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This paper aims to provide a context for Brazilian Portuguese language documentation and its data collection to establish linguistic repositories from a sociolinguistic overview.

The main sociolinguistic projects that have generated collections of Brazilian Portuguese language data are presented.

The comparison with another situation of repositories (seed vaults) and with the accounting concept of assets is evocated to map the challenges to be overcome in proposing a standardized and professional language repository to host the collections of linguistic data arising from the reported projects and others, in the accordance with the principles of the open science movement.

Thinking about the sustainability of projects to build linguistic documentation repositories, partnerships with the information technology area, or even with private companies, could minimize problems of obsolescence and safeguarding of data, by promoting the circulation and automation of analysis through natural language processing algorithms. These planning actions may help to promote the longevity of the linguistic documentation repositories of Brazilian sociolinguistic research.

The purpose of this paper is to provide a literature review of the principal formats and frameworks that have been used in the last 20 years to exchange linguistic resources. It aims to give special attention to the most recent approaches to publishing linguistic linked open data on the Web.

Research papers published since 1990 on the use of various formats, standards, frameworks and methods to exchange linguistic information were divided into two main categories: those proposing specific schemas and syntaxes to suit the requirements of a given type of linguistic data (these are referred to as offline approaches), and those adopting the linked data (LD) initiative and the semantic web technologies to support the interoperability of heterogeneous linguistic resources. For each paper, the type of linguistic resource exchanged, the framework/format used, the interoperability approach taken and the related projects were identified.

The information gathered in the survey reflects an increase in recent years in approaches adopting the LD initiative. This is due to the fact that the structural and syntactic issues which arise when addressing the interoperability of linguistic resources can be solved by applying semantic web technologies. What remains an open issue in the field of computational linguistics is the development of knowledge artefacts and mechanisms to support the alignment of the different aspects of linguistic resources in order to guarantee semantic and conceptual interoperability in the linked open data (LOD) cloud. Ontologies have proved to be of great use in achieving this goal.

The research presented here is by no means a comprehensive or all‐inclusive survey of all existing approaches to the exchange of linguistic resources. Rather, the aim was to highlight, analyze and categorize the most significant advances in the field.

This survey has practical implications for computational linguists and for every application requiring new developments in natural language processing. In addition, multilingual issues can be better addressed when semantic interoperability of heterogeneous linguistic resources is achieved.

The paper provides a survey of past and present research and developments addressing the interoperability of linguistic resources, including those where the linked data initiative has been adopted.

In this chapter, we explore uses of corpus linguistics within higher education research. Corpus linguistic approaches enable examination of large bodies of language data based on computing power. These bodies of data, or corpora, facilitate investigation of the meaning of words in context. The semiautomated nature of such investigation helps researchers to identify and interpret language patterns that might otherwise be inaccessible through manual analysis. We illustrate potential uses of corpus linguistic approaches through four short case studies by higher education researchers, spanning educational contexts, disciplines and genres. These case studies are underpinned by discussion of the development of corpus linguistics as a field of investigation, including existing open corpora and corpus analysis tools. We give a flavour of how corpus linguistic techniques, in isolation or as part of a wider research approach, can be particularly helpful to higher education researchers who wish to investigate language data and its context.

In this chapter, I offer a critique of linguistic field methodology, exploring the contribution that a participant-driven approach to data collection can make to language documentation and description. Bringing together material from linguistic field manuals, project documentation, hand-written field notes, and reflexive accounts of my field experiences, I trace my journey into the field, and through the process of collecting language data for the eventual production of a grammatical description. I establish that the basic field methodology advocated by linguists has traditionally involved tightly structured interviewing (known as “elicitation”). At the same time, I point to a literature in which this methodology is critiqued. While experienced fieldworkers no doubt employ multiple methodologies in the field, novice fieldworkers are encouraged to focus on their research goals. This can mean that elicitation sessions typically become the only way in which fieldwork is carried out.Drawing on my own experiences in the field, I demonstrate that linguistic fieldwork can combine ethnographic participation/observation methodology with community-driven text collection, and context-rich techniques of elicitation. This layered methodology prioritises people and social participation over the goals of academic research. It allows the research record to be shaped by the community, thus permitting the researcher to experience and seek understandings of the symbolic system of language from the perspective of the community. In my experience, such a methodology enhances the sustainability of the field project from both community and researcher perspectives. Crucially, it creates a context in which it is more likely that the linguist will be invited to return to the field and contribute in an ongoing way to a community, on their terms.

The purpose of this paper is to discuss the role of linguistic legacy materials within archives and databases. These data of past documentation projects are currently playing a minor role in the design of modern language archives. This is due to various challenges that legacy materials pose – ethical considerations, difficulties with formats, unclear or deficient metadata. Tackling these challenges can highlight general issues in language documentation and the use of language data. These insights can be used to inform the design of tools and infrastructures for data in this field, both recent and legacy materials.

This paper is conceptual and theorises digital language archives through their oldest deposits. It is informed by the author’s experiences in working with linguistic legacy materials of the South Estonian Kraasna dialect. The discussion makes references to relevant discourses in linguistics, archiving and computer science, encouraging transdisciplinary efforts in the design of language archives.

A digital archive created around linguistic legacy materials has the potential to respond to challenges posed by current data.

This paper discusses digital language archives from the perspective of documentary linguistics. It introduces the challenges and necessary steps in curating legacy materials. Several suggestions for the design of digital archives arise from this discussion. These ideas can inspire creators of digital language archives and provide a view from researchers using legacy materials.

The purpose of this paper is to demonstrate the possibility for the galleries, libraries, archives and museums sector to employ playful, immersive discovery interfaces for their collections and raise awareness of some of the considerations that go into the decision to use such technology and the creation of the interfaces.

This is a case study approach using the methodology of research through design. The paper introduces two examples of immersive interfaces to archival data created by the authors, using these as a springboard for discussing the different kinds of embodied experiences that users have with different kinds of immersion, for example, the exploration of the archive on a flat screen, a data “cave” or arena, or virtual reality.

The role of such interfaces in communicating with the audience of an archive is considered, for example, in allowing users to detect structure in data, particularly in understanding the role of geographic or other spatial elements in a collection, and in shifting the locus of knowledge production from individual to community. It is argued that these different experiences draw on different metaphors in terms of users’ prior experience with more well-known technologies, for example, “a performance” vs “a tool” vs “a background to a conversation”.

The two example interfaces discussed here are original creations by the authors of this paper. They are the first uses of mixed reality for interfacing with the archives in question. One is the first mixed reality interface to an audio archive. The discussion has implications for the future of interfaces to galleries, archives, libraries and museums more generally.

This report discusses the various types of linguistic information readily obtainable from online databases which are generally used for acquisition of technical information. There are illustrated examples of equivalent words, sample sentences and statistical linguistic data. The implications of online databases as substitutes for dictionaries, and as corpora for linguistic survey are discussed. Online databases include a vast amount of linguistic information, which is unabridged and continually updated, providing useful criteria for selection of words and expressions, and quantitative data for linguistic study.

This study evaluates the effect of the media image content of business to business (B2B) organizations to accelerate social media engagement. It highlights the importance of strategically designing image content for business marketing strategies.

This study designed a computation extensive research model based upon the stimulus-organism-response (SOR) theory using 39,139 Facebook posts of 125 organizations selected from Fortune 500 firms. Attributes from images and text were estimated using deep learning models. Subsequently, inferential analysis was established with ordinary least squares regression. Further machine learning algorithms, like support vector regression, k-nearest neighbour, decision tree and random forest, are used to analyze the significance and robustness of the proposed model for predicting engagement metrics.

The results indicate that the social media (SM) image content of B2B firms significantly impacts their social media engagement. The visual and linguistic attributes are extracted from the image using deep learning. The distinctive effect of each feature on social media engagement (SME) is empirically verified in this study.

This research presents practical insights formulated by embedding marketing, advertising, image processing and statistical knowledge of SM analytics. The findings of this study provide evidence for the stimulating effect of image content concerning SME. Based on the theoretical implications of this study, marketing and media content practitioners can enhance the efficacy of SM posts in engaging users.

The purpose of this paper is to propose a comprehensive framework for measuring the performance of an enterprise resource planning (ERP) system to survey suitable performance indicators (PIs) according to knowledge of the ERP implementation objectives set up at the implementation phase and build consistent measurement standards for facilitating the complex ERP performance evaluation process.

A seven‐step ERP performance measurement framework based on the objectives of ERP implementation is proposed. A fuzzy ERP performance index is used to account for the ambiguities involved in evaluating the performance of the ERP system. The fuzzy ERP performance index can be translated first into simple scores and then back to linguistic terms. An actual example in Taiwan demonstrates the feasibility of applying the proposed framework.

The findings indicate that the PIs of ERP performance measurement should align with the objectives of ERP implementation. The assessment results can represent the achievement of these objectives and the directions for improving the adopted ERP system.

This study may be interesting to some academic researchers and practical managers. The proposed framework can provide a procedure to link the objectives identified in the ERP system implementation phase and the performance considerations in the ERP use phase.

This study investigates how game design, which divides players into static teams, can reinforce group polarisation. The authors study this phenomenon from the perspective of social identity in the context of team-based location-based games, with a focus on game slang.

The authors performed an exploratory data analysis on an original dataset of n = 242,852 messages from five communication channels to find differences in game slang adoption between three teams in the location-based augmented reality game Pokémon GO. A divisive word “jym” (i.e. a Finnish slang derivative of the word “gym”) was discovered, and players' attitudes towards the word were further probed with a survey (n = 185). Finally, selected participants (n = 25) were interviewed in person to discover any underlying reasons for the observed polarised attitudes.

The players' teams were correlated with attitudes towards “jym”. Face-to-face interviews revealed association of the word to a particular player subgroup and it being used with improper grammar as reasons for the observed negative attitudes. Conflict over (virtual) territorial resources reinforced the polarisation.

Game design with static teams and inter-team conflict influences players' social and linguistic identity, which subsequently may result in divisive stratification among otherwise cooperative or friendly player-base.

The presented multi-method study connecting linguistic and social stratification is a novel approach to gaining insight on human social interactions, polarisation and group behaviour in the context of location-based games.