- Scientific names for species can change over time as taxonomy knowledge evolves
- An event-centric ontology model represents names and changes through time using different URIs for taxon concepts at different times
- Transition and snapshot models can then simplify the descriptions by linking concepts over time or just showing current names
- This approach allows integrated representation of taxonomy knowledge and its revisions in a computable way
Slides from keynote lecture by Andrew Prescott to the 7th Herrenhausen conference of the Volkswagen Foundation, 'Big Data in a Transdisciplinary Perspective'
Slides from keynote lecture by Andrew Prescott to the 7th Herrenhausen conference of the Volkswagen Foundation, 'Big Data in a Transdisciplinary Perspective'
About the Virtual Conference
With the expansion of digital data collection and the increased expectations of data sharing, researchers are turning to their libraries or institutional repositories as a place to store and preserve that data. Many institutions have created such data management services and see the data curation role as a growing and important element of their service portfolio. While some of the experience in managing other types of digital resources is transferrable, the management of large-scale scientific data has many special requirements and challenges. From metadata collection and cataloging data sources, to identification, discovery, and preservation, best practices and standards are still in their infancy.
This Virtual Conference will explore in greater depth than traditional webinars some of the practical lessons from those who have implemented data management and developed best practices, as well as provide some insight into the evolving issues the community faces. It will include discussions related to certification of trusted repositories, provenance and identification issues around data, data citation, preservation, and the work of several repository networks to advance distribution of scientific information.
RDAP13 Lorrie Johnson: Facilitating Access to Scientific DataASIS&T
Lorrie Johnson, U.S. Department of Energy/Office of Science and Technical Information: “Facilitating Access to Scientific Data: The DataCite, Science.gov, and WorldWideScience.org Initiatives”
Panel: Linked data and metadata (co-sponsored by the ASIS&T Digital Libraries SIG)
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
Science is witnessing a data revolution. Data are now created by faster and cheaper physical technologies, software tools and digital collaborations. Examples of these include satellite networks, simulation models and social network data. To transform these data successfully into information then into knowledge and finally into wisdom, we need new forms of computational thinking. These may be enabled by building "instruments" that make data comprehensible for the "naked mind" in a similar fashion to the way in which telescopes reveal the universe to the naked eye. These new instruments must be grounded in well-founded principles to ensure they have the fidelity and capacity to transform the complex and large-scale data into comprehensive forms; this demands new data-intensive methods.
Data-intensive refers to huge volumes of data, complex patterns of data integration and analysis and intricate interactions between data and users. Current methods and tools are failing to address data-intensive challenges effectively: they fail for several reasons, all of which are aspects of scalability. I will introduce three main aspects of data-intensive research and show how we are addressing the challenges that arise from the interaction of these aspects. I will make use of results from our interdisciplinary collaborations as examples of solutions to specific challenges that can arise when scaling up intensity.
The presentation explores the trend towards a scholarly communication system that is friendly to machines. It presents 3 exhibits illustrating the trend and 1 exhibit illustrating inertia in the system. It makes the point that machine-actionability can be much easier achieved if content and metadata are available in Open Access and under a permissive Creative Commons license. It also observes that even with content and metadata openly available, new costs related to advanced tools to explore the scholarly record will emerge. Finally, it points at significant challenges regarding the persistence of the scholarly record in light of increasingly interconnected and actionable content and advanced tools to interact with it.
The slides were used for a plenary presentation at the LIBER 2011 Conference in Barcelona, Spain, on June 30 2011.
Scott Edmunds talk on GigaScience Big-Data, Data Citation and future data handling at the International Conference of Genomics on the 15th November 2011.
Beyond Preservation: Situating Archaeological Data in Professional PracticeEric Kansa
I presented this lecture at the German Archaeological Institute (DAI) in Berlin on Nov. 6, 2014 (see: http://www.dainst.org/termin/-/event-display/ogNX4Gtxkd87/342513)
The lecture focuses on how archaeological data fits in professional practice. It looks at scholarly communications, government policies toward the sciences and humanities, and professional reward structures.
The lecture then shows examples of how Open Context publishes archeological data, including editorial processes to promote data quality and relate contributed data to the 'Web of Data' using Linked Open Data methods. Research applications of Open Context and linked archaeological data include the Digital Index of North American Archaeology (DINAA) project (see: http://ux.opencontext.org/blog/archaeology-site-data/) and a data integration study exploring the development and dispersal of animal husbandry economies in Epipaleolithic - Chalcolithic Anatolia (see: http://dx.doi.org/10.1371/journal.pone.0099845)
The lecture concludes with how archaeologists need to invest more intellectually in the method and theory of modeling and creating data. It also looks at how concepts and expectations of publishing static artifacts need to be revised (using techniques like version control) to enable continued and more transparent revision of data to fix problems, implement new standards, and meet new research goals.
IAO-Intel: An Ontology of Information Artifacts in the Intelligence DomainBarry Smith
We describe on-going work on IAO-Intel, an information artifact ontology developed as part of a suite of ontologies designed to support the needs of intelligence community. IAO-Intel provides a controlled, structured vocabulary for the consistent formulation of metadata about documents, images, emails and other carriers of information. It will provide a resource for uniform explication of the terms used in multiple existing military dictionaries, thesauri and metadata registries, thereby enhancing the degree to
which the content formulated with their aid will be available to computational reasoning.
Presented at the 2013 STIDS (Semantic Technology for Intelligence, Defense and Security) conference: http://stids.c4i.gmu.edu/
CSV-X is a schema language, model, and processing engine for non-uniform CSV enabling annotation, validation, cross-referencing, Linked Data, RDF serialization, and transformation to other formats.
About the Virtual Conference
With the expansion of digital data collection and the increased expectations of data sharing, researchers are turning to their libraries or institutional repositories as a place to store and preserve that data. Many institutions have created such data management services and see the data curation role as a growing and important element of their service portfolio. While some of the experience in managing other types of digital resources is transferrable, the management of large-scale scientific data has many special requirements and challenges. From metadata collection and cataloging data sources, to identification, discovery, and preservation, best practices and standards are still in their infancy.
This Virtual Conference will explore in greater depth than traditional webinars some of the practical lessons from those who have implemented data management and developed best practices, as well as provide some insight into the evolving issues the community faces. It will include discussions related to certification of trusted repositories, provenance and identification issues around data, data citation, preservation, and the work of several repository networks to advance distribution of scientific information.
RDAP13 Lorrie Johnson: Facilitating Access to Scientific DataASIS&T
Lorrie Johnson, U.S. Department of Energy/Office of Science and Technical Information: “Facilitating Access to Scientific Data: The DataCite, Science.gov, and WorldWideScience.org Initiatives”
Panel: Linked data and metadata (co-sponsored by the ASIS&T Digital Libraries SIG)
Research Data Access & Preservation Summit 2013
Baltimore, MD April 4, 2013 #rdap13
Science is witnessing a data revolution. Data are now created by faster and cheaper physical technologies, software tools and digital collaborations. Examples of these include satellite networks, simulation models and social network data. To transform these data successfully into information then into knowledge and finally into wisdom, we need new forms of computational thinking. These may be enabled by building "instruments" that make data comprehensible for the "naked mind" in a similar fashion to the way in which telescopes reveal the universe to the naked eye. These new instruments must be grounded in well-founded principles to ensure they have the fidelity and capacity to transform the complex and large-scale data into comprehensive forms; this demands new data-intensive methods.
Data-intensive refers to huge volumes of data, complex patterns of data integration and analysis and intricate interactions between data and users. Current methods and tools are failing to address data-intensive challenges effectively: they fail for several reasons, all of which are aspects of scalability. I will introduce three main aspects of data-intensive research and show how we are addressing the challenges that arise from the interaction of these aspects. I will make use of results from our interdisciplinary collaborations as examples of solutions to specific challenges that can arise when scaling up intensity.
The presentation explores the trend towards a scholarly communication system that is friendly to machines. It presents 3 exhibits illustrating the trend and 1 exhibit illustrating inertia in the system. It makes the point that machine-actionability can be much easier achieved if content and metadata are available in Open Access and under a permissive Creative Commons license. It also observes that even with content and metadata openly available, new costs related to advanced tools to explore the scholarly record will emerge. Finally, it points at significant challenges regarding the persistence of the scholarly record in light of increasingly interconnected and actionable content and advanced tools to interact with it.
The slides were used for a plenary presentation at the LIBER 2011 Conference in Barcelona, Spain, on June 30 2011.
Scott Edmunds talk on GigaScience Big-Data, Data Citation and future data handling at the International Conference of Genomics on the 15th November 2011.
Beyond Preservation: Situating Archaeological Data in Professional PracticeEric Kansa
I presented this lecture at the German Archaeological Institute (DAI) in Berlin on Nov. 6, 2014 (see: http://www.dainst.org/termin/-/event-display/ogNX4Gtxkd87/342513)
The lecture focuses on how archaeological data fits in professional practice. It looks at scholarly communications, government policies toward the sciences and humanities, and professional reward structures.
The lecture then shows examples of how Open Context publishes archeological data, including editorial processes to promote data quality and relate contributed data to the 'Web of Data' using Linked Open Data methods. Research applications of Open Context and linked archaeological data include the Digital Index of North American Archaeology (DINAA) project (see: http://ux.opencontext.org/blog/archaeology-site-data/) and a data integration study exploring the development and dispersal of animal husbandry economies in Epipaleolithic - Chalcolithic Anatolia (see: http://dx.doi.org/10.1371/journal.pone.0099845)
The lecture concludes with how archaeologists need to invest more intellectually in the method and theory of modeling and creating data. It also looks at how concepts and expectations of publishing static artifacts need to be revised (using techniques like version control) to enable continued and more transparent revision of data to fix problems, implement new standards, and meet new research goals.
IAO-Intel: An Ontology of Information Artifacts in the Intelligence DomainBarry Smith
We describe on-going work on IAO-Intel, an information artifact ontology developed as part of a suite of ontologies designed to support the needs of intelligence community. IAO-Intel provides a controlled, structured vocabulary for the consistent formulation of metadata about documents, images, emails and other carriers of information. It will provide a resource for uniform explication of the terms used in multiple existing military dictionaries, thesauri and metadata registries, thereby enhancing the degree to
which the content formulated with their aid will be available to computational reasoning.
Presented at the 2013 STIDS (Semantic Technology for Intelligence, Defense and Security) conference: http://stids.c4i.gmu.edu/
CSV-X is a schema language, model, and processing engine for non-uniform CSV enabling annotation, validation, cross-referencing, Linked Data, RDF serialization, and transformation to other formats.
RDF2Vec: RDF Graph Embeddings for Data MiningPetar Ristoski
Linked Open Data has been recognized as a valuable source for background information in data mining. However, most data mining tools require features in propositional form, i.e., a vector of nominal or numerical features associated with an instance, while Linked Open Data sources are graphs by nature. In this paper, we present RDF2Vec, an approach that uses language modeling approaches for unsupervised feature extraction from sequences of words, and adapts them to RDF graphs. We generate sequences by leveraging local information from graph sub-structures, harvested by Weisfeiler-Lehman Subtree RDF Graph Kernels and graph walks, and learn latent numerical representations of entities in RDF graphs. Our evaluation shows that such vector representations outperform existing techniques for the propositionalization of RDF graphs on a variety of different predictive machine learning tasks, and that feature vector representations of general knowledge graphs such as DBpedia and Wikidata can be easily reused for different tasks.
Providing open data is of interest for its societal and commercial value, for transparency, and because more people can do fun things with data. There is a growing number of initiatives to provide open data, from, for example, the UK government and the World Bank. However, much of this data is provided in formats such as Excel files, or even PDF files. This raises the question of
- How best to provide access to data so it can be most easily reused?
- How to enable the discovery of relevant data within the multitude of available data sets?
- How to enable applications to integrate data from large numbers of formerly unknown data sources?
One way to address these issues to to use the design principles of linked data (http://www.w3.org/DesignIssues/LinkedData.html), which suggest best practices for how to publish and connect structured data on the Web. This presentation gives an overview of linked data technologies (such as RDF and SPARQL), examples of how they can be used, as well as some starting points for people who want to provide and use linked data.
The presentation was given on August 8, at the Hacknight event (http://hacknight.se/) of Forskningsavdelningen (http://forskningsavd.se/) (Swedish: “Research Department”) a hackerspace in Malmö.
I Linked Open Data nei Beni Culturali, alcuni progetti e casi di studioCulturaItalia
Maria Emilia Masci, Scuola Normale Superiore, Linked Open Data (LOD): Un’Opportunità per il Patrimonio Culturale Digitale, Roma, ICCU, 29 novembre 2013
Describing Everything - Open Web standards and classificationDan Brickley
Original title: Open Web standards and classification: Foundations for a hybrid approach
Keynote address, UDC Seminar:
Classification at a Crossroads
30 October 2009 Koninklijke Bibliotheek, The Hague
Dan Brickley, Vrije University Amsterdam
Slides for the GLAM Panel at WikidataCon 2019 in Berlin, 25. October 2019, on the role of Wikidata within data ecosystems extending beyond the realm of Wikimedia projects. Authors: Susanna Ånäs (Finland); Mike Dickison (New Zealand); Joachim Neubert (Germany); Beat Estermann (Switzerland).
Knowledge – dynamics – landscape - navigation – what have interfaces to digit...Andrea Scharnhorst
When we google, search Wikipedia, and share information on Mendeley, we obviously deal with complex networks of information. But also traditional information spaces – the collections of libraries for instance – and their classification systems are evolving complex systems. This talk explores the possibilities to use concepts and methods from statistical physics to analyze information dynamics. We depart from information dynamics in scholarly communication, and point to current encounters between physics and scientometrics. We discuss more in-depth the evolution of category systems in libraries (Universal Decimal Classification) in comparison to on-line spaces (Wikipedia). The talk closes with an introduction into a new European network – the COST Action KnowEscape – in which information professionals, sociologists, computer scientists, physicists and digital humanities scholars in an unique alliance seek for knowledge maps to better navigate through large information spaces.
Talk on June 11, 2013 by Andrea Scharnhorst at the IMT in Lucca, Italy.
An introduction to the Joint Information Systems Committee Resource Discovery iKit. Includes a look at controlled vocabularies declared in the Resource Discovery Framework (RDF)/Simple Knowledge Organisation System (SKOS) and wikipedia entries. Presented by Tony Ross at the CILIPS Centenary Conference Branch and Group Day which took place 5 Jun 2008.
Maths, Chemistry, Physics are very well suited for the Semantic Web, but very poorly represented. Here I show how valuable it can be and what (relatively little) needs to be dome
Keynote presentation for CSWS 2013 Conference in Shanghai, China.
Some slides borrowed from Jan Wielemaker, Guus Schreiber, Jacco van Ossenbruggen, Niels Ockeloen, Antske Fokkens, Serge ter Braake.
Hypertext2007 Wendy Hall - "Whatever Happened to Hypertext?"hypertext2007
Wendy Hall, Professor of Computer Science at the University of Southampton, UK. This is the slides of the speak she gave after the Hypertext 2007 Dinner in Manchester, UK on the 11th September 2007.
Visit http://www.ht07.org for more details
Presented at Journal Paper Track, The Web Conference, Lyon, France, April 15, 2018
https://doi.org/10.1145/3184558.3186234
Abstract: Linked Open Data (LOD) technology enables web of data and exchangeable knowledge graphs through the Internet. However, the change in knowledge is happened everywhere and every time, and it becomes a challenging issue of linking data precisely because the misinterpretation and misunderstanding of some terms and concepts may be dissimilar under different context of time and different community knowledge. To solve this issue, we introduce an approach to the preservation of knowledge graph, and we select the biodiversity domain to be our case studies because knowledge of this domain is commonly changed and all changes are clearly documented. Our work produces an ontology, transformation rules, and an application to demonstrate that it is feasible to present and preserve knowledge graphs and provides open and accurate access to linked data. It covers changes in names and their relationships from different time and communities as can be seen in the cases of taxonomic knowledge.
We propose Crop Vocabulary(CVO) as a basis of the core vocabulary of crop names that becomes the guidelines for data interoperability between agricultural ICT systems on the food chain. Since a single species is treated in different ways, there are many different types of crop names. So, we organize the crop name discriminated by properties such as scientific name, planting method, edible part and registered cultivar information. Also, Crop Vocabulary is also linked to existing vocabularies issued by Japanese government agency and international organization such as AGROVOC. It is expected to use in the data format in the agricultural ICT system.
Presented in 45th Asia Pacific Advanced Network (APAN45) Meeting, Singapore (2018)
Presented as the invited talk at International Workshop on kNowledge eXplication for Industry (kNeXI2017). In this talk, I explain the experience and lesson learnt how to build ontologies. I am currently building the agriculture activity ontology (AAO). It describes classification and properties of various activities in the agriculture domain. It is formalized with Description Logics.
Presented at the Interest Group on Agricultural Data (IGAD) ,3 April, 2017, Barcelona, Spain
Abstract: n this talk, we present the current status of our agriculture ontologies that are developed to accelerate the data use in agriculture.
The agriculture activity ontology formalizes the activities in agriculture. We have developed it for three years. Now we are developing its applications. One application is to exchange formats between different farmer management systems. Another ontology is the crop ontology that standardizes the names of crops. The structure is simple but has links to many other standards in distribution industry, food industry and so on.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
3. Knowledge is power
We have developed our society by/with
knowledge.
Then
How will we develop the society in the digital
era by/with knowledge?
4. Knowledge is power
Scientia est potentia.
- Sir Francis Bacon
"Pourbus Francis Bacon" by Frans Pourbus the younger - www.lazienki-krolewskie.pl. Licensed
under Public domain via Wikimedia Commons -
http://commons.wikimedia.org/wiki/File:Pourbus_Francis_Bacon.jpg#mediaviewer/File:Pourbu
s_Francis_Bacon.jpg
5. Knowledge is power in AI
• Edward Feigenbaum
– "father of expert systems“
– Knowledge is power, and the computer is an
amplifier of that power. We are now at the dawn
of a new computer revolution…
Knowledge itself is to become the
new wealth of nations.
"27. Dr. Edward A. Feigenbaum 1994-1997" by United States Air Force - United States Air Force.
Licensed under Public domain via Wikimedia Commons -
http://commons.wikimedia.org/wiki/File:27._Dr._Edward_A._Feigenbaum_1994-
1997.jpg#mediaviewer/File:27._Dr._Edward_A._Feigenbaum_1994-1997.jpg
http://www.computerhistory.org/fellowawards/hall/bios/Edward
,Feigenbaum/
6. Knowledge Acquisition Bottleneck
• How can we tell knowledge to computers?
– Knowledge Engineers & Domain Experts work together to
extract and transform knowledge good for computers. But
it is time-consuming, and always insufficient and
incomplete.
• How can we understand knowledge for computers?
– Transformed knowledge is often hard to understand.
• How can we maintain knowledge for computers?
– The real world is changing.
How to adapt it?
Who and how?
7. Knowledge Acquisition Bottleneck
• Solutions – how we can obtain knowledge
– Ontology
• Sharable, sustainable, and formal knowledge about the
world
– Learning
• Learning from the initial knowledge (supervised
learning)
• Learning from the real world (un-supervised learning)
They are still inside of the computational world. But what we’ve learnt
from the expert systems issue is the difficulty lies on the interface
between the computational world and the human society
8. Web comes
• World Wide Web creates the inforsphere that
everyone can contribute her/his information
http://www.flickr.com/photos/rorycellan/8314288381/
http://www.w3.org/2004/Talks/w3c10-HowItAllStarted
9. Semantic Web
Information Management: A Proposal
Tim Berners-Lee, CERN
March 1989, May 1990
Tim Berners-Lee, James Hendler and Ora
Lassila, "The Semantic Web", Scientific
American, May 2001, p. 29-37.
10. Semantic Web
• "The Semantic Web is an extension of
the current web in which information is
given well-defined meaning, better
enabling computers and people to work
in cooperation."
The Semantic Web, Scientific American, May 2001, Tim Berners-Lee, James Hendler
and Ora Lassila
11. Layers of Semantic Web
Tim Berners-Lee http://www.w3.org/2002/Talks/09-lcs-sweb-tbl/
12. Layers of Semantic Web
Tim Berners-Lee http://www.w3.org/2002/Talks/09-lcs-sweb-tbl/
Descriptions on classes
Descriptions on instances
Ontology
Linked Data
• Ontology
– Descriptions on classes
– RDFS, OWL
– Tasks
• Ontology building
– Consistency, comprehensiveness,
logicality
• Alignment of ontologies
13. Layers of Semantic Web
Tim Berners-Lee http://www.w3.org/2002/Talks/09-lcs-sweb-tbl/
Descriptions on classes
Descriptions on instances
Ontology
Linked Data
• Linked Data
– Descriptions on instances (individuals)
– RDF + (RDFS, OWL)
– Pros for Linked Data
• Easy to write (mainly fact description)
• Easy to link (fact to fact link)
– Cons for Linked Data
• Difficult to describe complex structures
• Still need for class description (-> ontology)
14. Linked Data Principle
• Use URIs as names for things
• Use HTTP URIs so that people can look up
those names.
• When someone looks up a URI, provide useful
information, using the standards (RDF*,
SPARQL)
• Include links to other URIs. so that they can
discover more things.
20. 570 datasets,
Last updated: 2014-08-30
Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/
20
22. LODAC (LOD for Academia) Project 2011-2016
• Collect and publish academic data as LOD
LODAC SPECIES: Linking species-related data by name
Specimen
DB
Species
Info. DB
Taxon
Name DBGBIF BioSci.
DB
Category
DB
Names: 113118
Triples:14,532,449
Data from Source BIntegrated data
dc:references dc:references
dc:references dc:references
dc:references dc:references
dc:creator
dc:creator
crm:P55_has_current_location
crm:P55_has_current_location
crm:P55_has_current_location
dc:creator
Data from Source A
Work
Museum
Creator
Minimum Data to identify entitiesRaw Data for entities Raw Data for entities
Query expansion App.
CKAN (Japanese):
Dataset registry
DBPedia Japanese
LODAC Museum: Collecting and Linking museum data
23. LODAC Museum
• Purpose
– Enable creation, publishing, sharing and reuse of collection information
distributed to each museum by introducing LOD.
– Enable to uniquely identify resources such as works, creators, and
institutions, and relations between those on the web
• Activities
– Integrate and share collection data aggregated from data sources as RDF.
– Provide applications using generated LOD.
• Data sources
– Collection data obtained from websites of 114 museums.
– The Database of Japan Arts Thesaurus
– The database of government-designated cultural property
– Cultural Heritage Online Work Creator
Institution
Resources
Over 40
millions
triples
25. Yokohama Art Spot
• provides information on art around Yokohama.
– is a good example of how such efforts by local
people can be rewarded by flexible use of the
provided data.
LODAC Museum × Yokohama Art LOD × PinQA
Museum Collection Local Event Information Q&A
ical:location
RDF
store
SPARQL
endpoint
LODAC Museum
OWLIM SE
artwork
institution
creator
User Yokohama Art Spot
HTML
JavaScript
Python
SPARQLWrapper
RDF
store
SPARQL
endpoint
Yokohama Art LOD
ARC2
RDF
store
SPARQL
endpoint
PinQA
event
question
institution
creator
answer
user
F. Matsumura, I. Kobayashi, F. Kato, T. Kamura, I. Ohmukai and H.Takeda:Producing and
Consuming Linked Open Data on Art with a Local Community, J. F. Sequeda, A. Harth and O.
Hartig eds., Proceedings of the Third International Workshop on Consuming Linked Data
(COLD 2012) (2012), CEUR Workshop Proceedings Vol-905.
[COLD12]
27. LODAC Species: Interlinking species data
• Taxon names: 443,248
• Scientific name: 226,141
• Common name: 219,865
• hasScientificName property
node: 87,160
• hasCommonName property
node: 84,610
Y. Minami, H. Takeda1, F. Kato, I. Ohmukai, N. Arai, U. Jinbo, M. Ito, S.
Kobayashi and S. Kawamoto: Towards a Data Hub for Biodiversity with
LOD, H. Takeda, Y. Qu, R. Mizoguchi and Y. Kitamura eds., Semantic
Technology - Second Joint International Conference, JIST 2012, Nara,
Japan, December 2-4, 2012. Proceedings, Vol 7774 ofLNCS, pp 356–
361, Springer (2013).
• Integrating species databases as linked data
[JIST12]Specimen
rdf:type
species
institutionName
collectedDate
collectionLocality
crm:has_current_location
Bryophytes
TaxonName
ScientificName
CommonName TaxonRank
species
rdfs:subClassOf
rdfs:subClassOf
rdf:type
rdf:type
hasCommonName
hasScientificName hasSuperTaxon
rdf:type
hasTaxonRank
rdf:type
hasTaxonRank
rdf:type
Butterfly
BDLS
dcterms:source
dcterms:publisher
: Named Graph
: owl:Class
Named Graph for
the data sources
28.
29. An Application:
Query expansion for paper search
Input species
name
Papers include
species name
Papers include same genus
species
Papers include
common name
40. Our Society (real world)
Computational World
We’ve just dealt with knowledge fitted to the computational world
41. Three challenges to fill the gap
• Representation of Scientific Names
– Knowledge revision
• Agriculture Ontology
– Integration of domain specific terms
• Core Vocabulary
– Integration of terms across domains
43. Dynamics of Scientific Name
• Scientific name looks unique, but more precisely
unique as long as the current knowledge
– Scientific name changes in time according to new
scientific discovery
– Information on species is described with names in
some time (not always now)
• How to represent information with knowledge
revision?
44. Northern Oriole
These birds are found in the Nearctic in
summer, primarily the eastern United
States.
44
Challenge
52. Event-Centric Model for Taxon Revision
- case: merge of two families -
• At time t1, Buidae is merged into Audiae.
ltk:Taxon
Merger
ltk:Change
HigherTaxon
ex:merge1 ex:reclass1
ex:event1
rdf:type rdf:type
cka:interval
“t1”
“t2”
tl:beginsAt
DateTime
tl:endsAt
DateTime
cka:effect
ex:Auidae_1
ex:Buidae_1
ex:Auidae_2
ex:Xus_1
(OPR) (OPR)
(opr)(opr)
(con)
(con)
(con)
(con)
(event)
Event-Centric Model
Different URIs
URI
URI
URI
URI
URI : URI for taxon concept
Taxon concept = Taxon + Synonym
54. Generating simpler descriptions
- From Event-centric model to Snapshot model -
• Just show the current names
ltk:Change
HigherTaxon
ex:reclass1
rdf:type
cka:Relationship
Evolution
rdfs:subClassOf
ltk:higherTaxon
cka:relation
ltk:higher
Taxon
ex:event1
cka:interval
“t1”
“t2”
tl:beginsAt
DateTime
tl:endsAt
DateTime
ex:Auidae_2
ex:Xus_1
ex:Xus_1
ex:Buidae_1
ex:Auidae_2
cka:assures
(OPR)
(opr)
(event)
(con)
(con)
(con)
(con)
(con)
rule
Event-Centric Model Snapshot Model
ex:inv1
ex:inv1
“t1” “t2”
tl:endsAt
DateTime
tl:beginsAt
DateTime
(the name of the graph)
(named graph)
URI
URI
URI
URI
URI
59. Standardization of Agricultural Activities
Background
Issues
Purpose
Agricultural IT systems are widely adopted to manage and record activities
in the fields efficiently. Interoperability among these systems is needed to
integrate and analyze such records to improve productivity of agriculture.
To provide the standard vocabulary by defining the ontology for agricultural
activity
Data in agricultural IT systems is
not easy to federate and integrate
due to the variety of the languages
It prevents federation and
integration of these systems and
their data.
http://www.toukei.maff.go.jp/dijest/kome/kome05/kome05.html
しろかき
“Puddling”
砕土
“Pulverization”
代かき
“Puddling”
代掻き
“Puddling”
代掻き作業
“Puddling Activity”
荒代(かじり)
“Coarse pudding”
荒代かき
“Coarse pudding”
整地
“Land grading”
均平化
“land leveling”
60. AGROVOC
Thesaurus
AGROVOC organizes words by synonym, narrower/broader, and related
relationship.
harvesting topping(beets)
baling
gleaning
mechanical harvesting
mowing
AGROVOC
. . .
Narrower/broader relationship
is not clearly defined. So
relationship among bother
words are often mixed and
misunderstood.
relationship
between
siblings
AGROVOC is the most well-known vocabulary in agriculture supervised by
Food and Agriculture Organization(FAO) and the thesaurus containing
more than 32,000 terms of agriculture, fisheries, food, environment and
other related fields.
The number of activity names about rice farming, which is important in
Asia including Japan, are insufficient.
61. Lessons learnt – What should be considered
Define hierarchy clearly
Accept various synonymous words
Hierarchy is convenient for human to understand and for computers to
process. But it often be confused by mixing different criteria on relationship
among concepts/words. It causes difficulty when adding new concepts/words
and when integrating different hierarchies.
Names for a single concept may be multiple by region and by crop
Define relationship clearly between upper
and lower concepts as basis of classification
Clarify an entry word and their synonyms for each concept
harvesting topping(beets)
baling
gleaning
mechanical harvesting
mowing
Thesaurus
(AGROVOC)
. . .
harvesting mechanical harvesting
manual harvesting
[means]. . .
Harvest Harvest
Harvest
Inherit
byMachine
manually
+
+
relationship
between
siblings
Representation: ”Harvesting”
[means][Act]
Ontology!
62. Define activity concepts
Define hierarchy
Seeding:
activity to sow seeds on fields for seed propagation.
Purpose: seed propagation
Place : field
Target : seed
Act : sow
“Seeding”
Define activities with
properties and their values
The hierarchy of activities is organized by property
- New properties and their values are added
- “purpose”, “act”, “target”, “place”, “means” , “equipment”, “season”,
and “crop” in order.
- Property values are specialized
Seeding
property value
Designing of Agricultural Activity Ontology(AAO)
63. Formalization by Description Logics
Crop production activity
Crop growth activity
purpose:crop production
purpose:crop growth
Agricultural activity
Activity for control of
propagation
Activity for seed
propagation
purpose:control of propagation
purpose:seed propagation
Seeding
act : sow
target:seed
place:field
Activity for seed
propagation
Seeding
Designing of Agricultural Activity Ontology(AAO)
64. Differentiate concepts by property
purpose : seed propagation
place : paddy field
target : seed
act : sow
crop:rice
purpose : seed propagation purpose : seed propagation
place : field
target : seed
act : sow
Agricultural activity >…> Activity for seed propagation > Seeding
purpose : seed propagation
place : well-drained paddy field
target : seed
act : sow
crop:rice
Direct sowing of rice on well-drained paddy field Direct seeding in flooded paddy field
Well-drained paddy field < field paddy field < field
Designing of Agricultural Activity Ontology(AAO)
65. Activity for seeding Direct seeding in flooded paddy field
Direct sowing of rice on well-drained paddy field
Seeding on nursery box
The Structuralizaion of the Agricultural Activities (Protégé)
Designing of Agricultural Activity Ontology(AAO)
66. Polysemic concepts
[disjunction form]
[conjunction form]
Pudlling
Subsoil breaking
PulverizationLand preparation
Water retention
Activity for water
management
Land leveling
Polysemic
relationship
Pulverization by
harrow
purpose : pulverization
purpose : water retention
purpose : land leveling
Definition of agriculture activities with multiple purposes or other
properties.
Puddling
Designing of Agricultural Activity Ontology(AAO)
67. Water retention
Land leveling Pulverization
Puddling
Polysemic concepts (Protégé)
Designing of Agricultural Activity Ontology(AAO)
68. Reasoning by Ontology
Reasoning by Agriculture Activity Ontology
Activity for
biotic control
Activity for
suppression of
pest animals
Activity for
suppression of pest
animals by physical
means
control of
pest animals
Physical
means
means
(0,1)
purpose
(0,1)
Biotic control
purpose(0,1)
Activity for
suppression of pest
animals by chemical
means
Chemical
means
purpose
(0,1)
means
(0,1)
Making
scarecrow‘
suppression
of pest
animals
Purpose
(0,1)
build
act
(0,1)
scarecrow
target
(0,1)
Physical
means
Means
(0,1)
? Example of「Making scarecrow」
?
suppression
of pest
animals
Infer the most feasible upper concept for the given constraints for a new words
69. Reasoning by Ontology
かかし作り
物理的手段
means
(0,1)
means
(0,1)
Inference with SWCLOS
[1] Seiji Koide, Theory and Implementation of Object Oriented Semantic Web Language,
PhD Thesis, Graduate University for Advance Studies, 2011
[1]
[1]
Activity for
biotic control
Activity for
suppression of
pest animals
Activity for
suppression of pest
animals by physical
means
control of
pest animals
Physical
means
means
(0,1)
purpose
(0,1)
Biotic control
purpose(0,1)
suppression
of pest
animals
Activity for
suppression of pest
animals by chemical
means
Chemical
means
purpose
(0,1)
means
(0,1)
Making
scarecrow
make
act
(0,1)
scarecrow
target
(0,1)
Infer the most feasible upper concept for the given constraints for a new words
Reasoning by Agriculture Activity Ontology
Making scarecrow is a subclass of Activity for
suppression of pest animals by physical means
71. Web Services based on Agriculture Activity Ontology
Converting synonyms to core vocabulary
http://www.tanbo-kubota.co.jp/foods/watching/14_2.html
“Puddling Activity”
“sowing”
…
AAO
Puddling
Seeding
…
Converting
[system]
API
Puddling Activity
and sowing…
[system’]
Puddling
and seeding…
72. http://cavoc.org/
Common Agricultural VOCabulary
Agriculture Activity Ontology (AAO) ver 1.31
http://cavoc.org/aao/
Agriculture Activity Ontology(AAO): Summary
• Standardize the vocabulary for agricultural activities with the logical
model
• Define concepts of agriculture activities beyond
• Conceptual variety (often dependent to crop and farm style)
• Linguistic diversity (often dependent to crop and area)
• adopted as the part of ”the guideline for agriculture activity names
for agriculture IT systems” issued by Ministry of Agriculture, Forestry
and Fisheries (MAFF), Japan in 2016,
77. Information needed to register new cooperation
Managed by multiple agencies
Different formats
Lack of linkage
78. Local
Government User
User
Company
Company
Local
Government
Government
Company
Product
Name
Code Maker Buyer
Name
Organization Product
Name Address Name Code
Product
Nmae
Product
Code
Price Purcha
se
Date
Maker
Public Vocabulary Framework project
- Infrastructure for Multilayer Interoperability (IMI) -
• Sharing terms
– among administration units
– among administration unites and companies
– among administration units, companies and users
79. Public Vocabulary Framework project
- Infrastructure for Multilayer Interoperability (IMI) -
• A framework that enables exchange of data by sharing primary
vocabulary.
– Provide basic common concepts
• A core and domains
• Extensible vocabulary (application vocabularies)
– For Open data and data exchanges between systems
• RDF, XML, and texts
82Citizen ID Enterprise ID Character-set
Vocabulary
Share, Exchange, Storage
(Format)
Applications
IMI
80. Vocabulary structure of IMI
• IMI consists of core vocabulary, cross domain vocabulary and
domain-specific vocabularies.
Core
Vocabulary
Domain-specific Vocabularies
Vocabularies that are specialised for
the use in each domain.
Eg) number of beds, Schedule.
Shelter
Location
Hospital
Station
Disaster
Restoration
Cost
Core Vocabulary
Universal vocabularies that are widely used
in any domain.
Eg) people, object, place, date.
Geographical Space
/Facilities
Transportation
Disaster
Prevention
Finance
Domain-specific
Vocabularies
81.
82. Image of IMI vocabulary
• Vocabulary set and Information Exchange
Package are defined in trial area.
85
項目名 英語名 データタイプ 項目説明 項目説明(英語) キーワード サンプル値 Usage Info
人 PersonType
氏名 PersonName PersonNameType 氏名 Name of a Person -
性別 Gender
<abstract element,
no type>
性別 Gender of a Person -
Substitutable
Elements:
性別コード GenderCode CodeType 性別のコード Gender of a Person 1
APPLIC標準仕様V2.3
データ一覧
住民基本台帳:性別
引用
性別名 GenderText TextType 性別 Gender of a Person 男
現住所 PresentAddr
ess
AddressType 現住所 -
本籍 AddressType 本籍 -
… … … … … … … … …
… … … … … … … … …
項目名(Type/Sub-properties) 英語名 データタイプ …
氏名 PersonNameType
氏名 FullName TextType
フリガナ TextType
姓 FamilyName TextType
カナ姓 TextType
… … …
AED
Location
Address
LocationTwoDimensional
GeographicCoordinate
Equipment
Information
Spot of
Equipment
Business Hours
Owner
Access
Availability
User
Day of
Installation
Homepage
AED
Information
Type of Pad
Expiry date
Contact
Type
Model Number
SerialNumber
Photo
Note
Information
Source
Sample 1 : Definition of vocabulary
Sample 2 : Information Exchange Package
83. Adaptation by (local) Governments
• Ministry of Economics, Trade, and Industries (METI):
Corporate Information Portal
• Local Governments:
– Mori Town, Yakumo Town [Hokkaido]
– Hirono Town, [Iwate]
– Ishinomaki [Miyagi]
– Ota City [Gunma]
– Kawaguchi City [Saitama]
– Kanazawa-Ward (Yokohama City) [Kanagawa]
– Shizuoka City [Shizuoka]
– Tsuruga City [Fukui]
– Osaka City [Osaka]
– Oku-izumo Town, Yasugi City [Shimane]
– Tokushima Pref., Awa City [Tokushima]
– Ube City [Yamaguchi]
– …
84. Corporate Information portal website
Corporate number
Corporate Name
Corporation Type
Area
Resource
Search
Government
Registers
Applications
Gather the data
by using IMI based data structure
Corporation
85. Benefit of the website
CSV
PDF
RDF
Open Data
Other websites
New
ServicesAPI
Knowledge base
for all government department
86. Adaption by Corporate Information Portal
• This website uses the IMI core vocabulary that is national standard vocabulary
project for interoperability.
• The IMI define basic data items. (Name, Address, Corporation, Facility, - - - )
• corporateBusinessinfo
• corporateActivityInfo
hj:Corporate information
Type
• name(en)
• codeOfIndustry
• objectiveOfBusiness
• abstractOfBusiness
• areaOfBusiness
• stakeholder
• majorStockHolder
• financialInformation
• ・・・
hj:Corporate business
information Type
• adressNumber
hj:Address Type
• noOfStock
• holder
• ratio
hj:Stock holder Type
• ・・・
hj:Subsidy Type
• ・・・
hj:Award Type
• ・・・
hj:Certification Type
• ・・・
hj:Contact Type
• typeOfNote
• memo
hj:Note Type
• positionOfOrgtype
• organizationType
• capiltal
• noOfEmployee
ic:Corporation
Type
• ・・・
ic: Address Type
• dateOfCertification
• title
• category
• block
• area
• type
hj:Corporate activity Type
• target
• reason
• amount
• status
• period
• note
IMI
Core
Vocabulary
Corporate Information
Domain Vocabulary• ID
• name
• abbreviation
• alternativeName
• status
• abstract
• contactInformation
• relatedOrganization
• place
• address
• representative
• dateOfEstablishment
• additionalInformation
ic:Organization Type
• businessDomain
• startDateOfFy
• noOfMember
• agent
ic:Business unit Type
enhance
refer
87. Public Vocabulary Framework project
- Infrastructure for Multilayer Interoperability (IMI) -
• Towards interoperability beyond regions
– Community of Practice on Core Data Models
• Sharing good practice
• Mapping between core vocabularies
• DG Informatics (EC)
• IMI (Japan)
• NIEM (USA)
NIEM
ISA
JoinUp
UN
CEFACT
IMI
90. Our Society (real world)
Computational World
New Technical development
Challenge #1
91. Our Society (real world)
Computational World
Forming new knowledge
Challenge #2
92. Our Society (real world)
Computational World
Forming Structure in Society
Challenge #3
93. Lessons learnt from the challenges
The challenges are
not just in the computational world
rather
between the computational and the real worlds
even
in the real world
We must be socio-computer scientists
94. Summary
Semantic Web created the first step for
knowledge representation in the computer
world
But the computational world alone is not
enough. We should commit (or even change)
both the computational and real world to real
“knowledge is power” world. In order to do so,
we must work with people in our society.
However, the linked taxonomic name is not enough. The synonym name may lead to the incorrect knowledge if a reader doesn’t know the background knowledge of that synonym. Sometimes the synonym comes from a change of taxonomic classification.
For example, a case study of species Icterus galbula (Linnaeus, 1758) and Icterus bullockii (Swainson, 1827) that merged and split many times.
Icterus galbula has been flound since 1758
Icterus bullockii has been flound since 1827
the Baltimore Oriole, of the eastern United States
and Bullock’s Oriole, living in the western US,
were merged as one species, the Northern Oriole in the 1960s.
The merge was based on the fact they interbreed often and produce fertile offspring.
Because the name “galbula ” is the former name, it becomes an accepted name.
So, these name are synonym.
I galbula is a senior synonym whereas I. bullockii is a jounior synonym.
Of course, knowledge of these name must be combined together.
Moreover, after this day, if some researchers discovered new knowledge of this bird, they would record the new information a long with this name.
A problem with this lump was that Bullock’s Orioles are more closely related to other species of orioles rather than
Baltimore Orioles.
So, they split this name again to be “galbula” and “bullockii”.
If we need to find information of the “galbula”, we can query by this name.
However, some information from year 1960 include knowledge of “bullockii”.
In the other hand,
Some information about “bullockii” are missing, because some knowledge between 1960 and 1995 are recorded with the name “galbula”.
Therefore, the correct temporal context of concepts and reasons of their changes becomes necessity for understanding a taxon concept as well.