Taxonomy is a useful way to categorize your content so you can find it, re-use it, and help users browse and search through your content. It also helps with search engine optimization.
This document discusses taxonomy and metadata. It defines taxonomy as a classification scheme designed to group related things together, which can be informal or highly formalized. Taxonomies are semantic and provide a fixed vocabulary to label content meaningfully. Taxonomies act as knowledge maps and artificial memory devices by structuring concepts. The document also defines metadata as "data about data" such as author, title, and other information about a document. Metadata is used to identify, manage, retrieve, and connect content, as well as support business processes and records management. Standards like Dublin Core are discussed, as well as challenges around enforcing metadata use and acquiring metadata from users.
This document discusses taxonomies, metadata, and how they work together. It defines taxonomy as a hierarchical classification system and metadata as data that describes other data. Taxonomies facilitate organization, discovery, and retrieval of resources, while metadata supports identification and management. Both taxonomies and metadata can evolve over time through standards development and user contributions. When used together, taxonomies provide a classification structure and metadata describes resources within that structure.
Multisided Exposure Fairness for Search and RecommendationBhaskar Mitra
Online information access systems, like recommender systems and search, mediate what information gets exposure and thereby influence their consumption at scale. There is a growing body of evidence that information retrieval (IR) algorithms that narrowly focus on maximizing ranking utility of retrieved items may disparately expose items of similar relevance from the collection. Such disparities in exposure outcome raise concerns of algorithmic fairness and bias of moral import, and may contribute to both representational harms—by reinforcing negative stereotypes and perpetuating inequities in representation of women and other historically marginalized peoples—and allocative harms, from disparate exposure to economic opportunities. In this talk, we present a framework of exposure fairness metrics that model the problem jointly from the perspective of both the consumers and producers. Specifically, we consider group attributes for both types of stakeholders to identify and mitigate fairness concerns that go beyond individual users and items towards more systemic biases in retrieval. The development of expected exposure based metrics also opens up new opportunities and challenges for model optimization. We demonstrate how stochastic ranking policies can be optimized towards target expected exposure and highlight the trade-offs that may exist in optimizing for different fairness dimensions.
Presentation given on March 12, 2013 by Marjorie M.K. Hlava of Access Innovations, Inc. as a webinar for the San Francisco chapter of the Special Libraries Association.
UPGMA is an algorithm for constructing phylogenetic trees from distance matrix data. It works by sequentially clustering the two closest groups at each step, computing distances between new clusters and other groups as the average of all pairwise distances. UPGMA assumes a molecular clock and produces rooted, ultrametric trees reflecting phenotypic similarities rather than true evolutionary relationships.
This document discusses taxonomy and metadata. It defines taxonomy as a classification scheme designed to group related things together, which can be informal or highly formalized. Taxonomies are semantic and provide a fixed vocabulary to label content meaningfully. Taxonomies act as knowledge maps and artificial memory devices by structuring concepts. The document also defines metadata as "data about data" such as author, title, and other information about a document. Metadata is used to identify, manage, retrieve, and connect content, as well as support business processes and records management. Standards like Dublin Core are discussed, as well as challenges around enforcing metadata use and acquiring metadata from users.
This document discusses taxonomies, metadata, and how they work together. It defines taxonomy as a hierarchical classification system and metadata as data that describes other data. Taxonomies facilitate organization, discovery, and retrieval of resources, while metadata supports identification and management. Both taxonomies and metadata can evolve over time through standards development and user contributions. When used together, taxonomies provide a classification structure and metadata describes resources within that structure.
Multisided Exposure Fairness for Search and RecommendationBhaskar Mitra
Online information access systems, like recommender systems and search, mediate what information gets exposure and thereby influence their consumption at scale. There is a growing body of evidence that information retrieval (IR) algorithms that narrowly focus on maximizing ranking utility of retrieved items may disparately expose items of similar relevance from the collection. Such disparities in exposure outcome raise concerns of algorithmic fairness and bias of moral import, and may contribute to both representational harms—by reinforcing negative stereotypes and perpetuating inequities in representation of women and other historically marginalized peoples—and allocative harms, from disparate exposure to economic opportunities. In this talk, we present a framework of exposure fairness metrics that model the problem jointly from the perspective of both the consumers and producers. Specifically, we consider group attributes for both types of stakeholders to identify and mitigate fairness concerns that go beyond individual users and items towards more systemic biases in retrieval. The development of expected exposure based metrics also opens up new opportunities and challenges for model optimization. We demonstrate how stochastic ranking policies can be optimized towards target expected exposure and highlight the trade-offs that may exist in optimizing for different fairness dimensions.
Presentation given on March 12, 2013 by Marjorie M.K. Hlava of Access Innovations, Inc. as a webinar for the San Francisco chapter of the Special Libraries Association.
UPGMA is an algorithm for constructing phylogenetic trees from distance matrix data. It works by sequentially clustering the two closest groups at each step, computing distances between new clusters and other groups as the average of all pairwise distances. UPGMA assumes a molecular clock and produces rooted, ultrametric trees reflecting phenotypic similarities rather than true evolutionary relationships.
دورة تدريبية بعنوان تصنيف ديوي العشري
إعداد وتقديم :مصطفى شاكر محمود
أخصائي مكتب - اتمكتبة جامعة قطر
E-mail :mostafshaker@qu.edu.qa
Phone :+974 4403 6343
Joint Multisided Exposure Fairness for Search and RecommendationBhaskar Mitra
(Slides from my talk at SEA: Search Engines Amsterdam)
Online information access systems, like recommender systems and search, mediate what information gets exposure and thereby influence their consumption at scale. There is a growing body of evidence that information retrieval (IR) algorithms that narrowly focus on maximizing ranking utility of retrieved items may disparately expose items of similar relevance from the collection. Such disparities in exposure outcome raise concerns of algorithmic fairness and bias of moral import, and may contribute to both representational harms—by reinforcing negative stereotypes and perpetuating inequities in representation of women and other historically marginalized peoples—and allocative harms, from disparate exposure to economic opportunities. In this talk, we present a framework of exposure fairness metrics that model the problem jointly from the perspective of both the consumers and producers. Specifically, we consider group attributes for both types of stakeholders to identify and mitigate fairness concerns that go beyond individual users and items towards more systemic biases in retrieval.
Extraction of common conceptual components from multiple ontologiesValentina Carriero
Understanding large ontologies, with diverse semantics and modelling practices, is still an issue, and has an impact on many ontology engineering tasks. While existing methods summarise ontologies by extracting the most important nodes or subgraphs, a complete overview of an ontology, and a comparison between multiple ontologies, are not supported. Based on the hypothesis that ontologies are designed as compositions of patterns, this slides present a method able to extract conceptual components from multiple ontologies and the observed ontology design patterns implementing them.
related paper: https://arxiv.org/abs/2106.12831
Entrez is a search engine developed by the National Center for Biotechnology Information (NCB) that allows users to search and retrieve data from over 20 integrated biological databases, including sequences, gene records, citations, and abstracts. It provides a single interface to access all linked information on genes and proteins. Users can perform text searches using Boolean operators and view results in various formats like FASTA and XML.
Digital Object Identifier (DOI): Introduction and Applications Nader Ale Ebrahim
The Digital Object Identifier (DOI) is used for identifying intellectual property in the digital environment. The DOI is like a digital fingerprint: Each article receives a unique one at birth, and it can be used to identify the article throughout its lifespan, no matter where it goes. A DOI should be interpreted as 'digital identifier of an object' rather than 'identifier of a digital object'. A DOI can be assigned to any Object. In this workshop you will learn how to define a DOI, prepare Meta Data, and assign a DOI for a journal paper.
Survey of softwares for phylogenetic analysisArindam Ghosh
The document discusses the process of phylogenetic analysis using cytochrome c oxidase subunit 1 (COX1) gene sequences from several organisms: human, bovine, zebrafish, pig, and sheep. It provides the COX1 protein sequences for each organism downloaded from UniProt. The sequences will be aligned using Clustal Omega and a phylogenetic tree will be constructed using Clustal W2 to analyze the evolutionary relationships between the organisms.
Event: Plant and Animal Genomes Conference 2012.
Speaker: Bert Overduin
The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) provides a comprehensive record of the world's nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. Major components of ENA include the Sequence Read Archive (SRA) for next generation data and EMBL-Bank for assembled and annotated sequences. ENA works closely together with NCBI and DDBJ as partners in the International Nucleotide Sequence Database Collaboration (INSDC). Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our INSDC partners. Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and provides a portfolio of interactive and programmatic submission services to ensure the smoothest flow possible of data into the public domain. ENA data can be searched using rapid sequence similarity and text search services provided both within web-based tools and under programmatic interfaces. Data can be retrieved in a variety of appropriate widely adopted formats through a web browser and extensive REST services. This presentation will consist of an introduction to ENA, followed by a short demonstration of the various ways data can be browsed and retrieved.
The document discusses sequence similarity searching and comparison. It describes how programs like BLAST and FASTA are used to rapidly identify similarities between sequences and determine evolutionary relationships. BLAST and FASTA utilize word matching and heuristics to efficiently search large databases and return local or global alignments with scoring of matches. They provide a powerful method for functions prediction by comparing new sequences to known genes and proteins.
Optimiser le SEO de son site e commerce BtoC : arborescence idéales et bonnes...Julien Dereumaux
Programme :
Les principes importants en e-commerce
La structure idéale de son site e-commerce
Exemple et études de cas
Résultats et conseils
A la fin du webinar, vous allez avoir tout en main pour optimiser votre site, générer des leads plus qualifiés en plus grande quantité, gagner énormément de temps au quotidien et surtout prendre du plaisir à créer votre site !
Vous savez ce qu'il vous reste à faire, participez en live pour profiter de toutes les meilleurs pratiques !
En plus c'est gratuit ! :-)
Dictionaries and Tolerant Retrieval.pptManimaran A
The document discusses dictionaries and tolerant retrieval in information retrieval systems. It describes different data structures that can be used to store term dictionaries for inverted indexes, including arrays, hash tables, binary trees, and B-trees. It also discusses how to handle wildcard queries using techniques like permuterm indexes and k-gram indexes. The document explains methods for spell checking documents and queries, such as edit distance, weighted edit distance, n-gram overlap, and Soundex.
يُعد الإشراف التربوي من الأركان الرئيسة والفاعلة في أي نظامٍ تعليمي، لأنه يسهم في تشخيص واقع العملية التعليمية التعلُّمية من الناحيتين الفنية والإدارية، وبما يتلاءم والتطورات الحديثية في المجالات التربوية والتقنية.
This document discusses sequence alignment and the differences between global and local alignment. It defines sequence alignment as comparing two or more sequences to find identical or similar characters in the same order. Global alignment attempts to align the entire sequences, while local alignment finds the regions of highest similarity that may only be part of the sequences. Dynamic programming is used to calculate optimal alignments through initialization of a scoring matrix, filling it, and tracing back the highest scores. The Needleman-Wunch algorithm performs global alignment, while Smith-Waterman performs local alignment by setting negative scores to zero to terminate early alignments.
Semantic search uses language processing to analyze the meaning of content and search queries to return more relevant results. It involves classifying content using taxonomies, identifying named entities, extracting relationships between entities, and matching these based on meaning. Implementing semantic search requires preparing content through classification, metadata, and information architecture, as well as technologies for semantic tagging, entity extraction, triple stores, and integrating these capabilities with existing search and content management systems.
Taxonomies are essential to making the web "go". Information architects and content strategists can use and promote taxonomy within their organizations to increase findability and usability of a website. Learn more about taxonomies and see some great examples.
دورة تدريبية بعنوان تصنيف ديوي العشري
إعداد وتقديم :مصطفى شاكر محمود
أخصائي مكتب - اتمكتبة جامعة قطر
E-mail :mostafshaker@qu.edu.qa
Phone :+974 4403 6343
Joint Multisided Exposure Fairness for Search and RecommendationBhaskar Mitra
(Slides from my talk at SEA: Search Engines Amsterdam)
Online information access systems, like recommender systems and search, mediate what information gets exposure and thereby influence their consumption at scale. There is a growing body of evidence that information retrieval (IR) algorithms that narrowly focus on maximizing ranking utility of retrieved items may disparately expose items of similar relevance from the collection. Such disparities in exposure outcome raise concerns of algorithmic fairness and bias of moral import, and may contribute to both representational harms—by reinforcing negative stereotypes and perpetuating inequities in representation of women and other historically marginalized peoples—and allocative harms, from disparate exposure to economic opportunities. In this talk, we present a framework of exposure fairness metrics that model the problem jointly from the perspective of both the consumers and producers. Specifically, we consider group attributes for both types of stakeholders to identify and mitigate fairness concerns that go beyond individual users and items towards more systemic biases in retrieval.
Extraction of common conceptual components from multiple ontologiesValentina Carriero
Understanding large ontologies, with diverse semantics and modelling practices, is still an issue, and has an impact on many ontology engineering tasks. While existing methods summarise ontologies by extracting the most important nodes or subgraphs, a complete overview of an ontology, and a comparison between multiple ontologies, are not supported. Based on the hypothesis that ontologies are designed as compositions of patterns, this slides present a method able to extract conceptual components from multiple ontologies and the observed ontology design patterns implementing them.
related paper: https://arxiv.org/abs/2106.12831
Entrez is a search engine developed by the National Center for Biotechnology Information (NCB) that allows users to search and retrieve data from over 20 integrated biological databases, including sequences, gene records, citations, and abstracts. It provides a single interface to access all linked information on genes and proteins. Users can perform text searches using Boolean operators and view results in various formats like FASTA and XML.
Digital Object Identifier (DOI): Introduction and Applications Nader Ale Ebrahim
The Digital Object Identifier (DOI) is used for identifying intellectual property in the digital environment. The DOI is like a digital fingerprint: Each article receives a unique one at birth, and it can be used to identify the article throughout its lifespan, no matter where it goes. A DOI should be interpreted as 'digital identifier of an object' rather than 'identifier of a digital object'. A DOI can be assigned to any Object. In this workshop you will learn how to define a DOI, prepare Meta Data, and assign a DOI for a journal paper.
Survey of softwares for phylogenetic analysisArindam Ghosh
The document discusses the process of phylogenetic analysis using cytochrome c oxidase subunit 1 (COX1) gene sequences from several organisms: human, bovine, zebrafish, pig, and sheep. It provides the COX1 protein sequences for each organism downloaded from UniProt. The sequences will be aligned using Clustal Omega and a phylogenetic tree will be constructed using Clustal W2 to analyze the evolutionary relationships between the organisms.
Event: Plant and Animal Genomes Conference 2012.
Speaker: Bert Overduin
The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) provides a comprehensive record of the world's nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. Major components of ENA include the Sequence Read Archive (SRA) for next generation data and EMBL-Bank for assembled and annotated sequences. ENA works closely together with NCBI and DDBJ as partners in the International Nucleotide Sequence Database Collaboration (INSDC). Data arrive at ENA from a variety of sources. These include submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centres and routine and comprehensive exchange with our INSDC partners. Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and provides a portfolio of interactive and programmatic submission services to ensure the smoothest flow possible of data into the public domain. ENA data can be searched using rapid sequence similarity and text search services provided both within web-based tools and under programmatic interfaces. Data can be retrieved in a variety of appropriate widely adopted formats through a web browser and extensive REST services. This presentation will consist of an introduction to ENA, followed by a short demonstration of the various ways data can be browsed and retrieved.
The document discusses sequence similarity searching and comparison. It describes how programs like BLAST and FASTA are used to rapidly identify similarities between sequences and determine evolutionary relationships. BLAST and FASTA utilize word matching and heuristics to efficiently search large databases and return local or global alignments with scoring of matches. They provide a powerful method for functions prediction by comparing new sequences to known genes and proteins.
Optimiser le SEO de son site e commerce BtoC : arborescence idéales et bonnes...Julien Dereumaux
Programme :
Les principes importants en e-commerce
La structure idéale de son site e-commerce
Exemple et études de cas
Résultats et conseils
A la fin du webinar, vous allez avoir tout en main pour optimiser votre site, générer des leads plus qualifiés en plus grande quantité, gagner énormément de temps au quotidien et surtout prendre du plaisir à créer votre site !
Vous savez ce qu'il vous reste à faire, participez en live pour profiter de toutes les meilleurs pratiques !
En plus c'est gratuit ! :-)
Dictionaries and Tolerant Retrieval.pptManimaran A
The document discusses dictionaries and tolerant retrieval in information retrieval systems. It describes different data structures that can be used to store term dictionaries for inverted indexes, including arrays, hash tables, binary trees, and B-trees. It also discusses how to handle wildcard queries using techniques like permuterm indexes and k-gram indexes. The document explains methods for spell checking documents and queries, such as edit distance, weighted edit distance, n-gram overlap, and Soundex.
يُعد الإشراف التربوي من الأركان الرئيسة والفاعلة في أي نظامٍ تعليمي، لأنه يسهم في تشخيص واقع العملية التعليمية التعلُّمية من الناحيتين الفنية والإدارية، وبما يتلاءم والتطورات الحديثية في المجالات التربوية والتقنية.
This document discusses sequence alignment and the differences between global and local alignment. It defines sequence alignment as comparing two or more sequences to find identical or similar characters in the same order. Global alignment attempts to align the entire sequences, while local alignment finds the regions of highest similarity that may only be part of the sequences. Dynamic programming is used to calculate optimal alignments through initialization of a scoring matrix, filling it, and tracing back the highest scores. The Needleman-Wunch algorithm performs global alignment, while Smith-Waterman performs local alignment by setting negative scores to zero to terminate early alignments.
Semantic search uses language processing to analyze the meaning of content and search queries to return more relevant results. It involves classifying content using taxonomies, identifying named entities, extracting relationships between entities, and matching these based on meaning. Implementing semantic search requires preparing content through classification, metadata, and information architecture, as well as technologies for semantic tagging, entity extraction, triple stores, and integrating these capabilities with existing search and content management systems.
Taxonomies are essential to making the web "go". Information architects and content strategists can use and promote taxonomy within their organizations to increase findability and usability of a website. Learn more about taxonomies and see some great examples.
The document discusses how taxonomy and metadata can improve enterprise search. It provides an overview of several taxonomy and search strategies, including tuned search/best bets, faceted search, tagging, clustering, and disambiguation. Tuned search maps common search terms to specific landing pages or results. Faceted search allows filtering results by taxonomy categories. Metadata can be explicit tags or implicit structural elements. The document argues that taxonomy drives effective search by providing a common language and organizing information to improve precision and recall.
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “The Role of Taxonomy and Ontology in Semantic Layers” at a webinar hosted by Progress Semaphore on April 16, 2024.
Taxonomies at their core enable effective tagging and retrieval of content, and combined with ontologies they extend to the management and understanding of related data. There are even greater benefits of taxonomies and ontologies to enhance your enterprise information architecture when applying them to a semantic layer. A survey by DBP-Institute found that enterprises using a semantic layer see their business outcomes improve by four times, while reducing their data and analytics costs. Extending taxonomies to a semantic layer can be a game-changing solution, allowing you to connect information silos, alleviate knowledge gaps, and derive new insights.
Hedden, who specializes in taxonomy design and implementation, presented how the value of taxonomies shouldn’t reside in silos but be integrated with ontologies into a semantic layer.
Learn about:
- The essence and purpose of taxonomies and ontologies in information and knowledge management;
- Advantages of semantic layers leveraging organizational taxonomies; and
- Components and approaches to creating a semantic layer, including the integration of taxonomies and ontologies
The document discusses striking a balance between navigation and search when organizing information. It recommends:
1. Developing a taxonomy to categorize information into a hierarchical structure based on subject, type, or other facets. This taxonomy can then be applied in a system like SharePoint.
2. Using the taxonomy for both navigation, where users can browse categories, and search, where search results are structured according to the taxonomy.
3. Maintaining the taxonomy over time through an incremental process that engages users and keeps the structure consistent, easy to use, and aligned with how users think about information.
This presentation delivers a detailed understanding of taxonomy definitions, taxonomy value (ROI), and taxonomy design methodologies and approaches. It was originally delivered by Zach Wahl and Tatiana Cakici of Enterprise Knowledge at Taxonomy Boot Camp 2019 in Washington, DC.
The document provides guidance on initial steps for developing a search application, including validating the need for full-text search, identifying ideal search results, considering clustering results, and producing requirements and choosing a technology. Some key recommendations include sketching out ideal results for sample queries, determining how results should be ordered and presented, and considering if and how results could be clustered. Determining ideal results and clustering options can help drive specific requirements and the selection of an appropriate technology.
Taxonomy: Hero of Advanced Content - SXSW 2019Laura Creekmore
I gave this presentation at SXSW 2019, talking about how content structure can enhance your work on advanced content channels like AI, voice skills, chatbots, and ecommerce.
Information Architecture Primer - Integrating search,tagging, taxonomy and us...Dan Keldsen
This document discusses the importance of taxonomy and classification within an information architecture. It defines key terms like taxonomy, thesaurus, ontology, and classification. It explains that taxonomy and classification help address the eternal problems of effectively cataloging and retrieving unstructured information. The document also discusses challenges like ambiguity, multiple meanings of words, and the importance of browsing versus searching in navigating large amounts of information.
Presentation to the Information & Knowledge Management Society in Singapore, March 2008, on approaches to integrating controlled and uncontrolled vocabularies.
Taxonomies, while critical, are often created in collaboration with businesses and in isolation from users, which leads to misalignment of expectations and a disconnection from their mental models. But testing taxonomy is not difficult, doesn't have to be expensive, and offers clearly identifiable value to projects. In this very practical session you'll learn about when to test, the different kind of tests available, and what works best (and what doesn't) at different stages of different projects.
Presented at IA Summit 2015 with Dave Cooksey
RDFS can be used to create taxonomies and ontologies that define relationships between terms. Taxonomies are useful for enterprises to enhance search, browsing, and content reuse which can increase productivity. Large, public taxonomies in domains like biology have been developed and can be leveraged by applications through semantic annotation services.
The document discusses how to gain understanding from big data through effective data governance and classification. It argues that proper categorization of data using controlled vocabularies, taxonomies, and ontologies improves search, analytics and other uses of big data. A framework is presented outlining the key components of a data governance lifecycle for big data, including content creation, mining and classification, management of vocabularies/taxonomies/ontologies, and use of the structured data for search, transactions and analytics. Effective use of this framework can help organizations apply meaning and understanding to their big data.
Taxonomy 101: What do rockets and arugula have in common?AvenueCX
The document provides an introduction to taxonomies. It defines a taxonomy as a system for organizing content according to shared characteristics, which are often organized hierarchically. Taxonomies help people find relevant information quickly, provide access to broader audiences, ensure consistency of language, allow for content integration and reuse, and enable personalization. The document encourages attendees to tag content for others to find by keeping tags simple, focusing on main concepts, being specific, and not worrying about perfection.
Organization systems aim to design labeling and organization that makes information easy for users to find. Content should be clearly organized with critical information up top and related elements grouped together. Both exact schemes like alphabetical and ambiguous schemes like topic-based are used to organize content. Organization structures include hierarchies for a top-down approach, databases for a bottom-up approach, and hypertext for linking information chunks. Effective organization requires considering user needs and testing different schemes and structures.
Mining Institutional Knowledge: Using Text and Data Mining to Enhance DiscoveryMary Ellen Bates
I review some of the initiatives that knowledge managers and special librarians have led to enhance information and map internal and external content through text and data mining, and will offer a checklist of the questions an info pro needs to ask when evaluating knowledge mapping tools. Presented at SLA Annual Conference 2020.
RDFS can be used to define taxonomies and ontologies for organizing information. It allows defining relationships like broader/narrower terms which enables enhanced search capabilities and faceted browsing. Large, curated taxonomies in domains like biology have been developed and are widely used to power semantic annotation services and applications that deliver benefits like improved content management, search, and knowledge reuse.
This is a high-level summary of three important ways to help people find information. The slides were presented at Vera Rhoades' information architecture class at the University of Maryland.
The document discusses hybrid approaches to taxonomy and folksonomy for information organization. It describes how taxonomies and folksonomies each have strengths and weaknesses. Hybrid approaches discussed include having taxonomies and folksonomies co-exist, using tags to influence taxonomy development, and presenting taxonomy terms as tags for users. The document also outlines some corporate social tagging tools.
This document discusses strategies for implementing social media and metadata management in SharePoint. It begins with definitions of social media and metadata. It then discusses why metadata is important for enabling search, discovery, and reuse of content. Common problems with inconsistent or lacking metadata are explained. The document outlines best practices for planning a social media strategy including defining requirements, centralizing taxonomy, and recruiting key stakeholders. Emerging technologies that integrate with social media are also highlighted.
Similar to What Is Taxonomy and Why Is It Useful? (20)
Many websites rely on search instead of good information architecture, but many times search isn't well designed. This presentation reviews how to look at site search analytics, metadata and taxonomy, and user testing to improve the internal search
1. The document discusses three ways to make taxonomy development more effective: considering next steps in design; taking into account team and technology capabilities; and thinking strategically before design.
2. It provides examples from projects where lessons were learned about understanding stakeholder needs, educating others about taxonomy, and ensuring technology capabilities support the taxonomy.
3. Thinking strategically involves doing research, identifying possibilities and conditions needed, barriers, and efforts to overcome barriers in order to support business goals with the taxonomy.
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A step-by-step process for looking at your website, discovering the problems with the content, prioritizing these problems and then solving them. Takes an information architecture and content strategy approach.
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The document discusses the intersection of information architecture, content strategy, and user experience. It begins with definitions of information architecture and content strategy, noting they both deal with organizing and presenting information but information architecture is more spatial while content strategy is more temporal. It then compares the tools and deliverables of each, such as site maps and wireframes. The document discusses how information architecture and content strategy can work together on activities like usability testing and content inventories. It concludes by considering the future of both fields and how practitioners can better communicate and work across the disciplines.
Guiding Others Through the Maze: Working with Stakeholders to Build a TaxonomyTheresa Putkey
The document discusses how to guide stakeholders through building a taxonomy. It recommends holding a taxonomy workshop to provide history, examples, and an overview of the process. If a workshop is not possible, concepts should be covered one-on-one using examples. The taxonomy should be reviewed and iterated on frequently to get feedback and demonstrate functionality. Involving stakeholders in building parts allows them to learn, and maintenance indicates understanding of principles.
The document discusses principles of taxonomy. It covers a brief history of taxonomies, modern uses of taxonomies, the purpose of taxonomies including finding related items and improving search results, and how to build and maintain a taxonomy including conducting a content audit and determining relationships between terms. It also discusses transferring taxonomy skills to other domains.
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Meet up Milano 14 _ Axpo Italia_ Migration from Mule3 (On-prem) to.pdfFlorence Consulting
Quattordicesimo Meetup di Milano, tenutosi a Milano il 23 Maggio 2024 dalle ore 17:00 alle ore 18:30 in presenza e da remoto.
Abbiamo parlato di come Axpo Italia S.p.A. ha ridotto il technical debt migrando le proprie APIs da Mule 3.9 a Mule 4.4 passando anche da on-premises a CloudHub 1.0.
Instagram has become one of the most popular social media platforms, allowing people to share photos, videos, and stories with their followers. Sometimes, though, you might want to view someone's story without them knowing.
1. What Is Taxonomy and Why
Is It Useful?
Theresa Putkey
Information Architect & Taxonomist
Key Pointe Usability Consulting, Inc.
tputkey@keypointe.ca
@tputkey
www.keypointe.ca
2. What Is Taxonomy?
Many libraries organize their books by the Dewey Decimal
System. When you walk into a library, you might see thousands
of books. If it weren’t for the Dewey Decimal System, you
wouldn’t know which books are where. Dewey let’s you find
books based on things like author and subject, without having to
look at every single book.
3. What Is Taxonomy?
Using a taxonomy in a corporate, government, or organizational
environment has the same effect.
A taxonomy is a list of terms you use to categorize and find your
information again, without having to look through every file,
image, document, or web page.
4. Examples of Taxonomy
It’s easiest to understand taxonomy by looking at a few
examples. Here are some projects Key Pointe has
worked on in the past.
5. Example 1
A not-for-profit had a lot of files related
to their product offerings. The files were
a mess across several network drives
and personal hard drives.
They needed to implement a digital
asset management (DAM) system to
keep track of the files and they needed
a taxonomy to help them categorize and
find these files.
While they did use a file structure, not
everyone understood the file naming or
structure and they needed a different
way to find files.
6. Example 2
A technology company was re-doing
their Support website and needed to
categorize their information by subject.
They had different products, services,
and topics and wanted to allow users to
access these topics in different ways.
They also wanted to use taxonomy to
dynamically display content on pages,
so they didn’t have to hand code every
link.
7. Example 3
An investment company was re-doing
their intranet site. Content was created
by different teams about the same
topic. They wanted to make sure the
intranet users could find all content
about the same topic, regardless of
which team created it or where it was
saved on the intranet. They also wanted
to improve their search results page to
allow users to filter their search results
by taxonomy.
8. Why Is Taxonomy Helpful?
Based on the examples, we can create some themes
for how taxonomy helps us on the web.
9. Information Overload
● We have software products that are extremely
information heavy
● Managed with wCMS, eCMS, cCMS, DAM, PIM, MAM
● How do we keep track of all the things in those systems?
● Not everyone understands the logic behind a file system
● Taxonomy gives us another avenue to categorize and find
information
10. It’s Helpful to Content Authors
● Categorize information to find it again
● Can re-use content or link to it more easily
● Dynamically display information on a website instead of
building pages by hand
● Controlling terminology so authors are using consistent
wording
11. It’s Helpful to Users
● Find information outside of a traditional folder structure
● Find via familiar terminology
● Increases accuracy of search results
● Allows the search results to be filtered by taxonomy
12. Taxonomy In Action
Here are some examples of taxonomy in action, to help
you visualize how taxonomy is helpful on the web.
15. Users Can Find
an Item Despite
Idiosyncratic
Naming
I.e. Aubergine=Purple!
16. Users Can Find
an Item Despite
Different (but
correct!)
Naming
I.e. Mark Twain is the same
as Samuel Clemens
17. Summary
Taxonomy is a categorization technique which allows
us to find information without having to remember
exactly where it’s stored.
It helps us with finding content, re-using content,
dynamically creating web pages, filtering search
results, and improving the search results displayed.
18. Learn More
Use Information Architecture and Taxonomy to Improve SEO
The Accidental Taxonomist by Heather Hedden
Making the Case: Explaining Taxonomy to Business People
Everything you ever wanted to know about taxonomies from NISO
19. About Key Pointe Usability
Consulting
Through User Research, Information Architecture, and
Taxonomy, Key Pointe Usability Consulting researches
usability problems, develops website structures, and
creates designs that balance user expectations with
business needs. Key Pointe’s process results in intuitive
content and effective internal and external search
strategies for user-friendly customer experiences.