Category Archives: Knowledge Models

PhySH – Physics Subject Headings

Short Description

PhySH (Physics Subject Headings) is a physics classification scheme developed by the American Physical Society to organize journal, meeting, and other content by topic, available for use starting in January 2016. It is intended initially to meet the specific goals of the APS, while a longer term goal is to make it available for use by the broader community. PhySH consists of hierarchies of concepts grouped into facets: Research Areas, Physical Systems, Properties, Techniques, and Professional Topics. The concepts are also organized by discipline for convenience. Individual concepts may belong to more than one facet or discipline.

URL

http://physh.aps.org/

Owned/Developed by

  1. Name of Owner: American Physical Socety
  2. Technical Contact:  Arthur Smith, *protected email*
  3. License Contact: Mark Doyle, *protected email*

Adopted (as opposed to owned) by organizations/publishers:
How is this KM applied?

  1. Manually
  2. By Authors and Editorial Staff

How is this KM used?

  1. Classify manuscripts within the APS peer-review process
  2. Help editors in finding similar articles previously submitted and in finding suitable referees

Description of the current use case(s) of the KM

  1. Manuscripts are assigned concepts from PhySH by submitting authors; these assignments are reviewed and may be modified by editors.
  2. For each journal section, relevant concepts are assigned to the most appropriate handling editor who is knowledgeable in that area
  3. Editors can search for other articles on the same or related topics

Description of the future/potential use cases of the KM (not yet realized)

  1. Improve finding relevant content across APS journals, which often have overlapping scopes
  2. Link relevant content from other APS non-journal areas (e.g., meetings)
  3. Map other classification systems (eg. PACS) to PhySH to enable older material to be indexed in the same way
  4. Allow individuals (particularly referees) to identify their areas of expertise
  5. Integrate with other knowledge models – For example, an independent taxonomy for chemical substances or astronomical objects should be relatively easy to append to PhySH.
  6. PhySH concepts have permanent identifiers allowing them to be integrated into the web of linked data.

What are the main goals for using this KM?

  1. Improve the peer-review process for our journals by ensuring the right expertise is applied in reviews (PACS, which was previously used for this, ceased updating in 2010).
  2. Cover all of physics
  3. Improve discovery – Content properly tagged with PhySH is intended to enable new and useful ways to browse and search the content while providing the underpinnings for recommendation systems and other personalized services.

Rationale for KM vs other means of searching and browsing?

  1. By providing a standardized list of “keywords” rather than relying on author-supplied terms or full-text or statistical indexing, we can have a greater assurance that related articles are associated with one another.

Is the KM being actively developed?

  1. Yes, internally – also feedback is welcome, see physh.aps.org website for links.

License information:

  1. PhySH is copyrighted with all rights reserved by the American Physical Society. We are still considering what license we would use for any public release of PhySH.

Linking NPG ontologies to external datasets

 

We (Macmillan Science and Education) have made efforts to begin linking our domain models to external datasets.  Our article-types, journals and subjects models are now linked to DBpedia (Wikipedia) and Wikidata.  Our subjects model is additionally linked to Bio2RDF and MeSH.

Also, our core model is now linked to a number of other external models (CIDOC, FaBIO, schema.org, etc.).

Our models, now including these links, are available to view or download at nature.com/ontologies.

We will continue to refine and expand these links and would be interested in any thoughts, ideas and feedback from the community, particularly around any additional datasets we should consider linking to.

NPG Article Types Ontology

The NPG ArticleTypes Ontology is a categorization of kinds of publication which are used to index and group content published by Springer Nature. This taxonomy is organised into a single tree using the SKOS vocabulary. It includes article-types that are directly applied to content, such as Article, Review Article, News, or Book Review plus higher-level groupings such as Research, News and Comment, or Amendments and Corrections.

URL OF KNOWLEDGE MODEL:

http://www.nature.com/ontologies/models/domain/article-types/

OWNED/DEVELOPED BY:

ADOPTED (AS OPPOSED TO OWNED) BY ORGANIZATIONS/PUBLISHERS:

Springer Nature

HOW IS THIS KM APPLIED?

Applied manually by authors or editorial staff as part of the standard publishing workflow.

DESCRIPTION OF THE CURRENT USE CASE(S) OF THE KM

This model allows us to categorize content based on the type of publication, allowing content of similar type to be grouped or filtered at varying degrees of granularity.

IS THE KM BEING ACTIVELY DEVELOPED?

Yes, internally

LICENSE INFORMATION:

CC0 – http://creativecommons.org/about/cc0

Auto-tagging

We have a deep taxonomy of CS concepts – at the deepest level of the tree there are seven levels. The most useful concepts for precision search are of course the most granular concepts represented by the leaves of the tree.

However, concepts can be multi-parented, so the accurate application of a concept to a text requires that the context within the tree, i.e., the correct branch, be understood.

While expert authors who apply the terms to their articles have varying degrees of interest and attention to this indexing task, our experience shows that they rarely misapply terms – sometimes they appear lazy and are happy to assign only high-level concepts such as “Software” which is not too useful.

However, our experience with an auto-tagger shows that a huge amount of “noise” is created. We consider the noise unacceptable – presenting it to users will create distrust in the taxonomy itself.

We have been expanding the logical rules of the auto-tagger in an effort to reduce the noise to an acceptable level. So far, without success.

I have been trying to understand why.

So far, the best explanation I can come up with is that while hierarchical context is readily understood by the human brain, auto-taggers based on statistical occurrences of a concept and within proximity of other words and concepts, cannot accurately reproduce hierarchical context.

Any advice would be appreciated.

NPG Subjects Ontology

The NPG Subjects Ontology is a polyhierarchical categorization of scholarly subject areas which are used for the indexing of content by Springer Nature. It includes subject terms of varying levels of specificity such as Biological sciences (top level), Cancer (level 2), or B-2 cells (level 7). In total there are more than 2750 subject terms, organised into a polyhierarchical tree using the SKOS vocabulary.

URL

http://www.nature.com/ontologies/models/domain/subjects/

Owned/Developed by:

Adopted by Organizations / Publishers:

How is this KM applied?

Applied manually, by authors or editorial staff as part of the standard publishing workflow, or by professional indexers

Description of the current use cases of the KM

The NPG Subjects Ontology constitutes the main backbone of nature.com subject areas, a new section on nature.com that allows users to browse content topically rather than navigate via the more usual journal paradigm. Each of the terms in the ontology includes a link to the relevant subject page on nature.com.

Is the KM being actively developed?

Yes, internally

 License Information:

CC0 – http://creativecommons.org/about/cc0

NICEM Thesaurus

Short Description

Thesaurus of the National Information Center for Educational Media (NICEM), used for indexing the records of NICEM’s bibliographic database.

Owned / Developed by

  1. Name of Owner – Access Innovations, Inc.
  2. Name of Developer – Access Innovations, Inc.
  3. Technical Contact – Mary Garcia, *protected email*
  4. License Contact – *protected email*

How is this KM applied?

  1. Manually | Auto-tagging software | Both
  2. By Authors | Editorial Staff | Professional indexers

How is this KM used?

  1. Direct Bibliographic Search | Indirect (e.g., used to expose content resulting from other user actions)
  2. Display | Grouping of results
  3. People search | Author profiles | Publication profile

Description of the current use cases of the KM

Used for indexing bibliographic records of non-print educational media in the NICEM database.

What are the main goals for using this KM?

  1. Enhance UX
  2. Increase Search Engine Ranking
  3. Increase time user spends on site
  4. Increase traffic
  5. Increase downloads

Rationale for KM vs other means of searching and browsing?

The thesaurus contains terms that reflect the subject matter of educational material, especially at the K-12 levels. An associated rule base that has been developed specifically for those terms enables appropriate indexing and accurate retrieval of bibliographic records, as well as user-friendly browsing in conjunction with a search interface.

 Is the KM being actively developed?

  1. Yes, internally

License Information:

  1. Terms of license or link to license terms – Contact *protected email*.

NewsIndexer Thesaurus

Short Description

An indexing system for the newspaper industry. A specialized group of terms with the newspaper industry’s indexing needs in mind. The vocabulary is divided into sections that correspond to the sections of a typical newspaper. An accompanying rule base enables highly accurate categorization of newspaper articles.

URL

http://www.newsindexer.com

Owned/Developed by

  1. Name of Owner: Access Innovations, Inc.
  2. Name of Developer: Access Innovations, Inc.
  3. Technical Contact: Mary Garcia, *protected email*
  4. License Contact:  Marjorie Hlava, *protected email*

Adopted (as opposed to owned) by organizations/publishers:
How is this KM applied?

  1. Manually and Auto-tagging software
  2. By Editorial Staff | Professional indexers

How is this KM used?

  1. Direct Bibliographic Search
  2. Display

Description of the current use case(s) of the KM

Customized version used by Acquire Media for categorization of news items, and RSS delivery according to customers’ interests.

Description of the future/potential use cases of the KM (not yet realized)

Categorization of news stories (including archived stories) by and for newspaper publishers; indexing of 20th and 21st century historical studies.

What are the main goals for using this KM?

  1. Increase downloads

Rationale for KM vs other means of searching and browsing?

Every news day, you can tag the articles as they are produced through a cloud service or installed on your own local servers. We automatically feed this data through NewsIndexer, which scans every article and searches for terms similar to those in its controlled vocabulary. NewsIndexer then displays these terms for the human indexer’s review and approval. For backfile collections you can just accept the indexing as an automatic batch process. For ongoing daily feeds you might want to review all or a random sample of the results on a regular basis for maintenance.

Is the KM being actively developed?

  1. Yes, internally

License information:

http://www.newsindexer.com/contact.htm

Thesaurus of Psychological Index Term®

SHORT DESCRIPTION/ABOUT

The Thesaurus of Psychological Index Terms® is the controlled vocabulary used by APA’s professional indexers to index all of APA’s databases:  PsycINFO®, PsycARTICLES®, PsycBOOKS®, PsycEXTRA®, PsycTESTS®, PsycTHERAPY®,  and sycCRITIQUES®.  With the wide variety of concepts and vocabulary used in the psychological literature, search and retrieval of specific psychological concepts is virtually impossible without the controlled vocabulary of the Thesaurus. It provides a way of structuring the  diverse concepts in the field of psychology to assist in the creation of efficient and consistent indexing.   The Thesaurus , first published in 1974, has an influential role in research because it reflects the most current trends found in the behavioral and social science literature.  The Thesaurus can help authenticate the use of terms as they become accepted nomenclature.

URL OF KNOWLEDGE MODEL:

OWNED/DEVELOPED BY:

  1. Name of Owner: The American Psychological Association
  2. Name of Developer: Ian Galloway
  3. Technical Contact: igalloway [at] apa.org
  4. License Contact: Jan Fleming, jfleming [at] apa.org

HOW IS THIS KM APPLIED?

  1. Manually | Auto-tagging software | Both
  2. By Authors | Editorial Staff | Professional indexers

HOW THIS IS KM USED?

  1. Direct Bibliographic Search | Indirect (e.g., used to expose content resulting from other user actions)
  2. Display | Grouping of results
  3. People search | Author profiles | Publication profile

DESCRIPTION OF THE CURRENT USE CASE(S) OF THE KM:

The Thesaurus of Psychological Index Terms is currently used primarily to index over 3.7 million records that can be found in PsycINFO.

DESCRIPTION OF FUTURE/POTENTIAL USE CASES OF THE KM (NOT YET REALIZED)

Development of an ontology based on the structure and concepts found in the Thesaurus is currently underway.

WHAT ARE THE MAIN GOALS FOR USING THIS KM?

  1. Enhance UX
  2. Increase Search Engine Ranking
  3. Increase time user spends on site
  4. Increase traffic
  5. Increase downloads
  6. …)

RATIONALE FOR KM VS OTHER MEANS OF SEARCHING AND BROWSING?

The sheer volume of APA’s databases means that researchers need a pragmatic and efficient way to discover the precise records they are seeking. The Thesaurus provides the most targeted way find the major concepts within our database records.  The Thesaurus has been developed specifically to work with the interdisciplinary nature of the psychological literature. In conjunction with faceted searching, researchers can quickly sift through over 3 million records dating back to the 19th century with confidence.

IS THE KM BEING ACTIVELY DEVELOPED?

Yes, internally

LICENSE INFORMATION:

Terms of license or link to license terms: http://www.apa.org/about/contact/copyright/index.aspx

ACM Computing Classification System (CCS)

Short Description

ACM has published a de facto standard taxonomy for classifying and indexing computing literature and researchers’ areas of expertise since the 1960s. The CCS underwent a major overhaul in 1982 with substantive updates in 1998 and 2012.

The 2012 CCS was created by group of 120 ACM volunteers, a third of them ACM Fellows, who collaborated with ACM Staff and with Semedica, a Division of Silverchair.

The Update Project was led by Professor Zvi Kedem of NYU who served as its Editor-in-Chief, working closely with Bernard Rous, ACM Director of Publications.

The 2012 ACM Computing Classification System has been developed as a poly-hierarchical ontology that can be utilized in semantic web applications. It relies on a semantic vocabulary as the single source of categories and concepts that reflect the state of the art of the computing discipline and is receptive to structural change as it evolves in the future.

ACM has provided tools to facilitate the application of 2012 CCS categories to forthcoming papers.

URL OF KNOWLEDGE MODEL:

http://dl.acm.org/ccs.cfm

The full CCS classification tree is freely available for educational and research purposes in these downloadable formats: SKOS (xml), Word, and HTML. In the ACM Digital Library, the CCS is presented in a visual display format that facilitates navigation and feedback. The full CCS classification tree is also viewable as a flat file in the Digital Library.

 OWNED/DEVELOPED BY:

  1. Owner: ACM
  2. Developer: ACM-Semedica
  3. Technical Contact: Bernard Rous (rous [at] @hq.acm.org)
  4. License Contact: Deborah Cotton (cotton [at] hq.acm.org)

ADOPTED BY:

Various libraries, companies, and publishers such as Springer, IEEE, and Emerald have made use of the ACM CCS.

 HOW IS THIS KM APPLIED?

  1. ACM articles are generally indexed manually. Auto-tagging software is being evaluated.
  2. Index terms are applied by ACM authors and by professional indexers.
  3. A map of the 1998 CCS to the 2012 version has been built and automatically run against all articles in the ACM Digital Library. Both the 1998 and 2012 sets of concepts are available on Citation Pages of all indexed articles at this time.
  4. In displays of Article Citation Page under “Index Terms” tab. (See: 1145/1963190.1963191)
  5. In tag cloud displays of topics covered by specific publications (See: http://dl.acm.org/pub.cfm?id=J401) or Special Interest Groups (See: http://dl.acm.org/sig.cfm?id=SP923) or Institutional Profile pages (See: http://dl.acm.org/inst_page.cfm?id=60022148)
  6. CCS subjects are included in the index for Simple Search
  7. CCS subjects are directly searchable in Advanced Search. See left bottom of page: http://dl.acm.org/advsearch.cfm
  8. CCS subjects are themselves clickable to return papers indexed by those concepts
  9. CCS subjects are currently displayed on Author Profiles pages under Subject Areas. (See: http://dl.acm.org/author_page.cfm?id=81100246710)

DESCRIPTION OF FUTURE/POTENTIAL USE CASES OF THE KM (NOT YET REALIZED)

ACM is building a community and people-oriented search where the primary objects returned are experts, their attributes, and their contextual relationships. Published works will become attributes of the author (rather than the primary object of bibliographic search where authors are attributes of the published.) One clear use of the CCS in this new facility is the direct and immediate ability to discover people who are expert in one of the defined subject areas; to order them by their impact in that area; and display their working relationships.

Additionally, the 2012 CCS is only partially deployed in the ACM Digital Library today. Sections of the ACM DL still rely on the 1998 version of the CCS.

 WHAT ARE THE MAIN GOALS FOR USING THIS KM?

To enable efficient and precise discovery and exploration of topics

The ACM CCS is a hierarchical taxonomy. It is designed to provide a cognitive map of the computing space from the most general subject areas to the most specific topics.

RATIONALE FOR KM VS OTHER MEANS OF SEARCHING AND BROWSING?

When speaking of taxonomies in computer science circles, the question is often asked “Why bother? Taxonomies are antiquated; Google renders them unnecessary; and the ACM CCS is not used by anyone other than authors who are required to index their ACM articles with it, much to their irritation.”

There are certainly camps within the Information Retrieval community on this issue; one tends to dismiss the usefulness of taxonomies in today’s world while another sees them as powerful and with growing application. In the scientific, technical, and medical (STM) publishing domain, the taxonomic approach to semantic classification is booming — with publishers using taxonomy to allow users to cross-cut content topically, increasing application usage.

CCS searches in the ACM Digital Library have been a relatively small percentage of total searches. Yet some part of the user community finds the CCS very useful in search. Despite the fact that direct searching on CCS subject categories is not highly visible (being found rather cryptically at the bottom left of the Advanced Search page (http://portal.acm.org/advsearch.cfm), the annual number of CCS searches launched in the ACM DL is still about half a million. Adjustments in the Digital Library user interface to promote the CCS as a retrieval tool should multiply this number many fold.

Many scholarly publishers in the scientific, technical, and medical fields are making use of taxonomic classification to create topic collections and virtual journals that dynamically rebuild as new content is added.

ACM efforts to derive topical visualizations from our full-text index proved inferior to those derived from taxonomic terms. Using author-supplied keywords (which are not selected from a controlled vocabulary) was somewhat better but also proved inferior.

Google-type searching appears best suited to directed searches where the user knows exactly what he is looking for. Google supplies almost total recall and the user supplies the precision. For more general subject exploration and discovery purposes, the searches do not work quite as well. And the page-ranking algorithm itself skews results by defining relevance in terms of popularity. Finally, it should be noted that Google is well aware of how its indexes are enhanced by structured, fielded data leading to improved precision in searches; that is why Google Scholar at least has tried to make arrangements with all the publishers whose sites it crawls to provide specific standard meta-tagging. Most publishers, including ACM, have complied in their indexing agreements with Google Scholar.

Lastly, a robust up-to-date taxonomy provides a cognitive map of the discipline. This in itself can be useful in understanding what computer science is all about; where a specific area of concentration fits within the broader discipline; and in development of curricula.

IS THE KM BEING ACTIVELY DEVELOPED?

Yes. The ACM CCS itself is evolving along with its deployment.

 LICENSE INFORMATION:

The full CCS classification tree is freely available for educational and research purposes in these downloadable formats: SKOS (xml), Word, and HTML.

For commercial use, please write cotton [at] hq.acm.org

Unified Astronomy Thesaurus

Short Description:

The Unified Astronomy Thesaurus (UAT) is an open, interoperable and community-supported thesaurus which unifies the existing divergent and isolated Astronomy & Astrophysics thesauri into a single high-quality, freely-available open thesaurus formalizing astronomical concepts and their inter-relationships.

URL:

http://astrothesaurus.org/

Owned/Developed by:

  1. Name of Owner: American Astronomical Society, http://aas.org/
  2. Name of Developer:  Katie Frey, ADS, https://groups.google.com/d/forum/uat-users

Adopted (as opposed to owned) by organizations/publishers:

IOP Publishing intend to use this for auto-indexing of images in the the AAS Astronomy Image Explorer and for indexing content on IOPsience journals and books platform.

Is the KM being actively developed?

  1. Yes by ADS and the Astronomy Community, http://astrothesaurus.org/

License information:

  1. Name of License
  2. Terms of license or link to license terms