Bio2RDF Release 2 is an updated version that provides improved coverage of life science linked data through additional datasets and properties. It features open source conversion scripts, a common URI pattern for integration, and dataset provenance information. The release includes 19 datasets with over 1 billion RDF triples that can be queried using SPARQL endpoints or through federated queries across datasets using the Semanticscience Integrated Ontology. Future work aims to incorporate additional large datasets and consolidate provenance.
“Cloud BioLinux:Standardized, Pre-Configured and On-Demand
Computing for Genomics and Beyond
”. Genomics Standards Consortium Conference 2010, European Bioinformatics Institute, Hinxton, UK
Niche Investor Relations and financial sector marketing consultancy which helps GCC based corporations communicate effectively with their stakeholders.
ARINDON services are aimed at providing clients with Investor Relations strategy and roadmap aimed at improving attractiveness and client perception to target audience.
How the Tablet Shopping Experience Will Impact Holiday Retail SalesUserZoom
Join UserZoom's UX Researcher, Sneha Kanneganti, and Alfonso de la Nuez, Co-CEO, in a new webinar that presents the results involving three well-known winter season retail brands: Columbia Sportswear, The North Face and Under Armour.
“Cloud BioLinux:Standardized, Pre-Configured and On-Demand
Computing for Genomics and Beyond
”. Genomics Standards Consortium Conference 2010, European Bioinformatics Institute, Hinxton, UK
Niche Investor Relations and financial sector marketing consultancy which helps GCC based corporations communicate effectively with their stakeholders.
ARINDON services are aimed at providing clients with Investor Relations strategy and roadmap aimed at improving attractiveness and client perception to target audience.
How the Tablet Shopping Experience Will Impact Holiday Retail SalesUserZoom
Join UserZoom's UX Researcher, Sneha Kanneganti, and Alfonso de la Nuez, Co-CEO, in a new webinar that presents the results involving three well-known winter season retail brands: Columbia Sportswear, The North Face and Under Armour.
Progettazione e sviluppo del prototipo di una app per l'apprendimento del linguaggio nei bambini sotto i 36 mesi.
Creazione di interfaccia mamma e bambino, ottimizzate per gli utenti.
Riconoscimento automatico dell'utente (context awareness)
Ubiquitous and Context aware computing - Università degli Studi di Milano - Bicocca
Understanding Android Handling of Touch Eventsjensmohr
Showing how Android handles Touch Events by means of extending an ExpandableListView with a swipe gesture. I am explaining which problems I encountered and how I solved them.
Mobile note mobile by MAdvertise et BemobeeFranck Deville
2017 démarre très fort avec toujours plus de nouveautés et de challenges relevés.
De nombreux bilans annuels sur 2016 sont publiés et mettent en évidence un marché mobile toujours aussi fleurissant.
Madvertise vous récapitule les dernières tendances, exclusivités, acquisitions,...
Consultez l'ensemble des articles et chiffres clés réunis en un condensé 100% mobile en PJ.
Comparison of Jacob's Creek, Rosemount Estate, McGuigan Wines, Lindeman's and...Unmetric
Take a deep dive into the social media activities of the top wine brands in Australia on Facebook. Discover how brands like Lindeman's wines and Champagne Taittinger engage their audience with shareable content and social media campaigns.
Bio2RDF is an open-source project that offers a large and
connected knowledge graph of Life Science Linked Data. Each dataset is expressed using its own vocabulary, thereby hindering integration, search, query, and browse data across similar or identical types of data. With growth and content changes in source data, a manual approach to maintain mappings has proven untenable. The aim of this work is to develop a (semi)automated procedure to generate high quality mappings
between Bio2RDF and SIO using BioPortal ontologies. Our preliminary results demonstrate that our approach is promising in that it can find new mappings using a transitive closure between ontology mappings. Further development of the methodology coupled with improvements in
the ontology will offer a better-integrated view of the Life Science Linked Data
Progettazione e sviluppo del prototipo di una app per l'apprendimento del linguaggio nei bambini sotto i 36 mesi.
Creazione di interfaccia mamma e bambino, ottimizzate per gli utenti.
Riconoscimento automatico dell'utente (context awareness)
Ubiquitous and Context aware computing - Università degli Studi di Milano - Bicocca
Understanding Android Handling of Touch Eventsjensmohr
Showing how Android handles Touch Events by means of extending an ExpandableListView with a swipe gesture. I am explaining which problems I encountered and how I solved them.
Mobile note mobile by MAdvertise et BemobeeFranck Deville
2017 démarre très fort avec toujours plus de nouveautés et de challenges relevés.
De nombreux bilans annuels sur 2016 sont publiés et mettent en évidence un marché mobile toujours aussi fleurissant.
Madvertise vous récapitule les dernières tendances, exclusivités, acquisitions,...
Consultez l'ensemble des articles et chiffres clés réunis en un condensé 100% mobile en PJ.
Comparison of Jacob's Creek, Rosemount Estate, McGuigan Wines, Lindeman's and...Unmetric
Take a deep dive into the social media activities of the top wine brands in Australia on Facebook. Discover how brands like Lindeman's wines and Champagne Taittinger engage their audience with shareable content and social media campaigns.
Bio2RDF is an open-source project that offers a large and
connected knowledge graph of Life Science Linked Data. Each dataset is expressed using its own vocabulary, thereby hindering integration, search, query, and browse data across similar or identical types of data. With growth and content changes in source data, a manual approach to maintain mappings has proven untenable. The aim of this work is to develop a (semi)automated procedure to generate high quality mappings
between Bio2RDF and SIO using BioPortal ontologies. Our preliminary results demonstrate that our approach is promising in that it can find new mappings using a transitive closure between ontology mappings. Further development of the methodology coupled with improvements in
the ontology will offer a better-integrated view of the Life Science Linked Data
How can you access PubChem programmatically?Sunghwan Kim
Presented at the 255th American Chemical Society (ACS) National Meeting in New Orleans, LA (March. 19, 2018).
Building automated workflows that exploit the vast amount of data contained in PubChem requires programmatic access to the data through application programming interfaces (APIs). PubChem provides several programmatic access routes to its data, including Entrez Utilities (E-Utilities or E-Utils), PubChem Power User Gateway (PUG), PUG-SOAP, PUG-REST, PUG-View, and a REST-ful interface to PubChemRDF. This presentation provides an overview of these programmatic access tools, including recent updates, limitations, usage policies, and best practices.
*References*
(1) PUG-SOAP and PUG-REST: web services for programmatic access to chemical information in PubChem, Nucleic Acids Research, 2015, 43(W1):W605–W611. https://doi.org/10.1093/nar/gkv396
(2) An update on PUG-REST: RESTful interface for programmatic access to PubChem, Nucleic Acids Research, 2018, 46(W1):gky294. https://doi.org/10.1093/nar/gky294
GBIF web services for biodiversity data, for USDA GRIN, Washington DC, USA (2...Dag Endresen
Presentation of GBIF and the sharing of biodiversity data with web services. USDA GRIN Beltsville Washington DC, 13th December 2005. GBIF is the Global Biodiversity Information Facility for free and open access to biodiversity data.
Towards semantic systems chemical biology Bin Chen
introduce a semantic framework for studying systems chemical biology / systems pharmacology, in which three major projects (Chem2Bio2RDF, Chem2Bio2OWL, SLAP (semantic link association prediction) are covered.
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
My talk at NCI's CBIIT speaker series:
https://wiki.nci.nih.gov/display/CBIITSpeakers/2019/01/02/Jan+16%2C+Chunlei+Wu%2C+BioThings+API
A companion blog post: https://ncip.nci.nih.gov/blog/the-network-of-biothings/
See more details about BioThings project at http://biothings.io.
TDWG and GBIF, at European genbank network meeting (Bonn, April 2004)Dag Endresen
Presentation of TDWG and GBIF for the ECP/GR D&I Network meeting at ZADI Bonn Germany 11th April 2005. Dag Endresen (Nordic Gene Bank). TDWG is a standardization body for Biodiversity Information Standards; GBIF is a Global Biodiversity Information Facility for free and open access to biodiversity data.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
knowledge graphs are an emerging paradigm to represent information. yet their discovery and reuse is hampered by insufficient or inadequate metadata. here, the COST ACTION Distributed Knowledge Graphs had a first workshop to develop a KG metadata schema. In this presentation, the progress and plans are discussed with the W3C Community Group on Knowledge Graph Construction.
Data-Driven Discovery Science with FAIR Knowledge GraphsMichel Dumontier
Data-Driven Discovery Science with FAIR Knowledge Graphs
Despite the existence of vast amounts of biomedical data, these remain difficult to find and to productively reuse in machine learning and other Artificial Intelligence technologies. In this talk, I will discuss the role of the FAIR Guiding Principles to make AI-ready biomedical data, and their representation as knowledge graphs not only enables powerful ontology-backed semantic queries, but also can be used to predict missing information, as well as to check the quality of knowledge collected.
The main idea of the talk is to introduce the FAIR principles (what they are and what they are not), and how their application with semantic web technologies (ontologies/linked data) creates improved possibilities for large scale data integration, answering sophisticated questions using automated reasoners, and predicting new relations/validating data using graph embeddings. The audience will gain insight into the state of the art in a carefully presented manner that introduces principles, approaches, and outcomes relevant to Health AI.
The FAIR (Findable, Accessible, Interoperable, Reusable) Guiding Principles light a path towards improving the discovery and reuse of digital objects (data, documents, software, web services, etc) by machines. Machine reusability is a crucial strategic component in building robust digital infrastructure that strengthens scholarship and opens new pathways for innovation on a truly global scale. However, as the FAIR principles do not specify any particular implementation, communities have the homework to devise, standardize and implement technical specifications to improve the ‘FAIRness’ of digital assets. In this seminar, I will focus on the history and state of the art in the FAIRness assessment, including manual, semi-automated and fully automated approaches, and how these can be used by developers and consumers alike. This seminar will serve as a springboard for community discussion and adoption of these services to incrementally and realistically improve the FAIRness of their resources.
The Role of the FAIR Guiding Principles for an effective Learning Health SystemMichel Dumontier
he learning health system (LHS) is an integrated social and technological system that embeds continuous improvement and innovation for the effective delivery of healthcare. A crucial part of the LHS lies in how the underlying information system will secure and take advantage of relevant knowledge assets towards supporting complex and unusual clinical decision making, facilitating public health surveillance, and aiding comparative effectiveness research. However, key knowledge assets remain difficult to obtain and reuse, particularly in a decentralized context. In this talk, I will discuss the role of the Findable, Accessible, Interoperable, and Reusable (FAIR) Guiding Principles towards the realization of the LHS, along with emerging technologies to publish and refine clinical research and knowledge derived therein.
Keynote given for 2021 Knowledge Representation for Health Care http://banzai-deim.urv.net/events/KR4HC-2021/
CIKM2020 Keynote: Accelerating discovery science with an Internet of FAIR dat...Michel Dumontier
Biomedicine has always been a fertile and challenging domain for computational discovery science. Indeed, the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offer exciting opportunities to reuse our collective knowledge, were we not stymied by incompatible formats, overlapping and incomplete vocabularies, unclear licensing, and heterogeneous access points. In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services enable automated scientific discovery on a global scale.
bio:
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research focuses on the development of computational methods for scalable and responsible discovery science. Dr. Dumontier obtained his BSc (Biochemistry) in 1998 from the University of Manitoba, and his PhD (Bioinformatics) in 2005 from the University of Toronto. Previously a faculty member at Carleton University in Ottawa and Stanford University in Palo Alto, Dr. Dumontier founded and directs the interfaculty Institute of Data Science at Maastricht University to develop sociotechnological systems for responsible data science by design. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon 2020, the European Open Science Cloud, the US National Institutes of Health and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
This presentation was given on October 21, 2020 at CIKM2020.
The role of the FAIR Guiding Principles in a Learning Health SystemMichel Dumontier
The learning health system (LHS) is a concept for a socio-technological system that continuously improves the delivery of health care by coupling biomedical research with practice- and evidence- based medicine. Key aspects of the LHS are collecting, integrating, and analyzing data from different sources. While the increased digitalisation of healthcare is creating new data sources, these remain hard to find and use, let alone make use of as part of intelligent systems for the benefit of patients, healthcare providers, and researchers. This talk will examine recent developments towards making key parts of the LHS, such as clinical practice guidelines, Findable, Accessible, Interoperable, and Reusable (FAIR).
Acclerating biomedical discovery with an internet of FAIR data and services -...Michel Dumontier
With its focus on improving the health and well being of people, biomedicine has always been a fertile, if not challenging domain for computational discovery science. Indeed, the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offer exciting opportunities to reuse our collective knowledge, were we not stymied by incompatible formats, overlapping and incomplete vocabularies, unclear licensing, and heterogeneous access points. In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services, which is built on Semantic Web technologies, be well positioned to support automated scientific discovery on a global scale.
Accelerating Biomedical Research with the Emerging Internet of FAIR Data and ...Michel Dumontier
ith its focus on improving the health and well being of people, biomedicine has always been a fertile, if not challenging domain for computational discovery science. Indeed, the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offer exciting opportunities to reuse our collective knowledge, were we not stymied by incompatible formats, overlapping and incomplete vocabularies, unclear licensing, and heterogeneous access points. In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services enable automated scientific discovery on a global scale.
Are we FAIR yet? And will it be worth it?
The FAIR Principles propose essential characteristics that all digital resources (e.g. datasets, repositories, web services) should possess to be Findable, Accessible, Interoperable, and Reusable by both humans and machines. The Principles act as a guide that researchers and data stewards should expect from contemporary digital resources, and in turn, the requirements on them when publishing their own scholarly products. As interest in, and support for the Principles has spread, the diversity of interpretations has also broadened, with some resources claiming to already “be FAIR”.
This talk will elaborate on what FAIR is, what it entails, and how we should evaluate FAIRness. I will describe new social and technological infrastructure to support the creation and evaluation of FAIR resources, and how FAIR fits into institutional, national and international efforts. Finally, I will discuss the merits of the FAIR principles (and what we ask of people) in the context of strengthening data-driven scientific inquiry.Are we FAIR yet? And will it be worth it?
The FAIR Principles propose essential characteristics that all digital resources (e.g. datasets, repositories, web services) should possess to be Findable, Accessible, Interoperable, and Reusable by both humans and machines. The Principles act as a guide that researchers and data stewards should expect from contemporary digital resources, and in turn, the requirements on them when publishing their own scholarly products. As interest in, and support for the Principles has spread, the diversity of interpretations has also broadened, with some resources claiming to already “be FAIR”.
This talk will elaborate on what FAIR is, what it entails, and how we should evaluate FAIRness. I will describe new social and technological infrastructure to support the creation and evaluation of FAIR resources, and how FAIR fits into institutional, national and international efforts. Finally, I will discuss the merits of the FAIR principles (and what we ask of people) in the context of strengthening data-driven scientific inquiry.
Keynote given at NETTAB2018 - http://www.igst.it/nettab/2018/
The future of science and business - a UM Star LectureMichel Dumontier
I discuss how data science is affecting our way of life and how we at Maastricht University are preparing the next generation of leaders to address opportunities and challenges in responsible manner.
The FAIR Principles propose key characteristics that all digital resources (e.g. datasets, repositories, web services) should possess to be Findable, Accessible, Interoperable, and Reusable by people and machines. The Principles act as a guide that researchers should expect from contemporary digital resources, and in turn, the requirements on them when publishing their own scholarly products. As interest in, and support for the Principles has spread, the diversity of interpretations has also broadened, with some resources claiming to already “be FAIR”. This talk will elaborate on what FAIR is, why we need it, what it entails, and how we should evaluate FAIRness. I will describe new social and technological infrastructure to support the creation and evaluation of FAIR resources, and how FAIR fits into institutional, national and international efforts. Finally, I will discuss the merits of the FAIR principles (and what we ask of people) in the context of strengthening data-driven scientific inquiry.
A talk prepared for Workshop Working on data stewardship? Meet your peers!
Datum: 03 OKT 2017
https://www.surf.nl/agenda/2017/10/workshop-working-on-data-stewardship-meet-your-peers/index.html
Towards metrics to assess and encourage FAIRnessMichel Dumontier
With an increased interest in the FAIR metrics, there is need to develop tools and appraoches that can assess the FAIRness of a digital resource. This talk begins to explore some ideas in this space, and invites people to participate in a working group focused on the development, application, and evaluation of FAIR metric efforts.
A presentation to the New Year's Event for Maastricht University's Knowledge Engineering @ Work Program. https://www.maastrichtuniversity.nl/news/kework-first-10-students-academic-workstudy-track-graduate
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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.
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.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
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
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
1. Bio2RDF Release 2: Improved coverage,
interoperability and provenance of Life
Science Linked Data
Linked Data for the Life Sciences
Alison Callahan1, Jose Cruz-Toledo1, Peter Ansell2, Michel Dumontier1
1Carleton University, 2University of Queensland
ESWC2013::Bio2RDF Release 21
2. ESWC2013::Bio2RDF Release 2
is an open source framework
on the emerging semantic web
to produce and provide biological linked data
that uses simple conventions
2
4. Main features of Bio2RDF Release 2
• Bio2RDF conversion scripts, mapping files and web
application are open source and freely available at
http://github.com/bio2rdf
• Bio2RDF enables (syntactic) data integration within and
across datasets by using one language (RDF), having a
common URI pattern and a common resource registry
• 19 Release 2 datasets have provenance and endpoints
feature pre-computed graph summaries for fast lookup
• Bio2RDF web application enables entity resolution, query
federation across an expandable distributed network of
SPARQL endpoints
ESWC2013::Bio2RDF Release 24
6. Bio2RDF data are identified using
simple http URI patterns
Bio2RDF data are identified by Internationalized Resource Identifiers
(IRIs) of the form:
• http://bio2rdf.org/namespace:identifier
for source data with an assigned identifier
• http://bio2rdf.org/namespace_resource:identifier
for source data without an assigned identifier
• http://bio2rdf.org/namespace_vocabulary:identifier
for dataset-specific types and relations
Where namespace comes from a curated registry of datasets, hence
enabling simple syntactic-based integration in and across datasets.
ESWC2013::Bio2RDF Release 26
7. Data are described through machine-
understandable statements
ESWC2013::Bio2RDF Release 2
drugbank:DB00650
drugbank_vocabulary:Drug
rdf:type
drugbank_resource:DB00440_DB00650
drugbank_vocabulary:Drug-Drug-Interaction
rdf:type
drugbank_vocabulary:ddi-interactor-in
rdfs:label
DDI between Trimethoprim and
Leucovorin [drugbank_resource:
DB00440_DB00650]
rdfs:label
Leucovorin [drugbank:DB00650]
7
8. The linked data network expands
with inter-dataset statements
ESWC2013::Bio2RDF Release 2
drugbank:DB00650
pharmgkb_vocabulary:Drug
rdf:type
rdfs:label
Leucovorin [drugbank:DB00650]
pharmgkb:PA450198
drugbank_vocabulary:Drug
pharmgkb_vocabulary:xref
leucovorin [pharmgkb:PA450198]
rdfs:label
DrugBank
PharmGKB
8
10. You can get what links to it
ESWC2013::Bio2RDF Release 2
http://bio2rdf.org/linksns/drugbank/drugbank:DB00650
What links to DrugBank’s Leucovorin?
10
11. Every Bio2RDF dataset now contains
provenance metadata
ESWC2013::Bio2RDF Release 2
Features
- Entity-dataset link
- Creator
- Publisher
- Date created
- License & rights
- Source
- Availability
- SPARQL endpoint
- Data dump
Vocabularies
VoID
Dublin Core
W3C Provenance
Bio2RDF vocabulary
11
data item
Bio2RDF
dataset
Source
dataset
void:inDataset
prov:wasDerivedFrom
12. Dataset Namespace # of triples
Affymetrix affymetrix 44469611
Biomodels* biomodels 589753
Comparative Toxicogenomics Database ctd 141845167
DrugBank drugbank 1121468
NCBI Gene ncbigene 394026267
Gene Ontology Annotations goa 80028873
HUGO Gene Nomenclature Committee hgnc 836060
Homologene homologene 1281881
InterPro* interpro 999031
iProClass iproclass 211365460
iRefIndex irefindex 31042135
Medical Subject Headings mesh 4172230
NCBO BioPortal* bioportal 15384622
National Drug Code Directory* ndc 17814216
Online Mendelian Inheritance in Man omim 1848729
Pharmacogenomics Knowledge Base pharmgkb 37949275
SABIO-RK* sabiork 2618288
Saccharomyces Genome Database sgd 5551009
NCBI Taxonomy taxon 17814216
Total 19 1,010,758,291
Bio2RDF Release 2 – New and Updated Datasets
ESWC2013::Bio2RDF Release 212
20. You can use the SPARQLed query
assistant with updated endpoints
ESWC2013::Bio2RDF Release 2
http://sindicetech.com/sindice-suite/sparqled/
graph: http://sindicetech.com/analytics20
21. Use virtuoso’s built in faceted
browser to construct increasingly
complex queries with little effort
ESWC2013::Bio2RDF Release 221
22. Federated Queries over independent
SPARQL endpoints
# get all biochemical reactions in biomodels that are kinds of "protein catabolic
process“, as defined by the gene ontology (in bioportal endpoint)
SPARQL Endpoint: http://bioportal.bio2rdf.org/sparql
SELECT ?go ?label count(distinct ?x)
WHERE {
?go rdfs:label ?label .
?go rdfs:subClassOf ?tgo OPTION (TRANSITIVE) .
?tgo rdfs:label ?tlabel .
FILTER regex(?tlabel, "^protein catabolic process")
service <http://biomodels.bio2rdf.org/sparql> {
?x <http://bio2rdf.org/biopax_vocabulary:identical-to> ?go .
?x a <http://www.biopax.org/release/biopax-level3.owl#BiochemicalReaction> .
} # end service
}
ESWC2013::Bio2RDF Release 222
23. Question: Find all proteins that interact with beta
amyloid
SELECT * WHERE {
?protein a bio2rdf:Protein .
?protein bio2rdf:interacts_with bio2rdf:beta-amyloid
.
}
Heterogeneous biological data on the
semantic web is difficult to query
UniProt Protein PDB Protein
iRefIndex Protein
?
Physical interaction?
Pathway interaction?
Genetic interaction?
ESWC2013::Bio2RDF Release 223
24. ontology as a
strategy to formally
represent and
integrate knowledge
ESWC2013::Bio2RDF Release 224
25. uniprot:P05067
uniprot:Protein
is a
sio:gene
is a is a
Semantic data integration, consistency checking and
query answering over Bio2RDF with the
Semanticscience Integrated Ontology (SIO)
dataset
ontology
Knowledge Base
ESWC2013::Bio2RDF Release 2
pharmgkb:PA30917
refseq:Protein
is a
is a
omim:189931
omim:Gene pharmgkb:Gene
Querying Bio2RDF Linked Open Data with a Global Schema. Alison Callahan, José Cruz-Toledo and
Michel Dumontier. Bio-ontologies 2012.
25
27. Bio2RDF and SIO powered SPARQL 1.1 federated query:
Find chemicals in CTD and proteins in SGD that participate
in the same GO process
SELECT ?chem, ?prot, ?proc
FROM <http://bio2rdf.org/ctd>
WHERE {
?chemical a sio:chemical-entity.
?chemical rdfs:label ?chem.
?chemical sio:is-participant-in ?process.
?process rdfs:label ?proc.
FILTER regex (?process, "http://bio2rdf.org/go:")
SERVICE <http://sgd.bio2rdf.org/sparql> {
?protein a sio:protein .
?protein sio:is-participant-in ?process.
?protein rdfs:label ?prot .
}
}
ESWC2013::Bio2RDF Release 227
28. Bio2RDF RDFization guidelines are
available at our wiki
https://github.com/bio2rdf/bio2rdf-scripts/wiki/RDFization-Guide-v1.1
ESWC2013::Bio2RDF Release 228
29. What the future holds
• Aiming for twice yearly release schedule. Next release will
include large datasets (>15B RefSeq, Genbank, PubMed, PDB)
• Working with identifiers.org to create a common registry with
2200 entries
• Spiking in identifiers.org and original data uris, where
available
• Consolidating provenance/metrics with OpenPHACTS
• Incorporate W3C Linking Open Drug Data (LODD) effort
– OMIM (released), SIDER (beta), CHEMBL (beta), LinkedCT
(beta), DailyMed (RDF available), TCM (RDF available),
• Extended dataset coverage by tapping into existing endpoints
(uniprot, bioportal, ebi-rdf?)
• Showcase with other third party tools
ESWC2013::Bio2RDF Release 229
30. Bio2RDF Release 2 – A summary
• Updated data conversion source code to use PHP API (all
available through GitHub)
– http://github.com/bio2rdf/bio2rdf-scripts
– https://github.com/bio2rdf/bio2rdf-scripts/wiki/RDFization-
Guide-v1.1
• Simple Bio2RDF IRI design patterns that facilitate syntactic
consistency and interoperability backed by simple registry
• Dataset provenance and metrics
• We welcome comments, suggestions and contributions
• Join our mailing list at bio2rdf@googlegroups.com
ESWC2013::Bio2RDF Release 230
31. Acknowledgements
Bio2RDF Release 2
Allison Callahan, Jose Cruz-Toledo, Peter Ansell
Bio2RDF
Francois Belleau, Marc-Alexandre Nolin
Alex De Leon, Steve Etlinger, Nichealla Keath
Jacques Corbeil, James Hogan Jean Morissette, Nicole
Tourigny, Philippe Rigault and Paul Roe
ESWC2013::Bio2RDF Release 231
Bio2RDF facilitates data sharing and reuse in a number of ways: Access the scripts that generate our linked data. These scripts are openly licensed for modification, redistribution or use by anyone wishing to generate RDF data on their own We make use of syntactically consistent IRI patterns We do not impose a structural scheme for representing our data Bio2RDF allows for multiple mirrors host our data, a DNS “round robin” procedure balances incoming requests between participating mirrors, this prevents a single point of failure and allows for additional mirrors to be added to the network A centralized resource registry has been developed for consistent usage of namespaces and vocabularies- In the next slides I will go into a bit more detail about the first 3 points
The Bio2RDF project transforms silos of life science data into a globally distributed network of linked data for biological knowledge discovery.
In order to keep a clear link back to the original data, in our RDFized datasets we maintain the original data provider’s record identifiers by making use of the following URI pattern:- namespace: preferred short name for a biological dataset
All resources in every bio2RDF graph is linked to a graph that describes the provenance of the generated linked data. We make use of the W3C Vocabulary of Interlinked Datasets (VoID), the Provenance vocabulary and Dublin core vocabulary to describe items such as: URL to the source data Date of generation Licensing information (if available) URL to the script used to generate the data Download URL for linked data files URL of SPARQL endpoint
Here I present some numbers for the 19 updated datasets
Here I am showing with more detail the top 10 subject type – predicate - object type frequencies that can be found in our Drugbank endpoint So for example to find drugs that participate in drug-drug interactions one would use the ddi-interactor-in predicate that associates the 1074 resources of type drug to the 10891 resources typed as drug-drug-interaction.
We are currently in the process of exposing Bio2RDF data using a variety of 3rd party tools- specifically, all of our endpoints can be navigated using Virtuoso’s faceted browser- We have also generated Sindice metrics that enable the use of SPARQLedautomed query builder. (This tool allows users to semiautomatically construct SPARQL queries based on namespaces used therein)-- finally it is possible to use Sig.ma browser to aggreate data from multiple endpoints and construct mashups
However, types and predicates are dataset specific and therefore not consistentWouldn’t it be nice to be able to query all of these datasets with a common nomenclature? (our objective)