Protocols for Scholarly Communication

CERN, the European Organization for Nuclear Research, has operated an institutional preprint repository for more than 10 years. The repository contains over 850,000 records of which more than 450,000 are full-text OA preprints, mostly in the field of particle physics, and it is integrated with the library's holdings of books, conference proceedings, journals and other grey literature. In order to encourage effective propagation and open access to scholarly material, CERN is implementing a range of innovative library services into its document repository: automatic keywording, reference extraction, collaborative management tools and bibliometric tools. Some of these services, such as user reviewing and automatic metadata extraction, could make up an interesting testbed for future publishing solutions and certainly provide an exciting environment for e-science possibilities. The future protocol for scientific communication should naturally guide authors towards OA publication and CERN wants to help reach a full open access publishing environment for the particle physics community and the related sciences in the next few years.Comment: 8 pages, to appear in Library and Information Systems in Astronomy

Semantic Technologies for Manuscript Descriptions — Concepts and Visions

The contribution at hand relates recent developments in the area of the World Wide Web to codicological research. In the last number of years, an informational extension of the internet has been discussed and extensively researched: the Semantic Web. It has already been applied in many areas, including digital information processing of cultural heritage data. The Semantic Web facilitates the organisation and linking of data across websites, according to a given semantic structure. Software can then process this structural and semantic information to extract further knowledge. In the area of codicological research, many institutions are making efforts to improve the online availability of handwritten codices. If these resources could also employ Semantic Web techniques, considerable research potential could be unleashed. However, data acquisition from less structured data sources will be problematic. In particular, data stemming from unstructured sources needs to be made accessible to SemanticWeb tools through information extraction techniques. In the area of museum research, the CIDOC Conceptual Reference Model (CRM) has been widely examined and is being adopted successfully. The CRM translates well to Semantic Web research, and its concentration on contextualization of objects could support approaches in codicological research. Further concepts for the creation and management of bibliographic coherences and structured vocabularies related to the CRM will be considered in this chapter. Finally, a user scenario showing all processing steps in their context will be elaborated on

Automating Metadata Extraction: Genre Classification

A problem that frequently arises in the management and integration of scientific data is the lack of context and semantics that would link data encoded in disparate ways. To bridge the discrepancy, it often helps to mine scientific texts to aid the understanding of the database. Mining relevant text can be significantly aided by the availability of descriptive and semantic metadata. The Digital Curation Centre (DCC) has undertaken research to automate the extraction of metadata from documents in PDF([22]). Documents may include scientific journal papers, lab notes or even emails. We suggest genre classification as a first step toward automating metadata extraction. The classification method will be built on looking at the documents from five directions; as an object of specific visual format, a layout of strings with characteristic grammar, an object with stylo-metric signatures, an object with meaning and purpose, and an object linked to previously classified objects and external sources. Some results of experiments in relation to the first two directions are described here; they are meant to be indicative of the promise underlying this multi-faceted approach.

Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review

Since the Simple Knowledge Organization System (SKOS) specification and its SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a significant number of conventional knowledge organization systems (KOS) (including thesauri, classification schemes, name authorities, and lists of codes and terms, produced before the arrival of the ontology-wave) have made their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS" as an umbrella term to refer to all of the value vocabularies and lightweight ontologies within the Semantic Web framework. The paper provides an overview of what the LOD KOS movement has brought to various communities and users. These are not limited to the colonies of the value vocabulary constructors and providers, nor the catalogers and indexers who have a long history of applying the vocabularies to their products. The LOD dataset producers and LOD service providers, the information architects and interface designers, and researchers in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper examines a set of the collected cases (experimental or in real applications) and aims to find the usages of LOD KOS in order to share the practices and ideas among communities and users. Through the viewpoints of a number of different user groups, the functions of LOD KOS are examined from multiple dimensions. This paper focuses on the LOD dataset producers, vocabulary producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on Digital Librarie

Template Mining for Information Extraction from Digital Documents

published or submitted for publicatio

Event-based Access to Historical Italian War Memoirs

The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events which have happened in the past; among these, memoirs are a very common type of primary source. In this paper, we present an approach for extracting information from Italian historical war memoirs and turning it into structured knowledge. This is based on the semantic notions of events, participants and roles. We evaluate quantitatively each of the key-steps of our approach and provide a graph-based representation of the extracted knowledge, which allows to move between a Close and a Distant Reading of the collection.Comment: 23 pages, 6 figure

Applying digital content management to support localisation

The retrieval and presentation of digital content such as that on the World Wide Web (WWW) is a substantial area of research. While recent years have seen huge expansion in the size of web-based archives that can be searched efficiently by commercial search engines, the presentation of potentially relevant content is still limited to ranked document lists represented by simple text snippets or image keyframe surrogates. There is expanding interest in techniques to personalise the presentation of content to improve the richness and effectiveness of the user experience. One of the most significant challenges to achieving this is the increasingly multilingual nature of this data, and the need to provide suitably localised responses to users based on this content. The Digital Content Management (DCM) track of the Centre for Next Generation Localisation (CNGL) is seeking to develop technologies to support advanced personalised access and presentation of information by combining elements from the existing research areas of Adaptive Hypermedia and Information Retrieval. The combination of these technologies is intended to produce significant improvements in the way users access information. We review key features of these technologies and introduce early ideas for how these technologies can support localisation and localised content before concluding with some impressions of future directions in DCM