The Challenges of Describing Best Tagging Practices for JATS
Jeffrey Beck, Technical Information Specialist, National Center for Biotechnology Information (NCBI), U.S. National Library of Medicine, National Institutes of Health; Co-chair, NISO Journal Article Tag Suite (JATS) Standing Committee
This document provides an introduction to analyzing social graphs using graph databases. It discusses using Neo4j to store social graph data and analyze centrality and clustering coefficients. Sample code is shown for inserting nodes and relationships in Neo4j and traversing the graph. Analyzing a sample social network dataset found centrality values ranged from 1 to over 900, with a median of 10, and clustering coefficients ranged from 0 to 1. Visualization of the social graph and analysis results is also briefly discussed.
NoSQL Search Roadshow Zurich 2013 - Polyglot persistence with no sqlMichael Lehmann
The document discusses polyglot persistence, which is using multiple data persistence technologies like both SQL and NoSQL databases together. It notes that while relational databases have long dominated, NoSQL databases offer alternatives to address needs like large volumes of data, high speeds, and flexibility. The document outlines different types of NoSQL databases and considerations for choosing between them, and advocates using different databases based on their strengths and applying principles like separation of layers and reusable services to integrate diverse data stores in a polyglot approach.
DTD stands for Document Type Definition. It defines the structure and elements of an XML document. DTDs check if an XML document is valid by defining the grammar. They are used to create and manage large sets of shared documents. DTDs declare elements, attributes, entities, and define the document structure with content models. While DTDs were useful, more robust alternatives like XML Schema emerged.
Dont be fooled with BDD, automation engineer! ;)Iakiv Kramarenko
This talk is about:
- History of BDD
- What is BDD
- BDD is really cool stuff, but
- - it was created not for test automation enginers
- - and its tools like cucumber are not optimized to be used by automation engineers
- What are alternatives to BDD, that gives the same level of readability/simplicity
- How BDD tools can be improved to fit test automation engineers needs
Iakiv Kramarenko - Don't be fooled with BDD, automation engineerIevgenii Katsan
This document provides a summary of the history and development of Behavior-Driven Development (BDD). It describes how Dan North originally developed BDD as an evolution of Test-Driven Development (TDD) to address problems developers faced in understanding TDD practices. North proposed using more business-readable language and terminology in test names and structures. This led to the creation of tools like Cucumber that help facilitate writing tests in a "behavior context" using a Given-When-Then structure inspired by domain-driven design. The document traces the evolution of BDD from these origins to its current definition emphasizing collaboration between stakeholders and defining requirements over a focus on testing.
Combining Similarities and Regression for Entity Linking.César de Pablo
The document summarizes previous work on entity linking and knowledge base population tasks. It discusses the tasks of entity linking, which grounds entity mentions in documents to entries in a knowledge base, and slot filling, which learns attributes about target entities. It provides results from the TAC-KBP 2010 evaluation, showing entity linking accuracy for different entity types and domains. GPE entities were particularly difficult. Name similarity features and handling NIL queries impacted performance.
This document discusses document type definitions (DTDs), which define the structure and elements of an XML document. DTDs allow documents to be validated against a set of rules to check validity. The document provides an example of a simple DTD defining a greeting element containing text. It demonstrates how to add a DTD to an XML file and explains that the file must adhere to the DTD's rules to be considered valid. Validating parsers check documents against their DTDs and report any errors found.
This document provides an introduction to analyzing social graphs using graph databases. It discusses using Neo4j to store social graph data and analyze centrality and clustering coefficients. Sample code is shown for inserting nodes and relationships in Neo4j and traversing the graph. Analyzing a sample social network dataset found centrality values ranged from 1 to over 900, with a median of 10, and clustering coefficients ranged from 0 to 1. Visualization of the social graph and analysis results is also briefly discussed.
NoSQL Search Roadshow Zurich 2013 - Polyglot persistence with no sqlMichael Lehmann
The document discusses polyglot persistence, which is using multiple data persistence technologies like both SQL and NoSQL databases together. It notes that while relational databases have long dominated, NoSQL databases offer alternatives to address needs like large volumes of data, high speeds, and flexibility. The document outlines different types of NoSQL databases and considerations for choosing between them, and advocates using different databases based on their strengths and applying principles like separation of layers and reusable services to integrate diverse data stores in a polyglot approach.
DTD stands for Document Type Definition. It defines the structure and elements of an XML document. DTDs check if an XML document is valid by defining the grammar. They are used to create and manage large sets of shared documents. DTDs declare elements, attributes, entities, and define the document structure with content models. While DTDs were useful, more robust alternatives like XML Schema emerged.
Dont be fooled with BDD, automation engineer! ;)Iakiv Kramarenko
This talk is about:
- History of BDD
- What is BDD
- BDD is really cool stuff, but
- - it was created not for test automation enginers
- - and its tools like cucumber are not optimized to be used by automation engineers
- What are alternatives to BDD, that gives the same level of readability/simplicity
- How BDD tools can be improved to fit test automation engineers needs
Iakiv Kramarenko - Don't be fooled with BDD, automation engineerIevgenii Katsan
This document provides a summary of the history and development of Behavior-Driven Development (BDD). It describes how Dan North originally developed BDD as an evolution of Test-Driven Development (TDD) to address problems developers faced in understanding TDD practices. North proposed using more business-readable language and terminology in test names and structures. This led to the creation of tools like Cucumber that help facilitate writing tests in a "behavior context" using a Given-When-Then structure inspired by domain-driven design. The document traces the evolution of BDD from these origins to its current definition emphasizing collaboration between stakeholders and defining requirements over a focus on testing.
Combining Similarities and Regression for Entity Linking.César de Pablo
The document summarizes previous work on entity linking and knowledge base population tasks. It discusses the tasks of entity linking, which grounds entity mentions in documents to entries in a knowledge base, and slot filling, which learns attributes about target entities. It provides results from the TAC-KBP 2010 evaluation, showing entity linking accuracy for different entity types and domains. GPE entities were particularly difficult. Name similarity features and handling NIL queries impacted performance.
This document discusses document type definitions (DTDs), which define the structure and elements of an XML document. DTDs allow documents to be validated against a set of rules to check validity. The document provides an example of a simple DTD defining a greeting element containing text. It demonstrates how to add a DTD to an XML file and explains that the file must adhere to the DTD's rules to be considered valid. Validating parsers check documents against their DTDs and report any errors found.
SCHEMA BASED STORAGE OF XML DOCUMENTS IN RELATIONAL DATABASESijwscjournal
XML (Extensible Mark up language) is emerging as a tool for representing and exchanging data over the
internet. When we want to store and query XML data, we can use two approaches either by using native
databases or XML enabled databases. In this paper we deal with XML enabled databases. We use
relational databases to store XML documents. In this paper we focus on mapping of XML DTD into
relations. Mapping needs three steps: 1) Simplify Complex DTD’s 2) Make DTD graph by using simplified
DTD’s 3) Generate Relational schema. We present an inlining algorithm for generating relational schemas
from available DTD’s. This algorithm also handles recursion in an XML document.
SCHEMA BASED STORAGE OF XML DOCUMENTS IN RELATIONAL DATABASESijwscjournal
XML (Extensible Mark up language) is emerging as a tool for representing and exchanging data over the internet. When we want to store and query XML data, we can use two approaches either by using native databases or XML enabled databases. In this paper we deal with XML enabled databases. We use relational databases to store XML documents. In this paper we focus on mapping of XML DTD into relations. Mapping needs three steps: 1) Simplify Complex DTD’s 2) Make DTD graph by using simplified DTD’s 3) Generate Relational schema. We present an inlining algorithm for generating relational schemas
from available DTD’s. This algorithm also handles recursion in an XML document.
Collaborative Cuisine's 1 Hour JNDI CookbookKen Lin
For programmers who are already familiar with JNDI and LDAP basics, but wonder how to mix all those ingredients together into collaborative directory-enabled JEE solutions.
http://kenlin.com
The amount of data collected by applications nowadays is growing at a scary pace. Many of them need to handle billions of users generating and consuming data at an incredible speed. Maybe you are wondering how to create an application like this? What is required? What works best for your project?
In this session we’ll compare popular Java and JVM persistence frameworks for NoSQL databases: Spring Data, Micronaut, Hibernate OGM, Jakarta NoSQL, and GORM. How do they compare, what are the strengths, weaknesses, differences, and similarities? We’ll show each of them with a selection of different NoSQL database systems (Key-Value, Document, Column, Graph).
The data load on applications has increased exponentially in recent years. We know the JVM (Java Virtual Machine) can cope with heavy loads very well yet we often come across the big dilemma: there are tons of persistence frameworks out there but which one performs best for my case? It would normally take ages to evaluate and choose the best fit for your use case. We’ve done those comparisons for you.
This document discusses NoSQL Endgame, a framework for mapping object-relational mappings to NoSQL databases. It provides a cleaner DAO implementation and removes boilerplate code by supporting key-value stores, column-oriented, document, and graph databases. However, it only supports a few popular NoSQL databases out of the box and switching between vendors is not entirely easy. The framework is also outdated as the last release was in 2018.
The document discusses XML namespaces and XML schemas. It provides examples of using namespaces to differentiate between similarly named elements, such as <highschool:subject> and <medicine:subject>. It also compares defining an XML document using a DTD versus using an XML schema, and provides a sample schema for defining book information. Key differences between "ref" and "type" attributes in schemas are explained using an employee example.
This document defines and provides examples of XML DTDs. It explains that a DTD defines the structure and elements of an XML document and can be used to validate XML data. It describes the syntax of DTDs and the different types (internal and external). Key points covered include that a DTD specifies elements, attributes, and entities; defines the root element; and element types include PCDATA for parsed character data and CDATA for non-parsed character data. Examples are provided of internal and external DTDs. The document concludes that using a DTD allows different groups to agree on a common standard for exchanging data and applications to validate received and internal data.
A presentation on my early work on the Mastro system. Some of this research is now part of the ontop system, some evolved into more optimised forms (also in ontop).
These slides were presented as part of a W3C tutorial at the CSHALS 2010 conference (http://www.iscb.org/cshals2010). The slides are adapted from a longer introduction to the Semantic Web available at http://www.slideshare.net/LeeFeigenbaum/semantic-web-landscape-2009 .
A PDF version of the slides is available at http://thefigtrees.net/lee/sw/cshals/cshals-w3c-semantic-web-tutorial.pdf .
- The document provides an overview of the basic syntax for implementing Dublin Core metadata in HTML, XML, and RDF. It discusses encoding Dublin Core elements, properties, value strings, and encoding schemes in each syntax.
- It also briefly discusses the OAI Protocol for Metadata Harvesting (OAI-PMH) and RSS, giving an example of an OAI-PMH request.
- The key aspects of the Dublin Core abstract model are summarized, including descriptions, statements, properties, values, and value strings.
The document provides an overview of document type definitions (DTDs) including:
- What a DTD is and why they are used
- The basic building blocks of DTDs including elements, attributes, entities, PCDATA, and CDATA
- How to declare elements and attributes in a DTD including allowed content and occurrences
- Examples of internal and external DTD declarations
The document provides an overview of XML schemas, including their purpose to specify the structure and data types of XML documents. It describes the basic components of schemas, including elements, simple and complex types, and attributes. It provides an example schema for a "friend" element and addresses.
Lambico is a project aiming to simplify the persistence layer of your applications by providing a manner for easily defining the DAOs that manage the data stored in your database.
With Lambico you can define the DAOs for your entities just writing their interfaces, with no implementation at all.
Parancoe 3 is a Web meta-framework which is using Lambico for its persistence layer, and the more recent features of Spring MVC.
This document provides an introduction to object-relational mapping using Hibernate. It discusses relational database design, object-oriented design, and the impedance mismatch between the two. It then explains how an ORM like Hibernate can map objects to relational databases while hiding SQL and connection details. Code examples demonstrate using Hibernate and JPA to perform CRUD operations instead of raw JDBC. Configuration of Hibernate and JPA is also summarized.
Formats for Exchanging Archival Data: An Introduction to EAD, EAC-CPF, and Ar...Michael Rush
Presented July 1, 2011, as part of the session "Standards, Information, and Data Exchange" at the 7th International Seminar of Iberian Tradition Archives, Rio de Janeiro, Brazil.
Introduction to the usage of DTDs in connection with XML documents. Elements and attributes are introduced in details. Use of ID, IDREF, and IDREFS for uniqueness and referring to elements are illustrated using a number of examples.
The document discusses XML and DTDs. It defines DTDs as describing the components and guidelines in an XML document by listing elements, attributes and their possible values, entities, and their interactions. It provides examples of element declarations in DTDs using tags like ELEMENT, EMPTY, ANY, and content models. It also distinguishes between internal and external DTDs and when each is generally used.
VIVO: An overview and its Implementation at Brown
Ted Lawless, Library Applications Developer, Library Integrated Technology Services, Brown University
Serendipity in Digital Collections: Enhancing Discovery with Linked Data Anna L. Creech, Head, Resource Acquisition and Delivery, Boatwright Memorial Library, University of Richmond
SCHEMA BASED STORAGE OF XML DOCUMENTS IN RELATIONAL DATABASESijwscjournal
XML (Extensible Mark up language) is emerging as a tool for representing and exchanging data over the
internet. When we want to store and query XML data, we can use two approaches either by using native
databases or XML enabled databases. In this paper we deal with XML enabled databases. We use
relational databases to store XML documents. In this paper we focus on mapping of XML DTD into
relations. Mapping needs three steps: 1) Simplify Complex DTD’s 2) Make DTD graph by using simplified
DTD’s 3) Generate Relational schema. We present an inlining algorithm for generating relational schemas
from available DTD’s. This algorithm also handles recursion in an XML document.
SCHEMA BASED STORAGE OF XML DOCUMENTS IN RELATIONAL DATABASESijwscjournal
XML (Extensible Mark up language) is emerging as a tool for representing and exchanging data over the internet. When we want to store and query XML data, we can use two approaches either by using native databases or XML enabled databases. In this paper we deal with XML enabled databases. We use relational databases to store XML documents. In this paper we focus on mapping of XML DTD into relations. Mapping needs three steps: 1) Simplify Complex DTD’s 2) Make DTD graph by using simplified DTD’s 3) Generate Relational schema. We present an inlining algorithm for generating relational schemas
from available DTD’s. This algorithm also handles recursion in an XML document.
Collaborative Cuisine's 1 Hour JNDI CookbookKen Lin
For programmers who are already familiar with JNDI and LDAP basics, but wonder how to mix all those ingredients together into collaborative directory-enabled JEE solutions.
http://kenlin.com
The amount of data collected by applications nowadays is growing at a scary pace. Many of them need to handle billions of users generating and consuming data at an incredible speed. Maybe you are wondering how to create an application like this? What is required? What works best for your project?
In this session we’ll compare popular Java and JVM persistence frameworks for NoSQL databases: Spring Data, Micronaut, Hibernate OGM, Jakarta NoSQL, and GORM. How do they compare, what are the strengths, weaknesses, differences, and similarities? We’ll show each of them with a selection of different NoSQL database systems (Key-Value, Document, Column, Graph).
The data load on applications has increased exponentially in recent years. We know the JVM (Java Virtual Machine) can cope with heavy loads very well yet we often come across the big dilemma: there are tons of persistence frameworks out there but which one performs best for my case? It would normally take ages to evaluate and choose the best fit for your use case. We’ve done those comparisons for you.
This document discusses NoSQL Endgame, a framework for mapping object-relational mappings to NoSQL databases. It provides a cleaner DAO implementation and removes boilerplate code by supporting key-value stores, column-oriented, document, and graph databases. However, it only supports a few popular NoSQL databases out of the box and switching between vendors is not entirely easy. The framework is also outdated as the last release was in 2018.
The document discusses XML namespaces and XML schemas. It provides examples of using namespaces to differentiate between similarly named elements, such as <highschool:subject> and <medicine:subject>. It also compares defining an XML document using a DTD versus using an XML schema, and provides a sample schema for defining book information. Key differences between "ref" and "type" attributes in schemas are explained using an employee example.
This document defines and provides examples of XML DTDs. It explains that a DTD defines the structure and elements of an XML document and can be used to validate XML data. It describes the syntax of DTDs and the different types (internal and external). Key points covered include that a DTD specifies elements, attributes, and entities; defines the root element; and element types include PCDATA for parsed character data and CDATA for non-parsed character data. Examples are provided of internal and external DTDs. The document concludes that using a DTD allows different groups to agree on a common standard for exchanging data and applications to validate received and internal data.
A presentation on my early work on the Mastro system. Some of this research is now part of the ontop system, some evolved into more optimised forms (also in ontop).
These slides were presented as part of a W3C tutorial at the CSHALS 2010 conference (http://www.iscb.org/cshals2010). The slides are adapted from a longer introduction to the Semantic Web available at http://www.slideshare.net/LeeFeigenbaum/semantic-web-landscape-2009 .
A PDF version of the slides is available at http://thefigtrees.net/lee/sw/cshals/cshals-w3c-semantic-web-tutorial.pdf .
- The document provides an overview of the basic syntax for implementing Dublin Core metadata in HTML, XML, and RDF. It discusses encoding Dublin Core elements, properties, value strings, and encoding schemes in each syntax.
- It also briefly discusses the OAI Protocol for Metadata Harvesting (OAI-PMH) and RSS, giving an example of an OAI-PMH request.
- The key aspects of the Dublin Core abstract model are summarized, including descriptions, statements, properties, values, and value strings.
The document provides an overview of document type definitions (DTDs) including:
- What a DTD is and why they are used
- The basic building blocks of DTDs including elements, attributes, entities, PCDATA, and CDATA
- How to declare elements and attributes in a DTD including allowed content and occurrences
- Examples of internal and external DTD declarations
The document provides an overview of XML schemas, including their purpose to specify the structure and data types of XML documents. It describes the basic components of schemas, including elements, simple and complex types, and attributes. It provides an example schema for a "friend" element and addresses.
Lambico is a project aiming to simplify the persistence layer of your applications by providing a manner for easily defining the DAOs that manage the data stored in your database.
With Lambico you can define the DAOs for your entities just writing their interfaces, with no implementation at all.
Parancoe 3 is a Web meta-framework which is using Lambico for its persistence layer, and the more recent features of Spring MVC.
This document provides an introduction to object-relational mapping using Hibernate. It discusses relational database design, object-oriented design, and the impedance mismatch between the two. It then explains how an ORM like Hibernate can map objects to relational databases while hiding SQL and connection details. Code examples demonstrate using Hibernate and JPA to perform CRUD operations instead of raw JDBC. Configuration of Hibernate and JPA is also summarized.
Formats for Exchanging Archival Data: An Introduction to EAD, EAC-CPF, and Ar...Michael Rush
Presented July 1, 2011, as part of the session "Standards, Information, and Data Exchange" at the 7th International Seminar of Iberian Tradition Archives, Rio de Janeiro, Brazil.
Introduction to the usage of DTDs in connection with XML documents. Elements and attributes are introduced in details. Use of ID, IDREF, and IDREFS for uniqueness and referring to elements are illustrated using a number of examples.
The document discusses XML and DTDs. It defines DTDs as describing the components and guidelines in an XML document by listing elements, attributes and their possible values, entities, and their interactions. It provides examples of element declarations in DTDs using tags like ELEMENT, EMPTY, ANY, and content models. It also distinguishes between internal and external DTDs and when each is generally used.
VIVO: An overview and its Implementation at Brown
Ted Lawless, Library Applications Developer, Library Integrated Technology Services, Brown University
Serendipity in Digital Collections: Enhancing Discovery with Linked Data Anna L. Creech, Head, Resource Acquisition and Delivery, Boatwright Memorial Library, University of Richmond
Should We Expect a Bang or a Whimper? Will Linked Data Revolutionize Scholar Authoring and Workflow Tools?
Jeff Baer, Senior Director of Product Management, Research Development Services, Proquest
This document discusses Smart Content and linked data applications at Elsevier. It provides an overview of Elsevier's efforts to develop a linked data repository and infrastructure that connects Elsevier content to external vocabularies and data sources. Examples are given of current Smart Content applications, including linking clinical trial data to drugs and adverse events, linking neuroscience articles to related methods and Wikipedia definitions, and highlighting energy terms in articles. Considerations for planning Smart Content projects are also outlined, such as focusing on use cases, ensuring quality and reliability of resources, planning for ongoing maintenance, and thorough testing.
This document discusses using RELAX NG for defining DITA document type shells and modules. It provides an overview of RELAX NG and how it is a good match for DITA requirements. It demonstrates how to create a RELAX NG shell that includes vocabulary and constraint modules to define a DITA document type, and how the RELAX NG files can be converted to generate conforming DTD and XSD shells and modules.
By now, you have heard how important structured content is. But, maybe you poked around with something like DITA and were baffled by the complexity. Or, maybe you still aren’t sure what XSLT stands for. This workshop will take participants back to the basics, to provide a foundation for higher-level concepts that have taken hold of our industry. Topics will include:
- What XML looks like, what it does, and how to create it.
- How to define a structure model, including whether to use a - DTD, Schema, etc.
- What XSLT looks like, what it does, and how to make it work.
- What DITA and DocBook really are and whether one is right for you.
Russell Ward is an experienced technical writer and structured technologies developer. He has spent many years working with structured content to maximize efficiency in the techcomm environment, both as an employee and as an independent consultant. He is also an experienced trainer and speaks periodically at conferences and other peer events.
This document provides an overview and tutorial on database concepts, SQL using MySQL. It aims to give the reader a lucid understanding of databases, relational database management systems (RDBMS), and SQL. The tutorial explains key concepts such as data normalization, data types, and the basic SQL commands of INSERT, DELETE, SELECT, and UPDATE. It also demonstrates creating a sample contacts database with multiple tables to illustrate storing and retrieving data using SQL queries.
XML (eXtensible Markup Language) is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. It is used to store and transport data. The document discusses XML, comparing it to HTML and SGML. It also covers XML parsers, schemas, namespaces, XSLT, and other XML concepts in detail.
XML is a markup language that allows users to define their own tags. It was created to describe data rather than display it like HTML. XML uses tags to provide context and meaning to data. Documents must follow specific rules to be considered well-formed, such as having matching start and end tags. Documents can also specify a document type definition (DTD) or schema to add additional structure and validation.
The document provides an introduction to XML, explaining that it stands for Extensible Markup Language and is used to transport and store structured data. It describes how XML uses tags to identify different types of content and relationships. DTDs (Document Type Definitions) are also introduced, which allow users to define rules for tags and relationships in an XML document.
Slides for a talk.
Talk abstract:
In the dark of the night, if you listen carefully enough, you can hear databases cry. But why? As developers, we rarely consider what happens under the hood of widely used abstractions such as databases. As a consequence, we rarely think about the performance of databases. This is especially true to less widespread, but often very useful NoSQL databases.
In this talk we will take a close look at NoSQL database performance, peek under the hood of the most frequently used features to see how they affect performance and discuss performance issues and bottlenecks inherent to all databases.
This document summarizes a presentation on optimizing application architecture. It discusses various data structures and algorithms like quicksort. It also discusses serialization protocols like Protocol Buffers and compares their performance. Other topics covered include immutable collections, concurrent collections, avoiding locks, and considering functional programming and reactive extensions. The presentation emphasizes principles like separation of concerns, writing tests, and avoiding premature optimization. It encourages thinking outside of object-oriented patterns and exploring new developments in distributed computing.
The document discusses XML schemas. It explains that an XML schema describes the structure of an XML document and is an alternative to DTDs. It is written in XML and supports data types and namespaces. The document provides examples of simple XML schemas defining elements and attributes, and using restrictions to define acceptable values for elements and attributes.
The document discusses XML schemas and their advantages over DTDs. It explains that XML schemas describe the structure of an XML document, are written in XML syntax, and support data types. The document provides examples of simple and complex element definitions in an XML schema, as well as examples of XML documents referencing a DTD and XML schema.
Digital publishing has changed. Understand the base components that allow modern publishers to more easily publish content in multiple formats across multiple platforms.
Presentation originally developed by Apex VP and Principal Consultant Bill Kasdorf for a university press in June 2016, based on presentations on this subject that he has given to many organizations over the past ten years. Learn more at www.apexcovantage.com.
The document summarizes Martin Odersky's talk at Scala Days 2016 about the road ahead for Scala. The key points are:
1. Scala is maturing with improvements to tools like IDEs and build tools in 2015, while 2016 sees increased activity with the Scala Center, Scala 2.12 release, and rethinking Scala libraries.
2. The Scala Center was formed to undertake projects benefiting the Scala community with support from various companies.
3. Scala 2.12 focuses on optimizing for Java 8 and includes many new features. Future releases will focus on improving Scala libraries and modularization.
4. The DOT calculus provides a formal
Panel presentation to a graduate class at the University of Arizona School of Information Resources and Library Science. Invited by Dr. Jana Bradley. July 2006.
XML provides a structured format for journal articles that can drive automated processing and allow for repurposing of content. It structures content with tags and can be transformed to different outputs through stylesheets. Adopting XML may increase efficiency for publishers that produce similar content over time by facilitating error-free processing and reuse of article data."
The document discusses XML (eXtensible Markup Language), its differences from HTML, and its uses and advantages. XML was designed to carry and store data, unlike HTML which was designed to display data. XML allows users to define their own elements and tags to structure information. It simplifies data sharing and transport between different platforms. XML schemas provide more power and flexibility than DTDs in defining XML documents and element structures.
Data interchange integration, HTML XML Biological XML DTDAnushaMahmood
Data interchange integration. Data interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML Biological XML DTDData interchange integration, HTML XML
XML is a markup language used to define custom document formats and data exchange standards. It allows users to define tags and attributes to structure text-based data. XML documents must adhere to rules like having matching start/end tags and a single root element to be considered well-formed. Document Type Definitions (DTDs) can be used to establish a fixed vocabulary and structure for XML documents in an application. XPath and XQuery are query languages that allow retrieving and manipulating parts of XML documents and datasets based on element names, attributes, values and structures.
Jump Start on Apache Spark 2.2 with DatabricksAnyscale
Apache Spark 2.0 and subsequent releases of Spark 2.1 and 2.2 have laid the foundation for many new features and functionality. Its main three themes—easier, faster, and smarter—are pervasive in its unified and simplified high-level APIs for Structured data.
In this introductory part lecture and part hands-on workshop, you’ll learn how to apply some of these new APIs using Databricks Community Edition. In particular, we will cover the following areas:
Agenda:
• Overview of Spark Fundamentals & Architecture
• What’s new in Spark 2.x
• Unified APIs: SparkSessions, SQL, DataFrames, Datasets
• Introduction to DataFrames, Datasets and Spark SQL
• Introduction to Structured Streaming Concepts
• Four Hands-On Labs
Decoding and developing the online finding aidkgerber
Workshop for the Library Technology Conference on Encoded Archival Description, and the mark-up languages involved in its use including HTML, XML, and XSLT.
Similar to NISO/NFAIS Joint Virtual Conference: Connecting the Library to the Wider World - Successful Applications of Linked Data (20)
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
This presentation was provided by William Mattingly of the Smithsonian Institution, during the closing segment of the NISO training series "AI & Prompt Design." Session Eight: Limitations and Potential Solutions, was held on May 23, 2024.
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NISO/NFAIS Joint Virtual Conference: Connecting the Library to the Wider World - Successful Applications of Linked Data
1. The Challenges of Describing Best
Tagging Practices for JATS
Jeffrey Beck, NCBI/NLM/NIH
NISO/NFAIS Joint Virtual Conference:
Connecting the Library to the Wider World:
Successful Applications of Linked Data
Wednesday, December 3, 2014
2. Intro to JATS
JATS refers to NISO Z39.96-2012 Journal Article
Tag Suite.
It is a NISO standard that describes XML
elements and attributes and three article
models in XML.
3. JATS was based on the “NLM DTDs”, which have
been used to describe journal articles since
2003.
The “NLM DTDs” grew out of work being done
on the NCBI PubMed Central (PMC) DTDs in
2002.
4. So, what is this DTD you speak of?
DTD is Document Type Definition
– One of many (3 really) schema languages for
defining XML documents
– Essentially a set of rules for what can be in your
document, what must be in your document, and the
order of things if you wish to enforce order
We’ll get to “Why DTD” later.
5. A Brief History
• NLM Version 1 was released in December
2002 with the Archiving and Interchange DTD
and the Journal Publishing DTD.
• Version 1 was based on work at NCBI to
upgrade the PubMed Central DTD and a
project at Harvard University funded by the
Mellon Foundation to address the problems of
archiving scholarly journals in electronic form
(E-journals).
6. • The initial meeting included participants from
NCBI, Harvard, and the Mellon Foundation
along with NCBI’s consultants, Mulberry
Technologies, and Harvard’s consultants,
Inera, Inc.
But there was confusion about what the model
should be.
7. Easy Target for Conversion?
• Should the new DTD be a broad, descriptive
target that would be easy to translate articles
from other SGML or XML models into?
A model like this would have many optional
elements with few things in a prescribed
order, and different ways to tag the same
object.
8. Easy model to create content in?
• Or should the new DTD be a narrower,
prescriptive target that would give creators of
new XML articles guidance about how to make
a valid article?
A model like this would have more required
elements with fewer choices on how to tag
the same object.
9. The DTD Spectrum
Optimized for Conversion to Optimized to Create Content in
10. The DTD Spectrum
Conversion Creation
Archive and Interchange DTD Journal Publishing DTD
21. JATS?
Journal Article Tag Suite
The Tag Suite is the collection of all Elements
and Attributes.
Each model (Archiving, Publishing, Authoring) is
a Tag Set.
Each schema (DTD, XSD, RELAX NG) represents a
model or Tag Set.
23. NLM DTDs v 2.1 September 2005
NLM DTDs v 2.0 November 2004
NLM DTDs v 1.1 November 2003
NLM DTDs v 1.0 March 2003
This was when the Article Archiving and Journal Publishing models
became more open and we added the Authoring model.
24. NLM DTDs v 2.2 June 2006
NLM DTDs v 2.1 September 2005
NLM DTDs v 2.0 November 2004
NLM DTDs v 1.1 November 2003
NLM DTDs v 1.0 March 2003
25. NLM DTDs v 1.0 March 2003
NLM DTDs v 1.1 November 2003
NLM DTDs v 2.0 November 2004
NLM DTDs v 2.1 September 2005
NLM DTDs v 2.2 June 2006
NLM DTDs v 2.3 March 2007
Decision to formalize standard with NISO
Laura Kelly suggested that this would be a
good time to clean up those little things that we
know are problems but we haven’t fixed
because we wanted all of the new models to be
backward-compatible.
26. Backward-compatibility
• Means that all existing XML instances will be
valid according to the new model.
• Mostly we had minor housekeeping issues that we
had been putting off.
• In version 1.0, the @id on <list-item> was
defined as CDATA (when it obviously should
have been defined as ID to allow ID/IDREF
functionality).
• So, any existing <list-item id=“45qrt”> would be
valid under version 1.0 but not valid when the
attribute was properly defined as type=ID.
27. NLM DTDs v 3.0 November 2008
NLM DTDs v 2.3 March 2007
NLM DTDs v 2.2 June 2006
NLM DTDs v 2.1 September 2005
NLM DTDs v 2.0 November 2004
NLM DTDs v 1.1 November 2003
NLM DTDs v 1.0 March 2003
Backward-incompatible release
28. NLM DTDs v 3.0 November 2008
NLM DTDs v 2.3 March 2007
NLM DTDs v 2.2 June 2006
NLM DTDs v 2.1 September 2005
NLM DTDs v 2.0 November 2004
NLM DTDs v 1.1 November 2003
NLM DTDs v 1.0 March 2003
Backward-incompatible release
NLM DTDs v 3.1
NLM DTD Working Group is dissolved, and
the NISO Journal Article Tag Suite Working
Group is created.
29. August 2012
NLM DTDs v 3.0 November 2008
NLM DTDs v 2.3 March 2007
NLM DTDs v 2.2 June 2006
NLM DTDs v 2.1 September 2005
NLM DTDs v 2.0 November 2004
NLM DTDs v 1.1 November 2003
NLM DTDs v 1.0 March 2003
Backward-incompatible release
NISO Z39.96-2012 is
official
NISO Z39.96 JATS v 0.4 March 2011
30. December 2013
August 2012
JATS v1.1d1
released
NLM DTDs v 3.0 November 2008
NLM DTDs v 2.3 March 2007
NLM DTDs v 2.2 June 2006
NLM DTDs v 2.1 September 2005
NLM DTDs v 2.0 November 2004
NLM DTDs v 1.1 November 2003
NLM DTDs v 1.0 March 2003
Backward-incompatible release
NISO Z39.96-2012 is
official
NISO Z39.96 JATS v 0.4 March 2011
JATS V1.1d2 - December
2014??
31. Maintained in DTD
• We deliver DTD, XSD, and RNG as non-normative
supporting material to the
standard.
• But the models are written and maintained in
DTD and the other schemas are derived from
them.
32. Q: But this means that you will not get any of
the advantages of the more modern schema
languages in JATS?
A: Yes. That is correct.
Q: And that is bad!
A: Not necessarily.
Q: But, but … data typing!!!
33. In defense of DTD
• First, DTD is still the schema language of
choice for most users of JATS – publishers and
tagging vendors.
34. But, but … data typing!!!
Data Typing gives the schema writer control
over the value of an element or attribute.
Like saying that a value must be an integer or
that a string of characters must be a date.
There is little datatyping in DTD.
35. Let’s consider dates
It is reasonable to say that when we are creating
content to publish, we want the values that are
written as dates to be dates.
• The 14th of Smoon
• January 7, 1
• 1947-02-30
Are all a little hinky and should not be published!
36. But what if they already exist?
If you are tagging a journal’s historical content in
XML and you come across an issue with a cover
date of February 30, 1947. What do you do?
A: Fix it!
Q: What is it “supposed” to be?
37. If a date can sometimes not be a date, then you can
not have a hard and fast rule built into your schema
that says it must be a date always.
{Thanks to Tommie Usdin of Mulberry Technologies
and Co-Chair of the JATS Standing Committee for
this wonderful example that I stole.}
38. So, how do you tag a … ?
• But sometimes people want to be told what to
do.
39. • The JATS Tag Sets - especially the Archiving
and Interchange and even the Journal
Publishing are very flexible models that allow
content to be tagged in different ways
40. A reasonable question
• (1) It seems from the element reference page for <chem-struct-wrap> that
one could omit explicit labels because "A <chem-struct-wrap> may also be
numbered, automatically by a formatting application or by preserving the
number inside a <label> element." Having seen this, but not found similar
comments about "automatic numbering" for other elements that may
typically be numbered/labelled, I would like to know what the assumption
is about omitting labels in general for these (e.g. chemical structures,
equations, figures, tables, etc.): is a formatting application expected by
default to generate a number/label? If so, is there a way to suppress
numbering for some occurrences?
• (2) Relatedly, what is the expected behaviour for an <xref> element that
has no content (e.g. one that (a) references an element for which
automatic numbering has been assumed and which therefore lacks a
<label>, or (b) one that references an element possessing a <label>)?
• Message from Simon Newton to jats-list@lists.mulberrytech.com on
September 7, 2011
41. A reasonable question
• (1) It seems from the element reference page for <chem-struct-wrap> that
one could omit explicit labels because "A <chem-struct-wrap> may also be
numbered, automatically by a formatting application or by preserving the
number inside a <label> element." Having seen this, but not found similar
comments about "automatic numbering" for other elements that may
typically be numbered/labelled, I would like to know what the
assumption is about omitting labels in general for these (e.g. chemical
structures, equations, figures, tables, etc.): is a formatting application
expected by default to generate a number/label? If so, is there a way to
suppress numbering for some occurrences?
• (2) Relatedly, what is the expected behaviour for an <xref> element that
has no content (e.g. one that (a) references an element for which
automatic numbering has been assumed and which therefore lacks a
<label>, or (b) one that references an element possessing a <label>)?
• Message from Simon Newton to jats-list@lists.mulberrytech.com on
September 7, 2011
42. A reasonable question
• (1) It seems from the element reference page for <chem-struct-wrap> that
one could omit explicit labels because "A <chem-struct-wrap> may also be
numbered, automatically by a formatting application or by preserving the
number inside a <label> element." Having seen this, but not found similar
comments about "automatic numbering" for other elements that may
typically be numbered/labelled, I would like to know what the
assumption is about omitting labels in general for these (e.g. chemical
structures, equations, figures, tables, etc.): is a formatting application
expected by default to generate a number/label? If so, is there a way to
suppress numbering for some occurrences?
• (2) Relatedly, what is the expected behaviour for an <xref> element that
has no content (e.g. one that (a) references an element for which
automatic numbering has been assumed and which therefore lacks a
<label>, or (b) one that references an element possessing a <label>)?
• Message from Simon Newton to jats-list@lists.mulberrytech.com on
September 7, 2011
43. • Simon was asking for “Best Practices”
• So I was thrilled to see the following response:
44. I don't think any assumptions are made regarding
when and exactly how numbering should be
automated; there is only a recognition that it
commonly done in publishing systems, and JATS is
designed to support this (or no numbering at all) or
not, depending on local policies.
Neither is there any expectation that by default, a
formatting application will number things.
This means you have both the opportunity and the
burden to define a policy that makes the most
sense for your data and workflow.
Message from Weldell Piez to jats-list@lists.mulberrytech.com on
September 8, 2011
45. I don't think any assumptions are made regarding
when and exactly how numbering should be
automated; there is only a recognition that it
commonly done in publishing systems, and JATS is
designed to support this (or no numbering at all) or
not, depending on local policies.
Neither is there any expectation that by default, a
formatting application will number things.
This means you have both the opportunity and the
burden to define a policy that makes the most
sense for your data and workflow.
Message from Weldell Piez to jats-list@lists.mulberrytech.com on
September 8, 2011
46. Best Practices must be scoped
• They must make sense with your content.
… with your workflow
… and for any users of your content down the
line.
47. The Standing Committee position
The JATS Standing Committee makes an effort to
make the Tag Suite as useful as possible for all
users: creators of content, publishers, archives,
and other aggregators.
To do this “all reasonable practices” are
documented as much as possible in the non-normative
supporting information available at
http://jats.nlm.nih.gov.
48. But there are efforts to define tagging best
practices – or at least practices.
49. PMC Tagging Guidelines
We have the PMC Tagging Guidelines
(http://www.ncbi.nlm.nih.gov/pmc/pmcdoc/tagging-guidelines/
article/style.html) – which is essentially a
"Best Practices" for tagging articles in NLM XML for
submission to PMC.
These are still surprisingly open.
50. In response to the article “Inconsistent XML as a Barrier
to Reuse of Open Access Content”, which focused on
inconsistent tagging in the PMC Open Access articles
available for reuse, a group of mainly open access
publishers formed a group called JATS for Reuse to define
some best tagging practices.
See http://jats4r.github.io/
(http://www.ncbi.nlm.nih.gov/books/NBK159964/)