Linked data authority records for Irish place names

Linked Data technologies are increasingly being implemented to enhance cataloguing workflows in libraries, archives and museums. We review current best practice in library cataloguing, how Linked Data is used to link collections and provide consistency in indexing, and briefly describe the relationship between Linked Data, library data models and descriptive standards. As an example we look at the Logainm.ie dataset, an online database holding the authoritative hierarchical list of Irish and English language place names in Ireland. This paper describes the process of creating the new Linked Logainm dataset, including the transformation of the data from XML to RDF and the generation of links to external geographic datasets like DBpedia and the Faceted Application of Subject Terminology. This dataset was then used to enhance the National Library of Ireland's metadata MARCXML metadata records for its Longfield maps collection. We also describe the potential benefits of Linked Data for libraries, focusing on the use of the Linked Logainm dataset and its future potential for Irish heritage institutions

Linked Logainm: enhancing library metadata using linked data of Irish place names

Linked Logainm is the newly created Linked Data version of Logainm.ie, an online database holding the authoritative hierarchical list of Irish and English language place names in Ireland. As a use case to demonstrate the benefit of Linked Data to the library community, the Linked Logainm dataset was used to enhance the Longfield Map collection, a set of digitised 18th–19th century maps held by the National Library of Ireland. This paper describes the process of creating Linked Logainm, including the transformation of the data from XML to RDF, the generation of links to external geographic datasets like DBpedia and the Faceted Application of Subject Terminology, and the enhancement of the Library’s metadata records

New Media, Free Expression, and the Offences Against the State Acts

New media facilitates communication and creates a common, lived experience. It also carries the potential for great harm on an individual and societal scale. Posting integrates information and emotion, with study after study finding that fear and anger transfer most readily online. Isolation follows, with insular groups forming. The result is an increasing bifurcation of society. Scholars also write about rising levels of depression and suicide that stem from online dependence and replacing analogical experience with digital interaction, as well as escalating levels of anxiety that are rooted in the validation expectation of the ‘like’ function. These changes generate instability and contribute to a volatile social environment. Significant political risks also accompany this novel genre. Hostile actors can use social media platforms to deepen political schisms, to promote certain candidates, and, as demonstrated by the recent Cambridge Analytica debacle, to swing elections. Extremist groups and terrorist organisations can use online interactions to build sympathetic audiences and to recruit adherents. Since 1939, the Offences Against the State Act (OAS) has served as the primary vehicle for confronting political violence and challenges to state authority. How effective is it in light of new media? The challenges are legion. Terrorist recruitment is just the tip of the iceberg. Social networking sites allow for targeted and global fundraising, international direction and control, anonymous power structures, and access to expertise. These platforms create spaces within which extreme ideologies can prosper, targeting individuals likely to be sympathetic to the cause, 24 hours a day, seven days a week, ad infinitum. They offer an alternative reality, subject to factual manipulation and direction—a problem exacerbated by the risk of so-called deep fakes: autonomously-generated content that makes it appear that people acted, or that certain circumstances occurred, which never did. In November 2019 the Irish Government adopted a new regulation targeting social media. The measure focuses on political advertising and to ensure that voters have access to accurate information. It does not address the myriad further risks. This chapter, accordingly, focuses on ways in which the Offences Against the State Act (OAS) and related laws have historically treated free expression as a prelude to understanding how and whether the existing provisions are adequate for challenges from new media

Interaction Data Sets In The UK: An Audit

Interaction or flow data involves counts of flows between origin and destination areas and can be extracted from a range of sources. The Centre for Interaction Data Estimation and Research (CIDER) maintains a web-based system (WICID) that allows academic researchers to access and extract migration and commuting flow data (the so-called Origin-Destination Statistics) from the last three censuses. However, there are many other sources of interaction data other than the decadal census, including national administrative or registration procedures and large scale social surveys. This paper contains an audit of interaction data sets in the UK, providing detailed description and exemplification in each case and outlining the advantages and shortcomings of the different types of data where appropriate. The Census Origin-Destination Statistics have been described elsewhere in detail and only a short synopsis is provided here together with review of the interaction data that can be derived from other census products. The primary aims of the audit are to identify those interaction data sets that exist that might complement the census origin-destination statistics currently contained in WICID and to assess their suitability and availability as potential data sets to be held in an expanded version of WICID. Tables or flow data sets are included for exemplification. The paper concludes with a series of recommendations as to which of these data sets should be incorporated into a new information system for interaction flows that complement the census data and also provide opportunities for new research projects

Mind the gap: National and local partnership in the Irish public sector

This article uses case study data from a major Irish city council to investigate and explain public sector worker attitudes towards social partnership at local and national level. It is argued that the more sceptical attitudes to workplace partnership reflect structural differences between local and national arrangements, which have enabled public sector employers to use ‘social partnership’ as a constraint in the implementation process of a pre-determined public sector reform agenda

Institute of Historical Research Newsletter, Spring Term 2006

The IHR produces a termly newsletter, which gives details of seminars and conferences and other historical news. This is the newsletter for the spring term 2006

The cultural, ethnic and linguistic classification of populations and neighbourhoods using personal names

There are growing needs to understand the nature and detailed composition of ethnicgroups in today?s increasingly multicultural societies. Ethnicity classifications areoften hotly contested, but still greater problems arise from the quality and availabilityof classifications, with knock on consequences for our ability meaningfully tosubdivide populations. Name analysis and classification has been proposed as oneefficient method of achieving such subdivisions in the absence of ethnicity data, andmay be especially pertinent to public health and demographic applications. However,previous approaches to name analysis have been designed to identify one or a smallnumber of ethnic minorities, and not complete populations.This working paper presents a new methodology to classify the UK population andneighbourhoods into groups of common origin using surnames and forenames. Itproposes a new ontology of ethnicity that combines some of its multidimensionalfacets; language, religion, geographical region, and culture. It uses data collected atvery fine temporal and spatial scales, and made available, subject to safeguards, at thelevel of the individual. Such individuals are classified into 185 independentlyassigned categories of Cultural Ethnic and Linguistic (CEL) groups, based on theprobable origins of names. We include a justification for the need of classifyingethnicity, a proposed CEL taxonomy, a description of how the CEL classification wasbuilt and applied, a preliminary external validation, and some examples of current andpotential applications

A review of name-based ethnicity classification methods and their potential in population studies

Several approaches have been proposed to classify populations into ethnic groups using people's names, as an alternative to ethnicity self-identification information when this is not available. These methodologies have been developed, primarily in the public health and population genetics literature in different countries, in isolation from and with little participation from demographers or social scientists. The objective of this paper is to bring together these isolated efforts and provide a coherent comparison, a common methodology and terminology in order to foster new research and applications in this promising and multidisciplinary field. A systematic review has been conducted of the most representative studies that develop new name-based ethnicity classifications, extracting methodological commonalities, achievements and shortcomings; 13 studies met the inclusion criteria and all followed a very similar methodology to create a name reference list with which to classify populations into a few most common ethnic groups. The different classifications' sensitivity varies between 0.67 and 0.95, their specificity between 0.80 and 1, their positive predicted value between 0.70 and 0.96, and their negative predicted value between 0.96 and 1. Name-based ethnicity classification systems have a great potential to overcome data scarcity issues in a wide variety of key topics in population studies, as is proved by the 13 papers analysed. Their current limitations are mainly due to a restricted number of names and a partial spatio-temporal coverage of the reference population data-sets used to produce name reference lists. Improved classifications with extensive population coverage and higher classification accuracy levels will be achieved by using population registers with wider spatio-temporal coverage. Furthermore, there is a requirement for such new classifications to include all of the potential ethnic groups present in a society, and not just one or a few of them. Copyright (c) 2007 John Wiley & Sons, Ltd