This presentation has been held by me at the Workshop titled Linked Data for Information Extraction 2014 (LD4IE) held at the International Semantic Web Conference 2014. The related paper is titled "Online Index Extraction from Linked Open Data Sources" and here is the link: http://ceur-ws.org/Vol-1267/LD4IE2014_Benedetti.pdf
PhD thesis defense.
This manuscript describes a methodology designed and implemented to realise the recommendation of vocabularies based on the content of a given website. The goal of the proposed approach is to generate vocabularies by reusing existing schemas. The automatic recommendation helps to leverage websites to self-described web entities in the Web of Data; understandable by both humans and machines. In this direction, the implemented approach is wrapped within a broader methodology of turning a website in a machine understandable node by using technologies that have been developed in the scope of the Semantic Web vision. Transforming a website to a machine understandable entity is the first step required by the websites side in order to narrow the gap with web agents and enable the structured content consumption without the need of implementing an Application Programming Interface (API) that would provide read-write functionality. The motivation of the thesis stems from the fact that the data provided via an API is already presented on the corresponding website in most of the cases.
Profile-based Dataset Recommendation for RDF Data Linking Mohamed BEN ELLEFI
With the emergence of the Web of Data, most notably Linked Open Data (LOD), an abundance of data has become available on the web. However, LOD datasets and their inherent subgraphs vary heavily with respect to their size, topic and domain coverage, the schemas and their data dynamicity (respectively schemas and metadata) over the time. To this extent, identifying suitable datasets, which meet spefic criteria, has become an increasingly important, yet challenging task to support issues such as entity retrieval or semantic search and data linking. Particularly with respect to the interlinking issue, the current topology of the LOD cloud underlines the need for practical and ecient means to recommend suitable datasets: currently, only well-known reference graphs such as DBpedia (the most obvious target), YAGO or Freebase show a high amount of in-links, while there exists a long tail of potentially suitable yet under-recognized datasets. This problem is due to
the semantic web tradition in dealing with "fnding candidate datasets to link to", where data publishers are used to identify target datasets for interlinking.
While an understanding of the nature of the content of specic datasets is a crucial
prerequisite for the mentioned issues, we adopt in this dissertation the notion of
\dataset prole" | a set of features that describe a dataset and allow the comparison
of dierent datasets with regard to their represented characteristics. Our
rst research direction was to implement a collaborative ltering-like dataset recommendation
approach, which exploits both existing dataset topic proles, as well
as traditional dataset connectivity measures, in order to link LOD datasets into
a global dataset-topic-graph. This approach relies on the LOD graph in order to
learn the connectivity behaviour between LOD datasets. However, experiments have
shown that the current topology of the LOD cloud group is far from being complete
to be considered as a ground truth and consequently as learning data.
Facing the limits the current topology of LOD (as learning data), our research
has led to break away from the topic proles representation of \learn to rank"
approach and to adopt a new approach for candidate datasets identication where
the recommendation is based on the intensional proles overlap between dierent
datasets. By intensional prole, we understand the formal representation of a set of
schema concept labels that best describe a dataset and can be potentially enriched
This presentation was given at 10th International Semantic Web Conference, Bonn, and is related the publication of the same title.
Abstract of the publication: Entities on the Web of Data need to have labels in order to be exposable to humans in a meaningful way. These labels can then be used for exploring the data, i.e., for displaying the entities in a linked data browser or other front-end applications, but also to support keyword-based or natural-language based search over the Web of Data. Far too many applications fall back to exposing the URIs of the entities to the user in the absence of more easily understandable representations such as human-readable labels. In this work we introduce a number of label-related metrics: completeness of the labeling, the efficient accessibility of the labels, unambiguity of labeling, and the multilinguality of the labeling. We report our findings from measuring the Web of Data using these metrics. We also investigate which properties are used for labeling purposes, since many vocabularies define further labeling properties beyond the standard property from RDFS.
The publication is available at http://www.aifb.kit.edu/images/c/c0/LabelsInTheWebOfData.pdf
PhD thesis defense.
This manuscript describes a methodology designed and implemented to realise the recommendation of vocabularies based on the content of a given website. The goal of the proposed approach is to generate vocabularies by reusing existing schemas. The automatic recommendation helps to leverage websites to self-described web entities in the Web of Data; understandable by both humans and machines. In this direction, the implemented approach is wrapped within a broader methodology of turning a website in a machine understandable node by using technologies that have been developed in the scope of the Semantic Web vision. Transforming a website to a machine understandable entity is the first step required by the websites side in order to narrow the gap with web agents and enable the structured content consumption without the need of implementing an Application Programming Interface (API) that would provide read-write functionality. The motivation of the thesis stems from the fact that the data provided via an API is already presented on the corresponding website in most of the cases.
Profile-based Dataset Recommendation for RDF Data Linking Mohamed BEN ELLEFI
With the emergence of the Web of Data, most notably Linked Open Data (LOD), an abundance of data has become available on the web. However, LOD datasets and their inherent subgraphs vary heavily with respect to their size, topic and domain coverage, the schemas and their data dynamicity (respectively schemas and metadata) over the time. To this extent, identifying suitable datasets, which meet spefic criteria, has become an increasingly important, yet challenging task to support issues such as entity retrieval or semantic search and data linking. Particularly with respect to the interlinking issue, the current topology of the LOD cloud underlines the need for practical and ecient means to recommend suitable datasets: currently, only well-known reference graphs such as DBpedia (the most obvious target), YAGO or Freebase show a high amount of in-links, while there exists a long tail of potentially suitable yet under-recognized datasets. This problem is due to
the semantic web tradition in dealing with "fnding candidate datasets to link to", where data publishers are used to identify target datasets for interlinking.
While an understanding of the nature of the content of specic datasets is a crucial
prerequisite for the mentioned issues, we adopt in this dissertation the notion of
\dataset prole" | a set of features that describe a dataset and allow the comparison
of dierent datasets with regard to their represented characteristics. Our
rst research direction was to implement a collaborative ltering-like dataset recommendation
approach, which exploits both existing dataset topic proles, as well
as traditional dataset connectivity measures, in order to link LOD datasets into
a global dataset-topic-graph. This approach relies on the LOD graph in order to
learn the connectivity behaviour between LOD datasets. However, experiments have
shown that the current topology of the LOD cloud group is far from being complete
to be considered as a ground truth and consequently as learning data.
Facing the limits the current topology of LOD (as learning data), our research
has led to break away from the topic proles representation of \learn to rank"
approach and to adopt a new approach for candidate datasets identication where
the recommendation is based on the intensional proles overlap between dierent
datasets. By intensional prole, we understand the formal representation of a set of
schema concept labels that best describe a dataset and can be potentially enriched
This presentation was given at 10th International Semantic Web Conference, Bonn, and is related the publication of the same title.
Abstract of the publication: Entities on the Web of Data need to have labels in order to be exposable to humans in a meaningful way. These labels can then be used for exploring the data, i.e., for displaying the entities in a linked data browser or other front-end applications, but also to support keyword-based or natural-language based search over the Web of Data. Far too many applications fall back to exposing the URIs of the entities to the user in the absence of more easily understandable representations such as human-readable labels. In this work we introduce a number of label-related metrics: completeness of the labeling, the efficient accessibility of the labels, unambiguity of labeling, and the multilinguality of the labeling. We report our findings from measuring the Web of Data using these metrics. We also investigate which properties are used for labeling purposes, since many vocabularies define further labeling properties beyond the standard property from RDFS.
The publication is available at http://www.aifb.kit.edu/images/c/c0/LabelsInTheWebOfData.pdf
The EBSCOhost CustomLinks feature offers certain advantages over OpenURL linking when used in conjunction with the EBSCO Discovery Service (EDS) Partner Databases as well as with OCLC's freely available WorldCat Local "quick start" service. The latter is customized and branded locally by Rice University and used as an intermediary to augment the metadata available for linking from EDS to the desired item when not enough metadata is available in the EDS record alone for OpenURL linking to work effectively.
paper: http://dl.acm.org/citation.cfm?id=2815849&CFID=533841763&CFTOKEN=85077894
Abstract:
The Linked Open Data (LOD) Cloud has more than tripled its sources in just three years (from 295 sources in 2011 to 1014 in 2014). While the LOD data are being produced at a increasing rate, LOD tools lack in producing an high level representation of datasets and in supporting users in the exploration and querying of a source. To overcome the above problems and significantly increase the number of consumers of LOD data, we devised a new method and a tool, called LODeX, that promotes the understanding, navigation and querying of LOD sources both for experts and for beginners. It also provides a standardized and homogeneous summary of LOD sources and supports user in the creation of visual queries on previously unknown datasets.
We have extensively evaluated the portability and usability of the tool. LODeX have been tested on the entire set of datasets available at Data Hub, i.e. 302 sources. In this paper, we showcase the usability evaluation of the different features of the tool (the Schema Summary representation and the visual query building) obtained on 27 users (comprising both Semantic Web experts and beginners).
The Competency Convergence: Core Skills and Knowledge of Library and Museum P...jzgarnett
Looking at parallel skills between museum and library information professionals. What can we learn from each other? Based on a project completed at QUT. A comparative study of existing LIS literature and original research in the museum sector. Presented at the 2012 ALIA QLD Mini-Conference on November 21.
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
Natural Language Access to Data via Deductiondiannepatricia
Richard Waldinger, principal scientist in SRI's Artificial Intelligence Center, made this presentation at the Cognitive Systems Institute Speaker Series on February 18, 2016.
Linked Open Data Principles, Technologies and ExamplesOpen Data Support
Theoretical and practical introducton to linked data, focusing both on the value proposition, the theory/foundations, and on practical examples. The material is tailored to the context of the EU institutions.
Using icons is a great way to add visuals to your presentation. There are many ways to get icons online, some are even free. But if you need a specific icon that you can’t find or if you want a special spin to your icon (color, shadow etc) – you can use PowerPoint’s great (and somewhat hidden) “Merge Shapes” commands to create your own icons.
Using these commands you can combine basic shapes into other shapes. You can union and subtract shapes. You can intersect and combine. All while still working natively inside PowerPoint. Once you have created an icon you can change the color, filling and add shadows as needed.
It is just as fun as building with Lego blocks! Well, almost..
This is a guide in 15 steps showing you how you can use these commands to create your own icon - the example we are using is a calendar icon.
10 Tips for Making Beautiful Slideshow Presentations by www.visuali.seEdahn Small
1. Know your goal | make each slide count
2. Plan it out | in some detail
3. Avoid templates | they have the uglies
4. Choose a color scheme | 4 colors, 1 accent
5. Choose a font scheme | match tone
6. Choose a layout scheme | comprehension
7. Use images (wisely) | they’re more memorable
8. 15 words per slide | this slide had 16 words
9. Play with typography | impact, interest, hierarchy
10. Don’t overdo it | white space
Hope you enjoy!
SEE MORE OF MY WORK: http://www.visuali.se
This presentation gives you eight simple tips on how to make your PowerPoint presentation slides more visually engaging, creative and fun. Try out these advice and you will make your best PowerPoint presentation ever.
This presentation was created by my powerpoint design agency Slides. We are based in Spain but have clients worldwide.
Drop me an email and we will discuss your project.
Linked Open Graph: browsing multiple SPARQL entry points to build your own LO...Paolo Nesi
A number of accessible RDF stores are populating the linked open data world. The navigation on data reticular relationships is becoming every day more relevant. Several knowledge base present relevant links to common vocabularies while many others are going to be discovered increasing the reasoning capabilities of our knowledge base applications. In this paper, the Linked Open Graph, LOG, is presented. It is a web tool for collaborative browsing and navigation on multiple SPARQL entry points. The paper presented an overview of major problems to be addressed, a comparison with the state of the arts tools, and some details about the LOG graph computation to cope with high complexity of large Linked Open Dada graphs. The LOG.disit.org tool is also presented by means of a set of examples involving multiple RDF stores and putting in evidence the new provided features and advantages using dbPedia, Getty, Europeana, Geonames, etc. The LOG tool is free to be used, and it has been adopted, developed and/or improved in multiple projects: such as ECLAP for social media cultural heritage, Sii-Mobility for smart city, and ICARO for cloud ontology analysis, OSIM for competence / knowledge mining and analysis. Keywords LOD, LOD browsing, knowledge base browsing, SPARQL entry points.
The EBSCOhost CustomLinks feature offers certain advantages over OpenURL linking when used in conjunction with the EBSCO Discovery Service (EDS) Partner Databases as well as with OCLC's freely available WorldCat Local "quick start" service. The latter is customized and branded locally by Rice University and used as an intermediary to augment the metadata available for linking from EDS to the desired item when not enough metadata is available in the EDS record alone for OpenURL linking to work effectively.
paper: http://dl.acm.org/citation.cfm?id=2815849&CFID=533841763&CFTOKEN=85077894
Abstract:
The Linked Open Data (LOD) Cloud has more than tripled its sources in just three years (from 295 sources in 2011 to 1014 in 2014). While the LOD data are being produced at a increasing rate, LOD tools lack in producing an high level representation of datasets and in supporting users in the exploration and querying of a source. To overcome the above problems and significantly increase the number of consumers of LOD data, we devised a new method and a tool, called LODeX, that promotes the understanding, navigation and querying of LOD sources both for experts and for beginners. It also provides a standardized and homogeneous summary of LOD sources and supports user in the creation of visual queries on previously unknown datasets.
We have extensively evaluated the portability and usability of the tool. LODeX have been tested on the entire set of datasets available at Data Hub, i.e. 302 sources. In this paper, we showcase the usability evaluation of the different features of the tool (the Schema Summary representation and the visual query building) obtained on 27 users (comprising both Semantic Web experts and beginners).
The Competency Convergence: Core Skills and Knowledge of Library and Museum P...jzgarnett
Looking at parallel skills between museum and library information professionals. What can we learn from each other? Based on a project completed at QUT. A comparative study of existing LIS literature and original research in the museum sector. Presented at the 2012 ALIA QLD Mini-Conference on November 21.
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
Natural Language Access to Data via Deductiondiannepatricia
Richard Waldinger, principal scientist in SRI's Artificial Intelligence Center, made this presentation at the Cognitive Systems Institute Speaker Series on February 18, 2016.
Linked Open Data Principles, Technologies and ExamplesOpen Data Support
Theoretical and practical introducton to linked data, focusing both on the value proposition, the theory/foundations, and on practical examples. The material is tailored to the context of the EU institutions.
Using icons is a great way to add visuals to your presentation. There are many ways to get icons online, some are even free. But if you need a specific icon that you can’t find or if you want a special spin to your icon (color, shadow etc) – you can use PowerPoint’s great (and somewhat hidden) “Merge Shapes” commands to create your own icons.
Using these commands you can combine basic shapes into other shapes. You can union and subtract shapes. You can intersect and combine. All while still working natively inside PowerPoint. Once you have created an icon you can change the color, filling and add shadows as needed.
It is just as fun as building with Lego blocks! Well, almost..
This is a guide in 15 steps showing you how you can use these commands to create your own icon - the example we are using is a calendar icon.
10 Tips for Making Beautiful Slideshow Presentations by www.visuali.seEdahn Small
1. Know your goal | make each slide count
2. Plan it out | in some detail
3. Avoid templates | they have the uglies
4. Choose a color scheme | 4 colors, 1 accent
5. Choose a font scheme | match tone
6. Choose a layout scheme | comprehension
7. Use images (wisely) | they’re more memorable
8. 15 words per slide | this slide had 16 words
9. Play with typography | impact, interest, hierarchy
10. Don’t overdo it | white space
Hope you enjoy!
SEE MORE OF MY WORK: http://www.visuali.se
This presentation gives you eight simple tips on how to make your PowerPoint presentation slides more visually engaging, creative and fun. Try out these advice and you will make your best PowerPoint presentation ever.
This presentation was created by my powerpoint design agency Slides. We are based in Spain but have clients worldwide.
Drop me an email and we will discuss your project.
Linked Open Graph: browsing multiple SPARQL entry points to build your own LO...Paolo Nesi
A number of accessible RDF stores are populating the linked open data world. The navigation on data reticular relationships is becoming every day more relevant. Several knowledge base present relevant links to common vocabularies while many others are going to be discovered increasing the reasoning capabilities of our knowledge base applications. In this paper, the Linked Open Graph, LOG, is presented. It is a web tool for collaborative browsing and navigation on multiple SPARQL entry points. The paper presented an overview of major problems to be addressed, a comparison with the state of the arts tools, and some details about the LOG graph computation to cope with high complexity of large Linked Open Dada graphs. The LOG.disit.org tool is also presented by means of a set of examples involving multiple RDF stores and putting in evidence the new provided features and advantages using dbPedia, Getty, Europeana, Geonames, etc. The LOG tool is free to be used, and it has been adopted, developed and/or improved in multiple projects: such as ECLAP for social media cultural heritage, Sii-Mobility for smart city, and ICARO for cloud ontology analysis, OSIM for competence / knowledge mining and analysis. Keywords LOD, LOD browsing, knowledge base browsing, SPARQL entry points.
Talk at 3th Keystone Training School - Keyword Search in Big Linked Data - Institute for Software Technology and Interactive Systems, TU Wien, Austria, 2017
Engaging Information Professionals in the Process of Authoritative Interlinki...Lucy McKenna
Through the use of Linked Data (LD), Libraries, Archives and Museums (LAMs) have the potential to expose their collections to a larger audience and to allow for more efficient user searches. Despite this, relatively few LAMs have invested in LD projects and the majority of these display limited interlinking across datasets and institutions. A survey was conducted to understand Information Professionals' (IPs') position with regards to LD, with a particular focus on the interlinking problem. The survey was completed by 185 librarians, archivists, metadata cataloguers and researchers. Results indicated that, when interlinking, IPs find the process of ontology and property selection to be particularly challenging, and LD tooling to be technologically complex and unsuitable for their needs.
Our research is focused on developing an authoritative interlinking framework for LAMs with a view to increasing IP engagement in the linking process. Our framework will provide a set of standards to facilitate IPs in the selection of link types, specifically when linking local resources to authorities. The framework will include guidelines for authority, ontology and property selection, and for adding provenance data. A user-interface will be developed which will direct IPs through the resource interlinking process as per our framework. Although there are existing tools in this domain, our framework differs in that it will be designed with the needs and expertise of IPs in mind. This will be achieved by involving IPs in the design and evaluation of the framework. A mock-up of the interface has already been tested and adjustments have been made based on results. We are currently working on developing a minimal viable product so as to allow for further testing of the framework. We will present our updated framework, interface, and proposed interlinking solutions.
This presentation was provided by Abigail Sparling and Adam Cohen of The University of Alberta Library, during the NISO webinar "Implementing Linked Library Data," held on November 13, 2019.
“Publishing and Consuming Linked Data. (Lessons learnt when using LOD in an a...Marta Villegas
Talk given at the "1st Summer Datathon on Linguistic Linked Open Data (SD-LLOD-15)"
In this talk we will describe our experience when publishing and, more crucially, consuming Linked Data at the Spanish CLARIN Knowledge Centre (http://lod.iula.upf.edu). The center includes a Catalog of NLP resources & tools which aims to promote the use of language technology to researches of Humanities and Social Sciences. Though the original data set followed the XML/XSD schema, this was rewritten in accordance to the LOD approach in order to maximize the information contained in our repositories and to be able to enrich the data there.
We will addresses some critical aspects when RDFying XSD/XML data focusing on the strategy followed when mapping controlled vocabularies expressed in XML enumerations; when dealing with certain unstructured data (those where input strings may generate relevant instances); and when addressing identity resolution and linking tasks once the eventual instances are RDFied. Here we will also report on data cleansing, a crucial and unavoidable task which we addressed as an incremental process where SPARQL played an important role. We will see that some of the decisions taken depend on the eventual application we have in mind. The requirements of our Catalog (implemented as a web browser) include: displaying data to the user in a comprehensive way; aggregating external data in a sensitive manner and making hidden implicit relations explicit. In addition, the system needs to provide fresh data (regularly updated) in a quick response time.
Finally, we will report on our experiences when addressing data integration and enrichment (via data mashup). We experimented with different strategies (e.g. using external URIS vs caching local data) and faced different problems (time latency, dereferencing external URIS) that may be useful to share.
DSpace-CRIS_An open source solution for Research_EDU15Michele Mennielli
The research area is a complex world to manage. It involves collecting data, supporting researchers and administrators, monitoring results, allocating resources efficiently, enhancing visibility, and strengthening national and international collaborations. RIMs manage these activities, but they might be too expensive. This is why Cineca developed DSpace-CRIS, and released it in open source.
Semantic Similarity and Selection of Resources Published According to Linked ...Riccardo Albertoni
The position paper aims at discussing the potential of exploiting linked data best practice to provide metadata documenting domain specific resources created through verbose acquisition-processing pipelines. It argues that resource selection, namely the process engaged to choose a set of resources suitable for a given analysis/design purpose, must be supported by a deep comparison of their metadata. The semantic similarity proposed in our previous works is discussed for this purpose and the main issues to make it scale up to the web of data are introduced. Discussed issues contribute beyond the re-engineering of our similarity since they largely apply to every tool which is going to exploit information made available as linked data. A research plan and an exploratory phase facing the presented issues are described remarking the lessons we have learnt so far.
Presentation done by Ander García, Maria Teresa Linaza, Javier Franco and Miriam Juaristi, during "Data management" workshop, of the ENTER2015 eTourism conference.
About the Webinar
The library and cultural institution communities have generally accepted the vision of moving to a Linked Data environment that will align and integrate their resources with those of the greater Semantic Web. But moving from vision to implementation is not easy or well-understood. A number of institutions have begun the needed infrastructure and tools development with pilot projects to provide structured data in support of discovery and navigation services for their collections and resources.
Join NISO for this webinar where speakers will highlight actual Linked Data projects within their institutions—from envisioning the model to implementation and lessons learned—and present their thoughts on how linked data benefits research, scholarly communications, and publishing.
Speakers:
Jon Voss - Strategic Partnerships Director, We Are What We Do
LODLAM + Historypin: A Collaborative Global Community
Matt Miller - Front End Developer, NYPL Labs at the New York Public Library
The Linked Jazz Project: Revealing the Relationships of the Jazz Community
Cory Lampert - Head, Digital Collections , UNLV University Libraries
Silvia Southwick - Digital Collections Metadata Librarian, UNLV University Libraries
Linked Data Demystified: The UNLV Linked Data Project
This presentation gives details on technologies and approaches towards exploiting Linked Data by building LD applications. In particular, it gives an overview of popular existing applications and introduces the main technologies that support implementation and development. Furthermore, it illustrates how data exposed through common Web APIs can be integrated with Linked Data in order to create mashups.
Similar to Online Index Extraction from Linked Open Data Sources (20)
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.
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.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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.
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Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
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1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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
Connector Corner: Automate dynamic content and events by pushing a button
Online Index Extraction from Linked Open Data Sources
1. DB Group @ UNIMO
Fabio Benedetti Sonia Bergamaschi Laura Po
Department of Engineering “Enzo Ferrari”
University of Modena & Reggio Emilia
LD4IE 2014 – Riva Del Garda, Italy
Online Index Extraction from Linked Open Data Sources
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia 1
2. DB Group @ UNIMO
2
• Selection of a relevant LOD source
• Statistical indexes
• Architecture Overview
• Performance Evaluation
• LODeX & Conclusions
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
3. DB Group @ UNIMO
3
Schmachtenberg, Max, Christian Bizer, and Heiko Paulheim. "Adoption of the Linked Data Best Practices in
Different Topical Domains." The Semantic Web–ISWC 2014. Springer International Publishing, 2014. 245-260.
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
4. DB Group @ UNIMO
4
2009 2014*
Domain Number % Number %
Cross-domain 41 13.95% 41 4.04%
Geographic 31 10.54% 21 2.07%
Government 49 16.67% 183 18.05%
Life sciences 41 13.95% 83 8.19%
Media 25 8.50% 22 2.17%
Publications 87 29.59% 96 9.47%
Social web 0 0.00% 520 51.28%
User-generated
content 20 6.80% 48 4.73%
Total 294 1014
*Only 570 datasets belong to the LOD cloud,
the remaining datasets do not contain
ingoing/outgoing links to the LOD Cloud.
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
2009 Domain
Cross-domain
Geographic
Government
Life sciences
Media
Publications
Social web
2014
5. DB Group @ UNIMO
5
1. The documentation of the dataset
– The documentation can be poor or absent
– There are no standard to provide the documentation
– Sometime it is provided as an RDF file in XML format
2. Searching features of existing catalogs (i.e. Datahub)
– The metadata contain poor information
– None information about the structure of the dataset is used by the
search engine
3. The manual exploration of the Dataset
– It is required a good knowledge of SPARQL language
– It is a time consuming task
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
6. DB Group @ UNIMO
6
To automatically extract a set of indexes able to
describe the structure of a LOD dataset
How to describe the dataset
LOD datasets can have different purpose and structure:
• Ontology/Vocabulary (OWL & RDFS constraints)
• Open Data (i.e. generated from existing RDBMS)
The indexes should maximize the value of the information extraction
from heterogeneous datasets
Online & Automatic extraction
• It does not require any additional information by the user
• It works with SPARQL endpoints
– We have to handle the bad performance issues of these Datasets
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
7. DB Group @ UNIMO
7
We can think the entire set of RDF triples partitioned between:
• Intensional Knowledge
• Extensional Knowledge
The Intensional knowledge
• It contains the RDFS or OWL constraints of the Ontology
• It represents the T-Box components of the knowledge base
The Extensional knowledge
• It contains the entities of the real word
described in the dataset
• It represents the A-Box components of
the knowledge base
• its triples cover most of the dataset
Instantiated classes act as a
bridge between the two type of
knowledge
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
8. DB Group @ UNIMO
8
ex:sector
rdf:label rdf:Property
owl:Class
rdfs:domain
rdf:type rdf:type
ex:Sector ex:Organization
sector
rdf:type
rdf:type
rdf:type
ex:sector
Intensional
Knowledge
Instantiated
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
rdfs:range
rdf:label
rdf:type
owl:ObjectProperty
rdf:type
sector1
organization1
ex:sector
dc:name
“Energy” organization2
Classes
Extensional
Knowledge
9. DB Group @ UNIMO
9
The Statistical Indexes are grouped in three categories:
• Generic
• Intensional
• Extensional
Name Description Structure Category
t Number of Triples Integer
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
Generic
c Number of Classes Integer
I Number of Instances Integer
Cl Class List List(name, n. Instances)
Pl Property List List(name, n. occurrence)
IK Intensional K. triples List(s, p, o) Intensional
Sc Subject Class List(c, p, n. occurrence)
SCl Subject Class to literal List(c, p, n. occurrence) Extensional
Oc Object Class List(c, p, n. occurrence)
10. DB Group @ UNIMO
10
ex:Sector ex:Organization
rdf:type
sector1
rdf:type
Subject
Class
ex:sector rdf:type
Subject
Class to
literal
ex:Sector ex:Organization
rdf:type
sector1
rdf:type
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
organization1
ex:sector
dc:name
“Energy” organization2
Sc - Subject Class SCl - Subject Class to literal Oc -Object Class
S ex:Organization ex:Sector ex:Sector
P ex:sector dc:name ex:sector
n 2 1 1
organization1
ex:sector
dc:name
“Energy”
ex:sector
Object
Class
11. DB Group @ UNIMO
11
It takes in input a list of URLs of SPARQL endpoints
A set of Statistical Indexes for each endpoint is the output
• The IE process dynamically generates the SPARQL query used to
extract the Statistical Indexes
• It works in parallel querying different datasets
• Partial results and the Statistical Indexes are stored in a NoSQL DB
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
12. DB Group @ UNIMO
12
General Statistic Extraction
• It uses 6 different queries to extract the indexes of this group
Intensional Knowledge Extraction
• The extraction of the Intensional knowledge is performed through an
iterative algorithm
• The algorithm traverses the graph starting from the instantiated classes
Extensional Schema Extraction
• It uses different SPARQL aggregation query to extract SC, SCl and OC
• Use a technique called Pattern Strategy to complete the extraction
– It is a technique able to produce an higher number of less
complex SPARQL query
– It is used when the endpoint is not able to answer an aggregation
query and it throws a timeout error
A complete list of the 24 query patterns is available at http://dbgroup.unimo.it/lodexQueries
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
13. DB Group @ UNIMO
13
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
14. DB Group @ UNIMO
14
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
Reachable datasets 244
SPARQL 1.1 compatible 137
Extraction completed 107
Extraction completed
33
Without PS
Total triples (107 datasets) 3,45 b
AVG time extraction 6,12 m
Total time (single process) 11,15 h
Total time (9 processes) 3,35 h
The test has been performed on a list of
469 Datasets
• More than the 90 % completed the
extraction in less than 500 s
• The PS technique has proved its worth
• from 33 to 107 completed the
extraction
• The IE process is scalable
• linear correlation between number of
triples and time
15. DB Group @ UNIMO
LODeX is an online tool able to shows a visual Schema Summary for a LOD source
• We made use of the statistical indexes for the generation of the Schema
F. Benedetti, S. Bergamaschi, and L. Po, “A visual summary for linked open data sources” 2014, International Semantic Web Conference (Posters & Demos).
17
Summary.
• Users can interact with the Schema Summary dataset and focus on the
information that they are more interested in.
The tool is accessible at: www.dbgroup.unimo.it/lodex
Come to attend the LODeX demo at the ISWC demo session!
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
16. DB Group @ UNIMO
18
Conclusion
• We are able to extract valuable indexes from a LOD dataset
taking advantage of the definition of Intensional and
Extensional knowledge
• The process of extraction is been tested with an huge number
of dataset and its efficiency and effectiveness has been
proven
Future Works
• To extend VOID vocabulary with our descriptors
• We want propose LODeX as assistance tool for LOD portals.
• We are extending LODeX in order to support the automatic
SPARQL query generation
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
17. DB Group @ UNIMO
19
LD4IE 2014 – Riva Del Garda, Italy
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia
Online Index Extraction from Linked Open Data Sources
18. DB Group @ UNIMO
20
Thanks for your attention!
LD4IE 2014 – Riva Del Garda, Italy
Online Index Extraction from Linked Open Data Sources
Dot. Fabio Benedetti
Dip. Ing. “Enzo Ferrari” – University of Modena e Reggio Emilia