigor
boundaryml/baml
Agents need
the expressiveness of English,
but the structure of code
F*** You, Show Me The Prompt.
boundaryml/baml
<show don’t tell>
Less prompting +
More engineering
=
Reliability +
Maintainability
BAML
Sam
Greg Antonio
Chris
turned down
openai to join
ex-founder, one
of the earliest
BAML users
MIT PhD
20+ years in
compilers
made his own
database, 400k+
youtube views
Vaibhav Gupta
in/vaigup
[email protected]
boundaryml/baml
Thank you!
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies
In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, presentation slides, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
Increasing Retail Store Efficiency How can Planograms Save Time and Money.pptxAnoop Ashok
In today's fast-paced retail environment, efficiency is key. Every minute counts, and every penny matters. One tool that can significantly boost your store's efficiency is a well-executed planogram. These visual merchandising blueprints not only enhance store layouts but also save time and money in the process.
Cyber Awareness overview for 2025 month of securityriccardosl1
Working with data.open.ac.uk, the Linked Data Platform of the Open University
1. Working with data.open.ac.uk, the linked data platform of the OUMathieu d’Aquin and the LUCERO team @mdaquinKnowledge Media Institute, the Open UniversityLUCERO project lucero-project.info – data.open.ac.uk
2. Linked DataAs set of principles and technologies for a Web of DataPutting the “raw” data online in a standard, web enabled representation (RDF)Make the data Web addressable (URIs)Link with other data
4. So Linked Data for the OU?RAEDBPediaData from Research OutputsOpenLearnContentOROExposed as linked data, our data interlink with each other and the external world: become part of the “global data space” on the WebArchive of Course MaterialLibrary’sCatalogueOf Digital Contentgeonamesdata.gov.ukCurrently: OU public data sit in different systems – hard to discover, obtain, integrate by users.A/V MaterialPodcastsiTunesUBBCDBLP
5. Why is it important?The OU has been the first University to expose its data as linked data: http://data.open.ac.ukNow widely recognized as a critical step forward for the HE sector in the UK (and worldwide)Favor transparency and reuse of data, both externally and internallyReduces cost of dealing with our own public data: integration and reuse by designEnable both new kinds of applications, and to make the ones that are already feasible more cost effectiveAt least 3 other UK universities have now followed our example: http://data.online.lincoln.ac.uk/, http://data.ox.ac.uk/, http://data.southampton.ac.uk/And others in other countries are setting up similar initiatives
6. “if you are working in an IT department within a University you better read this report, as soon your department will need to be making these same decisions.” David Flanders, JISCExpoProgramme Manager,http://code.google.com/p/jiscexpo/wiki/luceroproject#Site_Visit_Report
9. Technological principle: Everything has a URIExample:http://data.open.ac.uk/course/m366 – the course M366http://data.open.ac.uk/oro/21166 – an article in OROhttp://data.open.ac.uk/page/person/ext-911ee9dfa3db572830b00bd8a9983e39 – an Person, who authored the article abovehttp://xmlns.com/foaf/0.1/Person – the type personhttp://purl.org/dc/terms/creator – the property that links an author to an article
10. Technological principle: Content negotiationAccept: text/html Accept: application/rdf+xml<?xml version="1.0" encoding="UTF-8"?><rdf:RDFxmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><rdf:Descriptionrdf:about="http://data.open.ac.uk/oro/9719"> <label xmlns="http://www.w3.org/2000/01/rdf-schema#" rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Aptamers directed to MUC1</label> <authorListxmlns="http://purl.org/ontology/bibo/" rdf:resource="http://data.open.ac.uk/oro/9719#authors"/> <title xmlns="http://purl.org/dc/terms/" rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Aptamers directed to MUC1</title> <abstract xmlns="http://purl.org/ontology/bibo/" rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Aptamers against the glycosylated form of MUC1 are described, along with their use in treatment and diagnosis of conditions associated with elevated production of MUC1.</abstract> <isPartOfxmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/oro/repository"/> <status xmlns="http://purl.org/ontology/bibo/" rdf:resource="http://purl.org/ontology/bibo/status/peerReviewed"/> <status xmlns="http://purl.org/ontology/bibo/" rdf:resource="http://purl.org/ontology/bibo/status/published"/> <creator xmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/person/ext-07bcb3718cb0de7883dc7b8fde7e283d"/> <creator xmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/person/b7fc322e6386517c5ebef3c09d13bd9e"/> <creator xmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/person/ext-7c8b5252e28115f91640559c2fe64ca3"/> <date xmlns="http://purl.org/dc/terms/">2007-11-15</date> <rdf:typerdf:resource="http://purl.org/ontology/bibo/Article"/> <rdf:typerdf:resource="http://purl.org/ontology/bibo/Patent"/></rdf:Description></rdf:RDF>
11. RDF<?xml version="1.0" encoding="UTF-8"?><rdf:RDFxmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><rdf:Descriptionrdf:about="http://data.open.ac.uk/oro/9719"> <label xmlns="http://www.w3.org/2000/01/rdf-schema#" rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Aptamers directed to MUC1</label> <authorListxmlns="http://purl.org/ontology/bibo/" rdf:resource="http://data.open.ac.uk/oro/9719#authors"/> <title xmlns="http://purl.org/dc/terms/" rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Aptamers directed to MUC1</title> <abstract xmlns="http://purl.org/ontology/bibo/" rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Aptamers against the glycosylated form of MUC1 are described, along with their use in treatment and diagnosis of conditions associated with elevated production of MUC1.</abstract> <isPartOfxmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/oro/repository"/> <status xmlns="http://purl.org/ontology/bibo/" rdf:resource="http://purl.org/ontology/bibo/status/peerReviewed"/> <status xmlns="http://purl.org/ontology/bibo/" rdf:resource="http://purl.org/ontology/bibo/status/published"/> <creator xmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/person/ext-07bcb3718cb0de7883dc7b8fde7e283d"/> <creator xmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/person/b7fc322e6386517c5ebef3c09d13bd9e"/> <creator xmlns="http://purl.org/dc/terms/" rdf:resource="http://data.open.ac.uk/person/ext-7c8b5252e28115f91640559c2fe64ca3"/> <date xmlns="http://purl.org/dc/terms/">2007-11-15</date> <rdf:typerdf:resource="http://purl.org/ontology/bibo/Article"/> <rdf:typerdf:resource="http://purl.org/ontology/bibo/Patent"/></rdf:Description></rdf:RDF>
12. By the way…On Study at the OU:http://data.open.ac.uk/course/m366 – if HTML requested, goes to http://www3.open.ac.uk/study/undergraduate/course/m366.htmTry http://www3.open.ac.uk/study/undergraduate/course/m366.rdf
13. Technological principle: link… also to external datasetsUsing URIs makes pieces of data directly addressable and linkable on the Web, independently of where the data is:http://data.open.ac.uk/course/m366 isAvailableInhttp://sws.geonames.org/458258/ (Republic of Latvia)http://data.open.ac.uk/organization/the_open_universitysameAshttp://education.data.gov.uk/doc/school/133849http://data.open.ac.uk/location/building/mbbn (Berrill Building North) postcode http://data.ordnancesurvey.co.uk/id/postcodeunit/MK76AAAnd others can link to our data…
14. SPARQLThe “SQL” of RDF and linked dataFits the graph data model of RDFSelect [variables: ?x ?name, etc.]From [graph, or all graphs if nothing]Where [triple patterns and filters]Order by, limit, offset, etc.SPARQL protocol: simply based on HTTPA SPARQL endpoint is a URL that takes a “query” parameterAnd return results in the SPARQL xml formatSee http://data.open.ac.uk
15. SPARQL: example queriesCourses available in Nigeriaselect distinct ?coursewhere {?course<http://data.open.ac.uk/saou/ontology#isAvailableIn> <http://sws.geonames.org/2328926/>. ?course a <http://purl.org/vocab/aiiso/schema#Module>}http://data.open.ac.uk/query?query=select%20distinct%20%3Fcourse%20where%20{%3Fcourse%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fsaou%2Fontology%23isAvailableIn%3E%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fsws.geonames.org%2F2328926%2F%3E.%20%3Fcourse%20a%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fpurl.org%2Fvocab%2Faiiso%2Fschema%23Module%3E}
16. SPARQL: example queriesCourses available in Nigeriaselect distinct ?coursewhere {?course<http://data.open.ac.uk/saou/ontology#isAvailableIn> <http://sws.geonames.org/2328926/>. ?course a <http://purl.org/vocab/aiiso/schema#Module>}http://data.open.ac.uk/query?query=select%20distinct%20%3Fcourse%20where%20{%3Fcourse%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fsaou%2Fontology%23isAvailableIn%3E%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fsws.geonames.org%2F2328926%2F%3E.%20%3Fcourse%20a%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fpurl.org%2Fvocab%2Faiiso%2Fschema%23Module%3E}
17. SPARQL: example queriesVideo podcasts related to postgraduate courses in computingselect ?x ?t where {?c <http://purl.org/dc/terms/subject> <http://data.open.ac.uk/topic/computing>. ?c <http://data.open.ac.uk/saou/ontology#courseLevel> <http://data.open.ac.uk/saou/ontology#postgraduate>.?x <http://data.open.ac.uk/podcast/ontology/relatesToCourse> ?c.?x <http://purl.org/dc/terms/title> ?t.?x <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://data.open.ac.uk/podcast/ontology/VideoPodcast>}http://data.open.ac.uk/query?query=select%20%3Fx%20%3Ft%0Awhere%20{%0A%20%20%20%3Fc%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fpurl.org%2Fdc%2Fterms%2Fsubject%3E%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Ftopic%2Fcomputing%3E.%0A%20%20%20%3Fc%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fsaou%2Fontology%23courseLevel%3E%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fsaou%2Fontology%23postgraduate%3E.%0A%20%20%20%3Fx%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fpodcast%2Fontology%2FrelatesToCourse%3E%20%3Fc.%0A%20%20%20%3Fx%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fpurl.org%2Fdc%2Fterms%2Ftitle%3E%20%3Ft.%0A%20%20%20%3Fx%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fwww.w3.org%2F1999%2F02%2F22-rdf-syntax-ns%23type%3E%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fpodcast%2Fontology%2FVideoPodcast%3E%0A}&limit=0
18. SPARQL: example queriesThings related to “earthquake”select ?c ?desc where {?c <http://purl.org/dc/terms/description> ?desc .{ {?c <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://data.open.ac.uk/openlearn/ontology/OpenLearnUnit>}UNION{?c <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://data.open.ac.uk/podcast/ontology/VideoPodcast>} }FILTER regex(str(?desc), "earthquake", "i" )}http://data.open.ac.uk/query?query=select%20%3Fc%20%3Fdesc%20where%7B%0A%3Fc%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fpurl.org%2Fdc%2Fterms%2Fdescription%3E%20%3Fdesc%20.%0A%7B%7B%3Fc%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fwww.w3.org%2F1999%2F02%2F22-rdf-syntax-ns%23type%3E%0A%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fopenlearn%2Fontology%2FOpenLearnUnit%3E%7D%0AUNION%0A%7B%3Fc%20%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fwww.w3.org%2F1999%2F02%2F22-rdf-syntax-ns%23type%3E%0A%3Chttps%3A%2F%2Fptop.only.wip.la%3A443%2Fhttp%2Fdata.open.ac.uk%2Fpodcast%2Fontology%2FVideoPodcast%3E%7D%7D%0AFILTER%20regex(str(%3Fdesc)%2C%20%22earthquake%22%2C%20%22i%22%20)%0A%7D&limit=0
27. Define URI SchemeData Modeling ValidationLucero Core TeamLucero membersData OwnerDevelopment of ExtractorURI Creation Rules DefinitionDeploymentLucero KMi Team
28. DatasetsAlready “officially” in place:ORO: more than 18,000 publications from OU researchersPodcasts: 2,500 audio and video tracks from podcast.open.ac.uk, linked to the relate coursesStudy at the OU: more than 600 live module descriptionsOpenLearn: more than 550 Units of course materialKMi Staff and Planet newsletterCurrently being processed:OU Buildings in MK and regional centersLibrary CatalogueYouTube channelOld Courses“Reading Experience Database” project People Profiles
30. Building applications with Linked DataEverything is based on HTTP/XMLIn principle, just need a Web connection…Libraries available in many languages to manipulate RDF dataJava: Jena (http://openjena.org/)PHP: ARC2 (https://github.com/semsol/arc2)Python:RDFLib (http://www.rdflib.net/)…
31. Example: Accessing data.open.ac.uk with PHP/Arc2include_once("arc2/ARC2.php");// declare the SPARQL endpoint$config = array('remote_store_endpoint' => 'http://data.open.ac.uk/query’,);$store = ARC2::getRemoteStore($config);// Execute a SPARQL query$postcodesq = 'select distinct ?p where {[] <http://data.ordnancesurvey.co.uk/ontology/postcode/postcode> ?p.}’;$rows = $store->query($postcodesq, 'rows');// Display the resultsforeach($rows as $row) { echo $row[‘p’].”</br/>”;}
32. ApplicationsFor education Mobile podcast explorer, podcast explorer on TV OU Building Map, OU location tracker (cf. foursquare)OU Expert SearchConnecting courses/OpenLearn to relevant podcastOU Course Profile Facebook app using list of courses, “Study Buddy” app connecting facebook users to relevant coursesFor ResearchDisplay connections in a research communityResearch Data/Impact AnalysisConnection research datasets to external data
37. Example application: Explore Information about a person in the “Reading Experience Database” based on data provided by DBPedia (Linked Data version of Wikipedia) New ways to look at humanities research data
39. The futureMore data… always more dataMore links, especially to external entities BBCGovernment agenciesOther universitiesMore applications:Integration into main OU websites (e.g., study at the OU)Integration into common OU applications (people profile, Facebook course profile, etc.)Support for common OU processes (REF audit, course recommendation, providing resources to AL and lecturers)Connecting to other UniversitiesMany other universities in the UK and abroad are making the move to linked data (see linkeduniversities.org)Linked data has the potential to create connections across institutions, a data-based network on higher education course providers
40. ConclusionLinked data is more than an emerging, academic trend. data.open.ac.uk and linked data in general are fast becoming very valuable resources for developers, internally and externally We are very proud to have been the first university to really deploy a linked data platformNeeds to sustain and evolve as a core service at the OU… … and as a key component of the Web of University Linked Data
#3: Usual pitch: - data on the web = every piece of data is web addressable, so data across different places/stores/systems become linkable: the Web = 1 data space