Linköping electronic conference proceedings, Jan 3, 2024
This paper presents the Swedish National Doctoral School in Digital Humanities: Data, Culture, an... more This paper presents the Swedish National Doctoral School in Digital Humanities: Data, Culture, and Society-Critical Perspectives (DASH) that
Cataloging & Classification Quarterly, Nov 17, 2021
Abstract In the face of the ever-increasing document volume, libraries around the globe are more ... more Abstract In the face of the ever-increasing document volume, libraries around the globe are more and more exploring (semi-) automated approaches to subject indexing. This helps sustain bibliographic objectives, enrich metadata, and establish more connections across documents from various collections, effectively leading to improved information retrieval and access. However, generally accepted automated approaches that are functional in operative systems are lacking. This article aims to provide an overview of basic principles used for automated subject indexing, major approaches in relation to their possible application in actual library systems, existing working examples, as well as related challenges calling for further research.
Engleski jezik izborni: Drugi strani jezik pocetna razina ucenja: Nastavni materijali : English l... more Engleski jezik izborni: Drugi strani jezik pocetna razina ucenja: Nastavni materijali : English language, facultative: Second foreign language, beginner´s level: teaching materials
General rights Copyright and moral rights for the publications made accessible in the public port... more General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Humanities scholars can today engage in research inquiry using data from a range of varied collec... more Humanities scholars can today engage in research inquiry using data from a range of varied collections which are often characterised by poor subject access, often resulting in systems that underperform and even effectively prevent access to data, information and knowledge. In spite of the availability of professional standards and guidelines to provide quality-controlled subject access through knowledge organisation systems (KOS), subject access in such collections is rarely based on KOS. At the same time, KOS themselves may come with problems such as being slow to update, being rigidly structured and not incorporating end-users' vocabulary. It may therefore be useful to consider methods for remediating these deficiencies in KOSs, such as collecting user-generated metadata via social tagging or complementing automated indexing techniques with manual ones. To help address the above problems, the paper discusses these challenges and points to possible solutions in different contexts. It does so by reflecting on an open educational resource (OER) devoted to this theme, titled Introduction to Knowledge Organisation Systems for Digital Humanities. It was developed as part of an EU project called DiMPAH (Digital Methods Platform for the Arts and Humanities), 2021-2023, creating seven OERs for inclusion in DARIAH Teach.
Bulletin of the Association for Information Science and Technology : Special Issue : iSchools Aro... more Bulletin of the Association for Information Science and Technology : Special Issue : iSchools Around the World
Proceedings of the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) : ... more Proceedings of the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) : co-located with the 20th International Conference on Theory and Practice of Digital Libraries 2016 (TPDL 2016) : Hannover, Germany, September 9, 2016
With the exponential growth of the World Wide Web, automated subject classification of Web pages ... more With the exponential growth of the World Wide Web, automated subject classification of Web pages has become a major research issue in information and computer sciences. Organizing Web pages into a hierarchical structure for subject browsing is gaining more recognition as an important tool in information-seeking processes. In this thesis, different automated classification approaches, focusing on organizing textual Web pages into a browsable hierarchical structure, were critically examined and compared. Three major approaches to automated subject classification have been recognized, each coming from a different research community: machine learning, information retrieval and library science. While these approaches have common research aims and a number of methods and techniques, and as such could benefit from each other, it has been shown that authors belonging to the three communities do not communicate with authors from the other two communities to a large extent. The two biggest differences between the approaches are whether they employ a vector space model (machine learning and information retrieval), and whether they make use of controlled vocabularies such as, for example, classification schemes, thesauri, or ontologies (library science). Certain special characteristics of Web pages (e.g. metadata and structural elements such as title, headings, main text) were investigated as to how they could be best used in automated classification. The study indicated that all the structural information and metadata available in Web pages should be used in order to achieve the best automated classification results; however, the exact way of combining them proved not to be very important.
Purpose -In order to estimate the value of semi-automated subject indexing in operative library c... more Purpose -In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation. Design/methodology/approach -On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records. Findings -The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval. Originality/value -The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.
Linköping electronic conference proceedings, Jan 3, 2024
This paper presents the Swedish National Doctoral School in Digital Humanities: Data, Culture, an... more This paper presents the Swedish National Doctoral School in Digital Humanities: Data, Culture, and Society-Critical Perspectives (DASH) that
Cataloging & Classification Quarterly, Nov 17, 2021
Abstract In the face of the ever-increasing document volume, libraries around the globe are more ... more Abstract In the face of the ever-increasing document volume, libraries around the globe are more and more exploring (semi-) automated approaches to subject indexing. This helps sustain bibliographic objectives, enrich metadata, and establish more connections across documents from various collections, effectively leading to improved information retrieval and access. However, generally accepted automated approaches that are functional in operative systems are lacking. This article aims to provide an overview of basic principles used for automated subject indexing, major approaches in relation to their possible application in actual library systems, existing working examples, as well as related challenges calling for further research.
Engleski jezik izborni: Drugi strani jezik pocetna razina ucenja: Nastavni materijali : English l... more Engleski jezik izborni: Drugi strani jezik pocetna razina ucenja: Nastavni materijali : English language, facultative: Second foreign language, beginner´s level: teaching materials
General rights Copyright and moral rights for the publications made accessible in the public port... more General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Humanities scholars can today engage in research inquiry using data from a range of varied collec... more Humanities scholars can today engage in research inquiry using data from a range of varied collections which are often characterised by poor subject access, often resulting in systems that underperform and even effectively prevent access to data, information and knowledge. In spite of the availability of professional standards and guidelines to provide quality-controlled subject access through knowledge organisation systems (KOS), subject access in such collections is rarely based on KOS. At the same time, KOS themselves may come with problems such as being slow to update, being rigidly structured and not incorporating end-users' vocabulary. It may therefore be useful to consider methods for remediating these deficiencies in KOSs, such as collecting user-generated metadata via social tagging or complementing automated indexing techniques with manual ones. To help address the above problems, the paper discusses these challenges and points to possible solutions in different contexts. It does so by reflecting on an open educational resource (OER) devoted to this theme, titled Introduction to Knowledge Organisation Systems for Digital Humanities. It was developed as part of an EU project called DiMPAH (Digital Methods Platform for the Arts and Humanities), 2021-2023, creating seven OERs for inclusion in DARIAH Teach.
Bulletin of the Association for Information Science and Technology : Special Issue : iSchools Aro... more Bulletin of the Association for Information Science and Technology : Special Issue : iSchools Around the World
Proceedings of the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) : ... more Proceedings of the 15th European Networked Knowledge Organization Systems Workshop (NKOS 2016) : co-located with the 20th International Conference on Theory and Practice of Digital Libraries 2016 (TPDL 2016) : Hannover, Germany, September 9, 2016
With the exponential growth of the World Wide Web, automated subject classification of Web pages ... more With the exponential growth of the World Wide Web, automated subject classification of Web pages has become a major research issue in information and computer sciences. Organizing Web pages into a hierarchical structure for subject browsing is gaining more recognition as an important tool in information-seeking processes. In this thesis, different automated classification approaches, focusing on organizing textual Web pages into a browsable hierarchical structure, were critically examined and compared. Three major approaches to automated subject classification have been recognized, each coming from a different research community: machine learning, information retrieval and library science. While these approaches have common research aims and a number of methods and techniques, and as such could benefit from each other, it has been shown that authors belonging to the three communities do not communicate with authors from the other two communities to a large extent. The two biggest differences between the approaches are whether they employ a vector space model (machine learning and information retrieval), and whether they make use of controlled vocabularies such as, for example, classification schemes, thesauri, or ontologies (library science). Certain special characteristics of Web pages (e.g. metadata and structural elements such as title, headings, main text) were investigated as to how they could be best used in automated classification. The study indicated that all the structural information and metadata available in Web pages should be used in order to achieve the best automated classification results; however, the exact way of combining them proved not to be very important.
Purpose -In order to estimate the value of semi-automated subject indexing in operative library c... more Purpose -In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation. Design/methodology/approach -On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records. Findings -The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval. Originality/value -The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.
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Papers by Koraljka Golub
1. The agINFRA Linked Data layer Valeria Pesce Global Forum on Agricultural Research (GFAR) Giovanni L’Abate Consiglio per la Ricerca e la sperimentazione in Agricoltura Centro di ricerca per l’agrobiologia e la pedologia (CRA-ABP) Luca Matteis Koraljka Golub Research Data Alliance 4th Plenary Meeting 22-24 September 2014, Amsterdam Agricultural Data Interoperability Interest Group agINFRA project EC 7th framework program INFRA-2011-1.2.2 - Grant agr. no: 283770
2. agINFRA - Background • agINFRA: FP7 project EC 7th framework program INFRA-2011-1.2.2 - Grant agr. no: 283770 Objective: Promoting data sharing and development of trust in agricultural sciences • agINFRA Knowledge Fair co-located with the Agricultural Data Interoperability Interest group meeting at the RDA 4th Plenary Meeting • Types of data covered by agINFRA: bibliographic, educational, germplasm, soil
3. Interoperability 1 They are often both called vocabularies Metadata elements to describe individual “things” (entities, datums, series…) Aka metadata sets, metadata element sets, vocabularies Sets of values for (some of) the metadata elements Aka controlled vocabularies, authority data, value vocabularies, Knowledge Organization Systems (KOSs)
4. Various flavors of vocabularies Title Author(s) Abstract Subject(s) Publication date Publication place Type of document other features… Entity to be describedType? Bibliographic resource for describing bibliographic resources Metadata vocabulary Authority data KOS “Value vocabularies” Data of type Person Authority data Data of type Geographic location “Description vocabularies” Controlled list Concepts suitable for organizing by Topic Concepts suitable for organizing by Type for describing people Metadata vocabularyfor describing geographic places Ontology
5. Names of things URIs of things Links to other URIs Metadata vocabularies RDFs / OWL KOS SKOS Names of metadata elements URIs of classes and properties Links to other URIs Serialization into RDF Interoperability 2: RDF and Linked Data http://purl.org/dc/elements/1.1/contributorhttp://purl.org/ontology/bibo/editor“Editor” rdfs:subPropertyOf http://aims.fao.org/aos/agrovoc/c_6599 http://id.loc.gov/authorities/sh85113862#concept“Rice” skos:exactMatch
6. Names of metadata elements URIs of classes and properties Databases / tables / series Names of things URIs of things Links to other URIs http://vocabularies.aginfra.eu/soil#isObservedOnLocation • Then, other complex things like “URI de-referencing” and “content negotiation”… (some good triple store platforms do it out of the box) Interoperability 2: RDF and Linked Data http://purl.org/ontology/bibo/editor“Editor” https://aginfra- sg.ct.infn.it/rdf/cncp/resource/ObservedSoilSite/ 16.4CLcch1-1 http://vocabularies.aginfra.eu/soil#Obs ervedSoilProfile “Observed soil 16.4CLcch1” rdfs:type Serialization into RDF “Observed in location”
7. Tools used in agINFRA • For building and managing SKOS: the FAO VocBench • For publishing KOSs as Linked Data: SKOS loaded into Allegrograph • For building and publishing RDF vocabularies: Neologism • For publishing data as Linked Data: D2RQ from database to RDF > mapping to published classes and properties Links are provided in the last slide
8. Linked Data in agINFRA • Linked Data Vocabularies – Reference to existing relevant RDF vocabularies and SKOS – New RDF vocabularies only when not existing (e.g. soil ontology) – New KOS only when: • Not existing • Mapping needed between local concepts and published concepts • Extension needed • Linked Data datasets – Bibliographic data: AGRIS triple store – Germplasm data: • CAAS Linked Data API (presented later) • CRA triple store (presented later) – Soil data: CRA triple store (presented later)
9. agINFRA LOD vocabularies 9 Vocabularies. aginfra.eu agINFRA VocBench agINFRA Neologism http://202.73.13.50:55481/aginfra/ VEST Registry http://vocabularies.aginfra.eu http://vocabularies.aginfra.eu CIARD RING Existing vocabularies KOSs Metadata / ontologies New agINFRA vocabularies http://aims.fao.org/vest-registry http://ring.ciard.net TOOLS agINFRA shop CIARD directories http://202.45.139.84:100 35/catalogs/fao/repositori es/agINFRA Triple store
10. URLs of agINFRA Linked Data vocabulary platforms • agINFRA overview of vocabularies: http://vocabularies.aginfra.eu • New agINFRA Soil Vocabulary: http://vocabularies.aginfra.eu/soil# • VocBench instances: http://202.73.13.50:55481/aginfra/ http://artemide.art.uniroma2.it/vocbench2 • Allegrograph triple store of agINFRA KOSs: http://202.45.139.84:10035/catalogs/fao/repositories/ag INFRA
11. Namespaces of agINFRA new vocabularies • agINFRA Soil vocabulary: http://vocabularies.aginfra.eu/soil# • CRA Soil Terms: http://data.entecra.it/rdf/kos/soil/ or http://soilmaps.entecra.it/rdf/kos/soil/ • CRA Germplasm Terms: http://data.entecra.it/rdf/germplasm/soil/ or http://planta-res.entecra.it/rdf/kos/germplasm/ • agINFRA Resource Types Terms: http://aginfra.eu/voc/aginfra_doctypes/ • agINFRA Educational Resources Terms: http://aginfra.eu/voc/aginfra_eduterms/
12. Example 1: the Soil Terms KOS Rationale: • CRA had local lists of values for several soil properties • In most cases those values mapped conceptually with terms in published KOSs Local values published as new KOS with mappings to USDA Soil Taxonomy terms and/or WRB whenever possible
13. Soil Terms: starting from a database table Excel file
14. Table loaded into the VocBench as SKOS
15. Example 2: Resource types in AGRIS Starting from a table Concept Type of Concept Relationship among concepts Bibliography Top broadMatch http://purl.org/dc/dcmitype/Text Book Top NT Handbook/Manual broadMatch http://purl.org/dc/dcmitype/Text Conference BT Event broadMatch http://purl.org/dc/dcmitype/Event Dictionary Top broadMatch http://purl.org/dc/dcmitype/Text Directory Top relatedTerm http://purl.org/dc/dcmitype/Collection Drawing BT Image broadMatch http://purl.org/dc/dcmitype/Image Encyclopaedia Top broadMatch http://purl.org/dc/dcmitype/Text Event Top NT Conference exactMatch http://purl.org/dc/dcmitype/Event Extension Top Film Top broadMatch http://purl.org/dc/dcmitype/MovingImage Graphics BT Image broadMatch http://purl.org/dc/dcmitype/Image Handbook/Manual BT Book broadMatch http://purl.org/dc/dcmitype/Text Image Top NT Drawing, NT Graphics, NT MapsorAtlases exactMatch http://purl.org/dc/dcmitype/Image JournalArticle Top NT Preprint broadMatch http://purl.org/dc/dcmitype/Text Lit.Review Top broadMatch http://purl.org/dc/dcmitype/Text Manuscript Top broadMatch http://purl.org/dc/dcmitype/Text MapsorAtlases BT Image broadMatch http://purl.org/dc/dcmitype/Image News Top Non-Conventional Top NumericalData Top broadMatch http://purl.org/dc/dcmitype/Dataset Other Top Patent Top broadMatch http://purl.org/dc/dcmitype/Text Preprint BT JournalArticle broadMatch http://purl.org/dc/dcmitype/Text Report Top broadMatch http://purl.org/dc/dcmitype/Text Sound/Music Top broadMatch http://purl.org/dc/dcmitype/Sound Speech Top broadMatch http://purl.org/dc/dcmitype/Sound Standard Top broadMatch http://purl.org/dc/dcmitype/Text Summary Top broadMatch http://purl.org/dc/dcmitype/Text Thesaurus Top broadMatch http://purl.org/dc/dcmitype/Text Thesis Top broadMatch http://purl.org/dc/dcmitype/Text Website Top External mapping
16. AGRIS resource types in the VocBench http://aginfra.eu/voc/aginfra_doctypes/
17. Example 3: the Soil VocabularyStartingfromtheINSPIREUMLrepresentation
18. http://vocabularies.aginfra.eu/soil# INSPIRE data model agINFRA Soil Vocabulary RDF model
19. agINFRA LOD data 19 Germplasm data http://[CAAS-API-base-URL]/germplasm/rest https://aginfra-sg.ct.infn.it/rdf/cncp/ CIARD RING Existing datasets CAAS CRA New agINFRA datasets http://ring.ciard.net DATASETS agINFRA shop? CIARD directories Germplasm data Soil data API https://aginfra-sg.ct.infn.it/rdf/... ?? CRA Triple store CRA Triple store CKAN CKAN Dataverse AGRIS GLN
20. Namespaces of agINFRA partners’ Linked Data • Sustainability namespaces with the data owners • CRA data: data.entecra.it (presented later) – http://data.entecra.it/rdf/soil/ temporarily at https://aginfra-sg.ct.infn.it/rdf/cncp/ – http://data.entecra.it/rdf/germplasm/ temporarily at http://93.63.35.32:8080/d2rq/ • CAAS data (presented later) – API: http://www.cgris.net/pquery.asp • AGRIS data – http://agris.fao.org/aos/ 20
21. Useful links • agINFRA project: http://aginfra.eu • agINFRA vocabularies: http://vocabularies.aginfra.eu • Tools: – VocBench: http://aims.fao.org/tools/vocbench-2 – Neologism: http://neologism.deri.ie/ – Allegrograph: http://franz.com/agraph/allegrograph/ – D2RQ: http://d2rq.org/
22. The end Thank you for your attention Valeria Pesce Giovanni L’Abate Luca Matteis Koraljka Golub