SKOS Research Articles

A dictionary to identify small molecules and drugs in free text

From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers. We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated corpus, and conclude the following: (i) each of the different processing steps increase precision with a minor loss of recall; (ii) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (iii) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (iv) the performance of a dictionary based on ChemIDplus alone is comparable to the performance of the combined dictionary. The combined dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web site http://www.biosemantics.org/chemlist.

Standards and best practices in scientific data management: Promoting interoperability and re‐use (parts 1 & 2)

AbstractThe practice of science has changed in the last three decades due to the rapid development of information and communication technologies and massive increases in computing capacity. The networked environment enables scientists around the world to access the real time data and information directly from his or her desktop. As the International Council for Science states, “Secondary analyses of data, and the combining of data from multiple sources, are opening up exciting new scientific horizons. Scientific publication practices are changing rapidly” (ICSU, 2005, 16–17). These changes have inspired the introduction of the term, e‐Science, to refer to the “dynamic, multi‐sector, and highly heterogeneous” scientific practices that new technologies have made possible (ARL, 2007). E‐Science is science that will be increasingly carried out through distributed global collaborations enabled by the Internet. A typical feature of such collaborative scientific enterprises is that they require access to very large data collections, very large scale computing resources and high performance visualization back to the individual user scientists (National e‐Science Center, 2004, p. 4). At the same time, there is a significant increase in small scale science, allowing for disparate yet related research to be unified via eScience developments.This session will reflect the impact that e‐Science has had on scientific data management. Computers and computerized instruments, in the laboratory, in the field, across the world, and above the earth, produce and analyze large volumes of data, manipulate variables that can't easily be controlled in nature, run models and simulations that would otherwise be harmful to humans or to the environment, replicate situations that occur at a single point in time, and produce results and analysis faster and cheaper than science conducted at the bench or in the field. E‐Science not only uses large datasets, it creates them. The link between online journals and digital data, relatively inexpensive storage, the ability of ever improving network infrastructures to transport this data, increased computing power, even at the desktop, and the implementation of Service Oriented Architectures makes the data more accessible and promotes its reuse. Governments, foundations and academic institutions are increasingly requiring the deposit of data. Increasingly, validating research means finding the data, and ensuring its chain of custody.This session will give insight into the role and activities of libraries in this new science environment. Librarians, information scientists and information management professionals in the sciences have been organizing, managing and describing traditional scientific products, such as journal articles and technical reports, for years, using a body of standards and best practices developed over time. However, scientists, practitioners, engineers, educators and students are now looking for and using data from a variety of sources, and information professionals supporting science are called upon to manage data to ensure accessibility, educated selection of the data, appropriate combination across disciplines, informed re‐use; and preservation and archiving.This double session, organized by the ASIST Standards Committee and SIG‐STI, will explore the emerging standards and best practices related to scientific data management. The findings and recommendations of a multi‐agency, multi‐disciplinary U.S. federal government effort to promote reliable, accessible digital data will provide an introduction to the requirements and issues surrounding the management of scientific data. The importance of basing standards and best practices on the needs of a community of practice will be discussed. Dryad, a data repository for research data underlying published research in the field of evolutionary biology and related disciplines, will serve as an example of how specific standards and practices can be employed in an information architecture to enable data discovery, access, preservation and reuse as well as interoperability with other data repositories. The unique characteristics of data and efforts to make data more findable through federation and data modeling will be described, and the application of existing library standards will be assessed. International practices and standards, such as the W3C's Simple Knowledge Organization System (SKOS), the Geospatial Metadata Standard (ISO 19115) and Data Registry Standard (ISO/IEC 11179), will be discussed in the context of exchanging international environmental data. Finally, the impact of these activities on the emerging field of data librarianship/curation will be described.The speakers' presentations will be followed by a panel discussion, which will encourage audience participation. The objective will be to identify similar approaches across the science communities represented, and to propose next steps that the ASIST Standards Committee and others might undertake.

CHRONOS architecture: Experiences with an open-source services-oriented architecture for geoinformatics

CHRONOS's purpose is to transform Earth history research by seamlessly integrating stratigraphic databases and tools into a virtual on-line stratigraphic record. In this paper, we describe the various components of CHRONOS's distributed data system, including the encoding of semantic and descriptive data into a service-based architecture. We give examples of how we have integrated well-tested resources available from the open-source and geoinformatic communities, like the GeoSciML schema and the simple knowledge organization system (SKOS), into the services-oriented architecture to encode timescale and phylogenetic synonymy data. We also describe on-going efforts to use geospatially enhanced data syndication and informally including semantic information by embedding it directly into the XHTML Document Object Model (DOM). XHTML DOM allows machine-discoverable descriptive data such as licensing and citation information to be incorporated directly into data sets retrieved by users.

Concept naming vs concept categorisation: a faceted approach to semantic annotation

PurposeThe purpose of this paper is to show that concept naming alone in document annotation is not sufficient to convey the thought content of the information resource. The paper presents an outline of semantic document annotation which combines two major processes: facet analysis and concept categorisation. This is also an effort to show how RDF schema can be designed and implemented so that the properties of the schema are able to express the basic structure of the subject matter of the resource.Design/methodology/approachThis paper presents a methodology for representing the subject matter of a document in terms of RDF. For the purposes of faceted subject annotation, it has developed an extended RDF schema for simple knowledge organisation system (SKOS). The facets and relationships of the faceted subject indexing language postulate‐based permuted subject indexing system (POPSI) have been transformed into RDFS classes. The elementary categories of POPSI form the property classes in the POPSI/RDF Schema. These property classes have been used to formulate the subject description of a document.FindingsThe subject annotation of a document using this schema expresses all the components of the thought content of an information resource.Practical implicationsThe examples given in this paper show the applicability of this schema in describing resources in web directories and annotating scholarly documents in digital libraries. In a broader perspective, this provides a methodology for formulating the subject metadata of web resources. This schema helps in formulating the subject string(s) for a resource outlining the skeleton structure of its thought content.Originality/valueSKOS has been developed as an RDF schema representation of the traditional knowledge organisation systems. But the schema has limited room to accommodate subject indexing languages. The present schema extends the SKOS schema to accommodate the representation of faceted subject indexing languages. The faceted subject annotation system has been adopted for the very reason that it has precedence over the enumerated classification systems, controlled vocabulary lists, etc. The potential to describe the specific subject of the document with more accuracy and representation of context gives the faceted subject indexing languages strength to make the subject description explicit and machine processible.

Semantic heterogeneity: comparing new semantic web approaches with those of digital libraries

PurposeTo demonstrate that newer developments in the semantic web community, particularly those based on ontologies (simple knowledge organization system and others) mitigate common arguments from the digital library (DL) community against participation in the Semantic web.Design/methodology/approachThe approach is a semantic web discussion focusing on the weak structure of the Web and the lack of consideration given to the semantic content during indexing.FindingsThe points criticised by the semantic web and ontology approaches are the same as those of the DL “Shell model approach” from the mid‐1990s, with emphasis on the centrality of its heterogeneity components (used, for example, in vascoda). The Shell model argument began with the “invisible web”, necessitating the restructuring of DL approaches. The conclusion is that both approaches fit well together and that the Shell model, with its semantic heterogeneity components, can be reformulated on the semantic web basis.Practical implicationsA reinterpretation of the DL approaches of semantic heterogeneity and adapting to standards and tools supported by the W3C should be the best solution. It is therefore recommended that – although most of the semantic web standards are not technologically refined for commercial applications at present – all individual DL developments should be checked for their adaptability to the W3C standards of the semantic web.Originality/valueA unique conceptual analysis of the parallel developments emanating from the digital library and semantic web communities.

Integrated access to cultural heritage resources through representation and alignment of controlled vocabularies

PurposeTo show how semantic web techniques can help address semantic interoperability issues in the broad cultural heritage domain, allowing users an integrated and seamless access to heterogeneous collections.Design/methodology/approachThis paper presents the heterogeneity problems to be solved. It introduces semantic web techniques that can help in solving them, focusing on the representation of controlled vocabularies and their semantic alignment. It gives pointers to some previous projects and experiments that have tried to address the problems discussed.FindingsSemantic web research provides practical technical and methodological approaches to tackle the different issues. Two contributions of interest are the simple knowledge organisation system model and automatic vocabulary alignment methods and tools. These contributions were demonstrated to be usable for enabling semantic search and navigation across collections.Research limitations/implicationsThe research aims at designing different representation and alignment methods for solving interoperability problems in the context of controlled subject vocabularies. Given the variety and technical richness of current research in the semantic web field, it is impossible to provide an in‐depth account or an exhaustive list of references. Every aspect of the paper is, however, given one or several pointers for further reading.Originality/valueThis article provides a general and practical introduction to relevant semantic web techniques. It is of specific value for the practitioners in the cultural heritage and digital library domains who are interested in applying these methods in practice.

The bio-zen plus ontology

Bio-zen plus is an OWL DL ontology for the domain of biomedical research. It incorporates several existing Semantic Web ontologies: the DOLCE foundational ontology, the Simple Knowledge Organisation System (SKOS), the Semantically Interlinked Online Communities ontology (SIOC), FOAF ontology, the Dublin Core metadata schema and the Creative Commons Metadata schema. The contents of many biomedical taxonomies and ontologies are available as extension packages. Bio-zen plus is the first ontology in the domain of life sciences that is optimized for practical use on the Semantic Web and makes extensive use of existing Semantic Web ontologies.

Extending the simple knowledge organization system for concept management in vocabulary development applications

AbstractIn this article, we describe the development of an extension to the Simple Knowledge Organization System (SKOS) to accommodate the needs of vocabulary development applications (VDA) managing metadata schemes and requiring close tracking of change to both those schemes and their member concepts. We take a neopragmatic epistemic stance in asserting the need for an entity in SKOS modeling to mediate between the abstract concept and the concrete scheme. While the SKOS model sufficiently describes entities for modeling the current state of a scheme in support of indexing and search on the Semantic Web, it lacks the expressive power to serve the needs of VDA needing to maintain scheme historical continuity. We demonstrate preliminarily that conceptualizations drawn from empirical work in modeling entities in the bibliographic universe, such as works, texts, and exemplars, can provide the basis for SKOS extension in ways that support more rigorous demands of capturing concept evolution in VDA.

Versioning concept schemes for persistent retrieval

L'A. propose d'etendre le Simple Knowledge Organization System (SKOS) Core Guide (Guide des Systemes Simples d'Organisation des Connaissances) en lui adjoignant un mecanisme pour suivre les changements que connaissent les arrangements conceptuels tels que thesaurus ou plans de classification. Ce mecanisme d'ontogenie du vocabulaire permettrait d'ameliorer la recherche d'information et de prevenir la perte de documents, grâce a un systeme de recherche persistente parmi les differentes versions d'un meme plan conceptuel.

ThManager: An Open Source Tool for Creating and Visualizing SKOS

Knowledge organization systems denotes formally represented knowledge that is used within the context of digital libraries to improve data sharing and information retrieval. To increase their use, and to reuse them when possible, it is vital to manage them adequately and to provide them in a standard interchange format. Simple knowledge organization systems (SKOS) seem to be the most promising representation for the type of knowledge models used in digital libraries, but there is a lack of tools that are able to properly manage it. This work presents a tool that fills this gap, facilitating their use in different environments and using SKOS as an interchange format.

Analysis of equivalence mapping for terminology services

This paper assesses the range of equivalence or mapping types required to facilitate interoperability in the context of a distributed terminology server. A detailed set of mapping types were examined, with a view to determining their validity for characterizing relationships between mappings from selected terminologies (AAT, LCSH, MeSH, and UNESCO) to the Dewey Decimal Classification (DDC) scheme. It was hypothesized that the detailed set of 19 match types proposed by Chaplan in 1995 is unnecessary in this context and that they could be reduced to a less detailed conceptually-based set. Results from an extensive mapping exercise support the main hypothesis and a generic suite of match types are proposed, although doubt remains over the current adequacy of the developing Simple Knowledge Organization System (SKOS) Core Mapping Vocabulary Specification (MVS) for inter-terminology mapping.

The Transformation from Thesaurus to Ontology Based on SKOS

The Transformation from Thesaurus to Ontology Based on SKOS

SKOS: Simple Knowledge Organisation for the Web

SUMMARY This article introduces the Simple Knowledge Organisation System (SKOS), a Semantic Web language for representing controlled structured vocabularies, including thesauri, classification schemes, subject heading systems, and taxonomies. SKOS provides a framework for publishing thesauri, classification schemes, and subject indexes on the Web, and for applying these systems to resource collections that are part of the Semantic Web. Semantic Web applications may harvest and merge SKOS data, to integrate and enhance retrieval service across multiple collections (e.g., libraries). This article also describes some alternatives for integrating Semantic Web services based on the Resource Description Framework (RDF) and SKOS into a distributed enterprise architecture.

Making use of upper ontologies to foster interoperability between SKOS concept schemes

PurposeThe purpose of this research is to introduce a mapping of the Simple Knowledge Organization Systems (SKOS) Core metadata to an ontology‐based model, whose main aim is to foster the semantic interoperability of different concept schemes.Design/methodology/approachResearch objectives have been achieved through the introduction of a common ground for the definition of concepts, based on shared definitions included in widely used upper ontologies. This effort makes use of a particular upper ontology: OpenCyc, the open source version of Cyc, which is currently one of the most complete general knowledge bases.FindingsAn in‐depth study of the SKOS vocabulary has suggested its extension, with the aim of correcting the shortcomings related with SKOS schemes semantic interoperability. However, although such an extension would help avoid ambiguities and enable inter‐thesaurus interoperability, the paper is focused on using a non‐invasive contribution. Non‐invasive in that the SKOS Core should not be modified as a result of this activity, but also, non‐invasive in that current SKOS schemes would not require modifications.Originality/valueThe use of formal representations to provide the SKOS terms with computational semantics, as well as the introduction of an intermediate ontology‐based model built on the SKOS information. Although both proposals stand on one upper ontology (OpenCyc), they could be easily adapted to others, which provides an added value to this research work.

Ontology mappings to improve learning resource search

AbstractThis paper proposes an ontology mapping‐based framewrowrk that allows searching for learning resources using multiple ontologies. The present applications of ontologies in e‐learning use various ontologies (eg, domain, curriculum, context), but they do not give a solution on how to interoperate e‐learning systems based on different ontologies. The proposed solution uses a mapping ontology that is a part of a recent Semantic Web initiative, the Simple Knowledge Organisation System. On top of that, we develop and implement two search algorithms. Finally, we evaluated the solution by developing a system that helps students search for relevant learning resource using a local context (ie, course curriculum) ontology.