ICAR 2015
Workshop 10 (TUESDAY, JULY 7, 2015, 4:30-6:00 PM)
The Arabidopsis information portal for users and developers
Agnes Chan (J. Craig Venter Institute)
A Guided Tour of Araport
ICAR 2015
Workshop 10 (TUESDAY, JULY 7, 2015, 4:30-6:00 PM)
The Arabidopsis information portal for users and developers
Agnes Chan (J. Craig Venter Institute)
A Guided Tour of Araport
This presentation looks in detail at SPARQL (SPARQL Protocol and RDF Query Language) and introduces approaches for querying and updating semantic data. It covers the SPARQL algebra, the SPARQL protocol, and provides examples for reasoning over Linked Data. We use examples from the music domain, which can be directly tried out and ran over the MusicBrainz dataset. This includes gaining some familiarity with the RDFS and OWL languages, which allow developers to formulate generic and conceptual knowledge that can be exploited by automatic reasoning services in order to enhance the power of querying.
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
In this presentation, we describe the underlying principles of the Semantic Web along with the core concepts and technologies, how they fit in with the Grails Framework and any existing tools, API\'s and Implementations.
Getting the best of Linked Data and Property Graphs: rdf2neo and the KnetMine...Rothamsted Research, UK
Graph-based modelling is becoming more popular, in the sciences and elsewhere, as a flexible and powerful way to exploit data to power world-changing digital applications. Com- pared to the initial vision of the Semantic Web, knowledge graphs and graph databases are be- coming a practical and computationally less formal way to manage graph data. On the other hand, linked data based on Semantic Web standards are a complementary, rather than alternative, ap- proach to deal with these data, since they still provide a common way to represent and exchange information. In this paper we introduce rdf2neo, a tool to populate Neo4j databases starting from RDF data sets, based on a configurable mapping between the two. By employing agrigenomics- related real use cases, we show how such mapping can allow for a hybrid approach to the man- agement of networked knowledge, based on taking advantage of the best of both RDF and prop- erty graphs.
Health Datapalooza IV: June 3rd-4th, 2013
Open Government Data
Moderator:
George Thomas, Enterprise Architect, Office of the Chief Information Officer (CIO), U.S. Department of Health & Human Services
Speakers:
John Erickson, Director of Web Science Operations, Tetherless Word Constellation, Rensselaer Polytechnic Institute
James P. McCusker, Ph.D Student, Dept. of Computer Science, Rensselaer Polytechnic Institute
Mark Musen, Professor, Stanford University and Principal Investigator, National Center for Biomedical Ontologies
Natasha Noy, Senior Research Scientist, Stanford University and Executive Committee Member, National Center for Biomedical Ontologies
Michael Pendleton, Linked Open Data Manager, US Environmental Protection Agency
The session will open with an overview of trends affecting open data sharing, including ‘broad data’ challenges that emerge when application developers have millions of open government datasets available. We will explore issues of web-scale data discovery, rapid and potentially ad hoc integration, visualization, and analysis of partially modeled datasets as well as issues arising from combining different data use policies. We will present emerging solution standards and transitioning academic technologies, including innovative work conducted by the ‘Watson’ research group at Rensselaer Polytechnic Institute on using Watson as a ‘data advisor’. Panelists will synthesize session topics including optimal steps toward an open health knowledge graph facilitating ‘data liquidity’ (as defined by the ability to easily combine and refine data from disparate publishers). Panelists will discuss enabling the implementation of effective ‘lifting schemes’ by leveraging ‘collaboration without coordination’ processes to produce efficient data access techniques that drive innovative new application development tools, products, and services.
Introduction of semantic technology for SAS programmersKevin Lee
There is a new technology to express and search the data that can provide more meaning and relationship –
semantic technology. The semantic technology can easily add, change and implement the meaning and relationship
to the current data. Companies such as Facebook and Google are currently using the semantic technology. For
example, Facebook Graph Search use semantic technology to enhance more meaningful search for users.
The paper will introduce the basic concepts of semantic technology and its graph data model, Resource Description
Framework (RDF). RDF can link data elements in a self-describing way with elements and property: subject,
predicate and object. The paper will introduce the application and examples of RDF elements. The paper will also
introduce three different representation of RDF: RDF/XML representation, turtle representation and N-triple
representation.
The paper will also introduce “CDISC standards RDF representation, Reference and Review Guide” published by
CDISC and PhUSE CSS. The paper will discuss RDF representation, reference and review guide and show how
CDISC standards are represented and displayed in RDF format.
The paper will also introduce Simple Protocol RDF Query Language (SPARQL) that can retrieve and manipulate data
in RDF format. The paper will show how programmers can use SPARQL to re-represent RDF format of CDISC
standards metadata into structured tabular format.
Finally, paper will discuss the benefits and futures of semantic technology. The paper will also discuss what semantic
technology means to SAS programmers and how programmers take an advantage of this new technology.
Overview of the SureChEMBL system and web interface.
https://www.surechembl.org/search/
SureChEMBL is a freely available web resource for chemistry patent searching. It is based on a fully automatic and dynamic text and image mining pipeline.
This presentation looks in detail at SPARQL (SPARQL Protocol and RDF Query Language) and introduces approaches for querying and updating semantic data. It covers the SPARQL algebra, the SPARQL protocol, and provides examples for reasoning over Linked Data. We use examples from the music domain, which can be directly tried out and ran over the MusicBrainz dataset. This includes gaining some familiarity with the RDFS and OWL languages, which allow developers to formulate generic and conceptual knowledge that can be exploited by automatic reasoning services in order to enhance the power of querying.
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
In this presentation, we describe the underlying principles of the Semantic Web along with the core concepts and technologies, how they fit in with the Grails Framework and any existing tools, API\'s and Implementations.
Getting the best of Linked Data and Property Graphs: rdf2neo and the KnetMine...Rothamsted Research, UK
Graph-based modelling is becoming more popular, in the sciences and elsewhere, as a flexible and powerful way to exploit data to power world-changing digital applications. Com- pared to the initial vision of the Semantic Web, knowledge graphs and graph databases are be- coming a practical and computationally less formal way to manage graph data. On the other hand, linked data based on Semantic Web standards are a complementary, rather than alternative, ap- proach to deal with these data, since they still provide a common way to represent and exchange information. In this paper we introduce rdf2neo, a tool to populate Neo4j databases starting from RDF data sets, based on a configurable mapping between the two. By employing agrigenomics- related real use cases, we show how such mapping can allow for a hybrid approach to the man- agement of networked knowledge, based on taking advantage of the best of both RDF and prop- erty graphs.
Health Datapalooza IV: June 3rd-4th, 2013
Open Government Data
Moderator:
George Thomas, Enterprise Architect, Office of the Chief Information Officer (CIO), U.S. Department of Health & Human Services
Speakers:
John Erickson, Director of Web Science Operations, Tetherless Word Constellation, Rensselaer Polytechnic Institute
James P. McCusker, Ph.D Student, Dept. of Computer Science, Rensselaer Polytechnic Institute
Mark Musen, Professor, Stanford University and Principal Investigator, National Center for Biomedical Ontologies
Natasha Noy, Senior Research Scientist, Stanford University and Executive Committee Member, National Center for Biomedical Ontologies
Michael Pendleton, Linked Open Data Manager, US Environmental Protection Agency
The session will open with an overview of trends affecting open data sharing, including ‘broad data’ challenges that emerge when application developers have millions of open government datasets available. We will explore issues of web-scale data discovery, rapid and potentially ad hoc integration, visualization, and analysis of partially modeled datasets as well as issues arising from combining different data use policies. We will present emerging solution standards and transitioning academic technologies, including innovative work conducted by the ‘Watson’ research group at Rensselaer Polytechnic Institute on using Watson as a ‘data advisor’. Panelists will synthesize session topics including optimal steps toward an open health knowledge graph facilitating ‘data liquidity’ (as defined by the ability to easily combine and refine data from disparate publishers). Panelists will discuss enabling the implementation of effective ‘lifting schemes’ by leveraging ‘collaboration without coordination’ processes to produce efficient data access techniques that drive innovative new application development tools, products, and services.
Introduction of semantic technology for SAS programmersKevin Lee
There is a new technology to express and search the data that can provide more meaning and relationship –
semantic technology. The semantic technology can easily add, change and implement the meaning and relationship
to the current data. Companies such as Facebook and Google are currently using the semantic technology. For
example, Facebook Graph Search use semantic technology to enhance more meaningful search for users.
The paper will introduce the basic concepts of semantic technology and its graph data model, Resource Description
Framework (RDF). RDF can link data elements in a self-describing way with elements and property: subject,
predicate and object. The paper will introduce the application and examples of RDF elements. The paper will also
introduce three different representation of RDF: RDF/XML representation, turtle representation and N-triple
representation.
The paper will also introduce “CDISC standards RDF representation, Reference and Review Guide” published by
CDISC and PhUSE CSS. The paper will discuss RDF representation, reference and review guide and show how
CDISC standards are represented and displayed in RDF format.
The paper will also introduce Simple Protocol RDF Query Language (SPARQL) that can retrieve and manipulate data
in RDF format. The paper will show how programmers can use SPARQL to re-represent RDF format of CDISC
standards metadata into structured tabular format.
Finally, paper will discuss the benefits and futures of semantic technology. The paper will also discuss what semantic
technology means to SAS programmers and how programmers take an advantage of this new technology.
Overview of the SureChEMBL system and web interface.
https://www.surechembl.org/search/
SureChEMBL is a freely available web resource for chemistry patent searching. It is based on a fully automatic and dynamic text and image mining pipeline.
"Methodology for Assessment of Linked Data Quality: A Framework" at Workshop on Linked Data Quality
Paper: https://dl.dropboxusercontent.com/u/2265375/LDQ/ldq2014_submission_3.pdf
"Using Linked Data to Evaluate the Impact of Research and Development in Europe: A Structural Equation Model" presented at ISWC 2013 (http://link.springer.com/chapter/10.1007/978-3-642-41338-4_16)
Presentation for I-Semantics 2013 conference on "User-driven Quality Evaluation of DBpedia", link to full paper: http://svn.aksw.org/papers/2013/ISemantics_DBpediaDQ/public.pdf.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
10. Filter in SPARQL
• Keyword FILTER, followed by filter expression in parentheses
• Filter condiFons output truth values (and possibly errors)
• Many filter funcFons are not specified by RDF
funcFons
• partly taken from XQuery/XPath-Standard for XML
11. Filter Functions
Comparison operators: <, =, >, <=, >=, !=
• Comparison of data literals according to natural order
• Support for numerical data types, xsd:dateTime, xsd:string
(alphabeFc ordering), xsd:Boolean (1>0)
• For other types and other RDF-elements, only = and != are
available
• Comparison of literals of incompaFble types (e.g. xsd:string and
xsd:integer) is not allowed
ArithmaFc operators: +, -, *, /
• Support for numerical data types
• Used to combine values in filter condiFons Ex.: FILTER(?weight/
(?size*?size)>=25)
18. Resulting Sorting
• SorFng same as with filter comparison operators
• SorFng of URIs alphabeFcally as sequence of characters
Other possible specificaFons:
• ORDER BY DESC(?price): descending
• ORDER BY ASC(?price): ascending, default seong
• ORDER BY DESC(?price), ?Ftle: hierarchical classificaFon criteria
19. LIMIT, OFFSET, DISTINCT
RestricFon of output set:
• LIMIT: maximal number of results (table rows)
• OFFSET: posiFon of the first delivered result
• SELECT DISTINCT: removal of duplicate table rows
LIMIT and OFFSET only make sense with ORDER BY!
23. Hands-on Bio2RDF - 3
SELECT * WHERE {
?drug a
<http://bio2rdf.org/drugbank_vocabulary:Drug>. }
• filter for drugs starting with A
24. Hands-on Bio2RDF -3
SELECT * WHERE {
?drug a
<http:bio2rdf.orgdrugbank_vocabulary:Drug>. }
• filter for drugs starting with A
• FILTER regex(?title, "A")
25. Hands-on Bio2RDF -3
SELECT * WHERE {
?drug a
<http://bio2rdf.org/drugbank_vocabulary:Drug>. }
• filter for drugs starting with A
• FILTER regex(?title, “A")
• sort them alphabetically
26. Hands-on DIY
• Get 100 drug-metabolizing enzymes
• Get phenotypes and genes associated with
OMIM diseases
• Retrieve unique diseases and publications
associated with the BRCA1 gene
27. Hands-on DIY
• Get 100 drug-metabolizing enzymes
• Get phenotypes and genes associated with
OMIM diseases
• Retrieve unique diseases and publications
associated with the BRCA1 gene
TIPS:
- View the resource as NTriples to construct your query
- Use prefix.cc to look up prefixes
- Always use LIMIT
- Start by getting results one triple at a time and build up.