Статті в журналах з теми "Robust Minimal Recursion Semantic"

The article describes a pilot implementation of a grammar containing different types of locative PPs. In particular, we investigate the distinction between static and directional locatives, and between different types of directional locatives. Locatives may act as modifiers as well as referring expressions depending on the syntactic context. We handle this with a single lexical entry. The implementation is of Norwegian locatives, but English locatives are both discussed and compared to Norwegian locatives. The semantic analysis is based on a proposal by Markus Kracht (2002), and we show how this analysis can be incorporated into Minimal Recursion Semantics (MRS) (Copestake et al. 2005). We discuss how the resulting system may be applied in a transfer-based machine translation system, and how we can map from a shallow MRS representation to a deeper semantic representation.

The general problem of finding satisfying solutions to constraint-based underspecified representations of quantifier scope is NP-complete. Existing frameworks, including Dominance Graphs, Minimal Recursion Semantics, and Hole Semantics, have struggled to balance expressivity and tractability in order to cover real natural language sentences with efficient algorithms. We address this trade-off with a general principle of coherence, which requires that every variable introduced in the domain of discourse must contribute to the overall semantics of the sentence. We show that every underspecified representation meeting this criterion can be efficiently processed, and that our set of representations subsumes all previously identified tractable sets.

Languages differ qualitatively in their numeral systems. At one extreme, some languages have a small set of number terms, which denote approximate or inexact numerosities; at the other extreme, many languages have forms for exact numerosities over a very large range, through a recursively defined counting system. Why do numeral systems vary as they do? Here, we use computational analyses to explore the numeral systems of 30 languages that span this spectrum. We find that these numeral systems all reflect a functional need for efficient communication, mirroring existing arguments in other semantic domains such as color, kinship, and space. Our findings suggest that cross-language variation in numeral systems may be understood in terms of a shared functional need to communicate precisely while using minimal cognitive resources.

Abstract With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Processing (NLP) have started to exploit various semantic models. The semantic models have been created on the base of LSA, clustering, word embeddings, deep learning, neural networks, etc., and abstract logical forms, such as Minimal Recursion Semantics (MRS) or Abstract Meaning Representation (AMR), etc. Additionally, the Linguistic Linked Open Data Cloud has been initiated (LLOD Cloud) which interlinks linguistic data for improving the tasks of NLP. This cloud has been expanding enormously for the last four-five years. It includes corpora, lexicons, thesauri, knowledge bases of various kinds, organized around appropriate ontologies, such as LEMON. The semantic models behind the data organization as well as the representation of the semantic resources themselves are a challenge to the NLP community. The NLP applications that extensively rely on the above discussed models include Machine Translation, Information Extraction, Question Answering, Text Simplification, etc.

This paper presents a question generation system based on the approach of semantic rewriting. The state-of-the-art deep linguistic parsing and generation tools are employed to convert (back and forth) between the natural language sentences and their meaning representations in the form of Minimal Recursion Semantics (MRS). By carefully operating on the semantic structures, we show a principled way of generating questions without ad-hoc manipulation of the syntactic structures. Based on the (partial) understanding of the sentence meaning, the system generates questions which are semantically grounded and purposeful. And with the support of deep linguistic grammars, the grammaticality of the generation results is warranted. Further, with a specialized ranking model, the linguistic realizations from the general purpose generation model are further refined for our the question generation task. The evaluation results from QGSTEC2010 show promising prospects of the proposed approach.

Purpose This paper aims to respond to the high cost of facility management-enabled building information model (FM-BIM) creation and maintenance, a significant and under-researched barrier to adoption for existing buildings. The resultant approach focuses on only value-adding content (“Lean”) developed flexibly and iteratively in collaboration with end-users (“Agile”). Design/methodology/approach Five case studies were developed for university and hospital buildings in collaboration with end-users, guided by the process presented. These informed the refinement of a robust and flexible approach to increase BIM functionality with minimal geometry, focusing instead on the development of specific parameters to map semantic information necessary for each desired FM use. Findings The resulting BIM provided a breadth of model functionality with minimal modeling effort: 15 hours average implementation time per supported FM use. This low level of effort was achieved by limiting geometry to where it is necessary for the FM use implementation. Instead, the model incorporated the majority of geometry by reference and focused on semantic and topological parameters to house FM information. Research limitations/implications This study provides the basis for a new ontology structure focused on defining the rules for hosting asset management data (host entity, parameter type and characteristics) to reduce the reliance on complex geometric model development. Practical implications By prioritizing highly beneficial applications, early investment is minimized, providing quick returns at low risk, demonstrating the value of FM-BIM to end-users. Originality/value The Lean-Agile approach addresses the known research gap of low-effort, flexible approaches to FM-BIM model creation and maintenance and its effectiveness is analyzed through five case studies.

Special processes recruited during the recognition of personally familiar people have been assumed to reflect the rich episodic and semantic information that selectively represents each person. However, the processes may also include person nonselective ones, which may require interpretation in terms beyond the memory mechanism. To examine this possibility, we assessed decrease in differential activation during the second presentation of an identical face (repetition suppression) as an index of person selectivity. During fMRI, pictures of personally familiar, famous, and unfamiliar faces were presented to healthy subjects who performed a familiarity judgment. Each face was presented once in the first half of the experiment and again in the second half. The right inferior temporal and left inferior frontal gyri were activated during the recognition of both types of familiar faces initially, and this activation was suppressed with repetition. Among preferentially activated regions for personally familiar over famous faces, robust suppression in differential activation was exhibited in the bilateral medial and anterior temporal structures, left amygdala, and right posterior STS, all of which are known to process episodic and semantic information. On the other hand, suppression was minimal in the posterior cingulate, medial prefrontal, right inferior frontal, and intraparietal regions, some of which were implicated in social cognition and cognitive control. Thus, the recognition of personally familiar people is characterized not only by person-selective representation but also by nonselective processes requiring a research framework beyond the memory mechanism, such as a social adaptive response.

The ability to associate images with natural language sentences that describe what is depicted in them is a hallmark of image understanding, and a prerequisite for applications such as sentence-based image search. In analogy to image search, we propose to frame sentence-based image annotation as the task of ranking a given pool of captions. We introduce a new benchmark collection for sentence-based image description and search, consisting of 8,000 images that are each paired with five different captions which provide clear descriptions of the salient entities and events. We introduce a number of systems that perform quite well on this task, even though they are only based on features that can be obtained with minimal supervision. Our results clearly indicate the importance of training on multiple captions per image, and of capturing syntactic (word order-based) and semantic features of these captions. We also perform an in-depth comparison of human and automatic evaluation metrics for this task, and propose strategies for collecting human judgments cheaply and on a very large scale, allowing us to augment our collection with additional relevance judgments of which captions describe which image. Our analysis shows that metrics that consider the ranked list of results for each query image or sentence are significantly more robust than metrics that are based on a single response per query. Moreover, our study suggests that the evaluation of ranking-based image description systems may be fully automated.

We present a constraint-based syntax-semantics interface for the construction of RMRS (Robust Minimal Recursion Semantics) representations from shallow grammars. The architecture is designed to allow modular interfaces to existing shallow grammars of various depth - ranging from chunk grammars to context-free stochastic grammars. We define modular semantics construction principles in a typed feature structure formalism that allow flexible adaptation to alternative grammars and different languages.

This paper proposes an HPSG account of the French tense and aspect system, focussing on the analysis of the passé simple (simple past) and imparfait (imperfective) tenses and their interaction with aspectually sensitive adjuncts. Starting from de Swart's (1998) analysis of the semantics of tense and aspect, I show that while the proposed semantic representations are appropriate, the analysis of implicit aspectual operators as coercion operators is inadequate. The proposed HPSG analysis relies on Minimal Recursion Semantics to relate standard syntactic structures with de Swart-style semantic representations. The analysis has two crucial features: first, it assumes that the semantic contribution of tense originates in the verb's semantic representation, despite the fact that tense can get wide scope over other semantic elements. Second, it allows the occurrence of implicit aspectual operators to be controlled by the verb's inflectional class, which accounts for their peculiar distribution.

In this paper, I shall discuss the semantic attachment of intersective modifiers in German coherent constructions. I shall show that a purely syntactic solution to the observable attachment ambiguity is undesirable for reasons of processing e ciency and/or massive spurious ambiguity. Instead, I shall follow Egg and Lebeth (1995) and propose an extension to Minimal Recursion Semantics, permitting the expression of underspecified semantic attachment. This rather trivial move, as we shall see, will not only be preferable for processing reasons, but it will also be more in line with the spirit of underspecified semantics, e ectively providing a compact representation of purely semantic distinctions, instead of unfolding these distinctions into a rain forest of tree representations and derivations. I will present an implementation of the underspecification approach integrated into the German HPSG developed at DFKI and compare its e ciency to an alternative implementation where semantic attachment is unfolded by means of retrieval rules.

‎The glue approach to semantic interpretation has been developed principally for Lexical Functional Grammar. Recent work has shown how glue can be used with a variety of syntactic theories and this paper outlines how it can be applied to HPSG. As well as providing an alternative form of semantics for HPSG, we believe that the benefits of HPSG glue include the following: (1) simplification of the Semantics Principle; (2) a simple and elegant treatment of modifier scope, including empirical phenomena like quantifier scope ambiguity, the interaction of scope with raising, and recursive modification; (3) an analysis of control that handles agreement between controlled subjects and their coarguments while allowing for a property denotation for the controlled clause; (4) re-use of highly efficient techniques for semantic derivation already implemented for LFG, and which target problems of ambiguity management also addressed by Minimal Recursion Semantics.

In Modern Greek there is a rich aspectual system, which involves both morphologically expressed grammatical aspect and eventuality types, carried primarily by the meaning of the verbal predicate. Particular emphasis is paid to the interaction between grammatical aspect and eventuality types, since it is due to this interaction that the verbal predicate acquires distinct meanings. In order to explain potential changes in the meaning of the eventualities caused by the interaction with grammatical aspect, I propose a formal analysis within HPSG, using Minimal Recursion Semantics (MRS) for the semantic representations. Following the MRS architecture, I introduce a number of relations, which represent both grammatical aspect and eventuality types. The close interaction between grammatical aspect and eventuality types triggers special meanings which traditionally can be explained by inserting contextual information into the representations. In this paper, I argue against such an analysis, providing an alternative which is based on the introduction of subeventual templates formulated by Michaelis (2003) and Pustejovsky (1995). In this context, grammatical aspect combines with eventuality types and selects eventualities or subeventualities appropriate to its selection restrictions, using information that is already there in the denotation of the eventualities.

Educational Institutions are facing enormous tasks of marking and grading students at the end of every examination within the shortest possible time. Marking theoretical essay questions which involves thousands of examinees can be biased, subjective and time-consuming, leading to variation in grades awarded by different human assessors. This study presents an Essay Grading System called Intelligent Natural Language Processing Essay Grading System (iNLPEGS) with high accuracy percentage and minimal loss function for scoring assessment that can accommodate more robust questions. Secondary dataset collected from Kaggle provided by The Hewlett Foundation was used to aid semantic analysis and Part of Speech tagging. Assemblage of Computer Science questions and answers were collected from Babcock University Computer Science Department to create a more robust dataset to ensure high reliability. An Intelligent Natural Language Processing Essay Grading Model was designed based on Enhanced Latent Semantic Analysis using Part of Speech n-gram Inverse Document Frequency. Web based application was developed using Django, Gensim, Jupyter Notebook and Anaconda as the development tools due to availability of several Python libraries with SQLite as the database. Results of performance evaluation of iNLPEGS showed accuracy of 89.03% and error of 10.97% connoting that there is very little difference between scores from the developed intelligent essay grading system and a human grader. Also, the loss function from Root Mean Square Error (RSME) showed value of 0.620 which is very small and thus signifies closeness to the line of best fit from the regression equation.

Abstract Background A wide array of existing instruments are commonly used to assess childhood behavior and development for the evaluation of social, emotional and behavioral disorders such as Autism Spectrum Disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and anxiety. Many of these instruments either focus on one diagnostic category or encompass a broad set of childhood behaviors. We analyze a wide range of standardized behavioral instruments and identify a comprehensive, structured semantic hierarchical grouping of child behavioral observational features. We use the hierarchy to create Rosetta: a new set of behavioral assessment questions, designed to be minimal yet comprehensive in its coverage of clinically relevant behaviors. We maintain a full mapping from every functional feature in every covered instrument to a corresponding question in Rosetta. Results In all, 209 Rosetta questions are shown to cover all the behavioral concepts targeted in the eight existing standardized instruments. Conclusion The resulting hierarchy can be used to create more concise instruments across various ages and conditions, as well as create more robust overlapping datasets for both clinical and research use.

Abstract Transformer-based language models have taken many fields in NLP by storm. BERT and its derivatives dominate most of the existing evaluation benchmarks, including those for Word Sense Disambiguation (WSD), thanks to their ability in capturing context-sensitive semantic nuances. However, there is still little knowledge about their capabilities and potential limitations in encoding and recovering word senses. In this article, we provide an in-depth quantitative and qualitative analysis of the celebrated BERT model with respect to lexical ambiguity. One of the main conclusions of our analysis is that BERT can accurately capture high-level sense distinctions, even when a limited number of examples is available for each word sense. Our analysis also reveals that in some cases language models come close to solving coarse-grained noun disambiguation under ideal conditions in terms of availability of training data and computing resources. However, this scenario rarely occurs in real-world settings and, hence, many practical challenges remain even in the coarse-grained setting.We also perform an in-depth comparison of the two main language model based WSD strategies, namely, fine-tuning and feature extraction, finding that the latter approach is more robust with respect to sense bias and it can better exploit limited available training data. In fact, the simple feature extraction strategy of averaging contextualized embeddings proves robust even using only three training sentences per word sense, with minimal improvements obtained by increasing the size of this training data.

Abstract Background With recent advances in microscopy, recordings of cell behaviour can result in terabyte-size datasets. The lattice light sheet microscope (LLSM) images cells at high speed and high 3D resolution, accumulating data at 100 frames/second over hours, presenting a major challenge for interrogating these datasets. The surfaces of vertebrate cells can rapidly deform to create projections that interact with the microenvironment. Such surface projections include spike-like filopodia and wave-like ruffles on the surface of macrophages as they engage in immune surveillance. LLSM imaging has provided new insights into the complex surface behaviours of immune cells, including revealing new types of ruffles. However, full use of these data requires systematic and quantitative analysis of thousands of projections over hundreds of time steps, and an effective system for analysis of individual structures at this scale requires efficient and robust methods with minimal user intervention. Results We present LLAMA, a platform to enable systematic analysis of terabyte-scale 4D microscopy datasets. We use a machine learning method for semantic segmentation, followed by a robust and configurable object separation and tracking algorithm, generating detailed object level statistics. Our system is designed to run on high-performance computing to achieve high throughput, with outputs suitable for visualisation and statistical analysis. Advanced visualisation is a key element of LLAMA: we provide a specialised tool which supports interactive quality control, optimisation, and output visualisation processes to complement the processing pipeline. LLAMA is demonstrated in an analysis of macrophage surface projections, in which it is used to i) discriminate ruffles induced by lipopolysaccharide (LPS) and macrophage colony stimulating factor (CSF-1) and ii) determine the autonomy of ruffle morphologies. Conclusions LLAMA provides an effective open source tool for running a cell microscopy analysis pipeline based on semantic segmentation, object analysis and tracking. Detailed numerical and visual outputs enable effective statistical analysis, identifying distinct patterns of increased activity under the two interventions considered in our example analysis. Our system provides the capacity to screen large datasets for specific structural configurations. LLAMA identified distinct features of LPS and CSF-1 induced ruffles and it identified a continuity of behaviour between tent pole ruffling, wave-like ruffling and filopodia deployment.

Abstract Background Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, published algorithms mostly solve only one specific problem and they typically require a considerable coding effort and machine learning background for their application. Results We have thus developed InstantDL, a deep learning pipeline for four common image processing tasks: semantic segmentation, instance segmentation, pixel-wise regression and classification. InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort. To make the pipeline robust, we have automated and standardized workflows and extensively tested it in different scenarios. Moreover, it allows assessing the uncertainty of predictions. We have benchmarked InstantDL on seven publicly available datasets achieving competitive performance without any parameter tuning. For customization of the pipeline to specific tasks, all code is easily accessible and well documented. Conclusions With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.

Brain reorganization patterns associated with language recovery after stroke have long been debated. Studying mechanisms of spontaneous and treatment-induced language recovery in post-stroke aphasia requires a network-based approach given the potential for recruitment of perilesional left hemisphere language regions, homologous right hemisphere language regions, and/or spared bilateral domain-general regions. Recent hardware, software, and methodological advances in functional near-infrared spectroscopy (fNIRS) make it well-suited to examine this question. fNIRS is cost-effective with minimal contraindications, making it a robust option to monitor treatment-related brain activation changes over time. Establishing clear activation patterns in neurotypical adults during language and domain-general cognitive processes via fNIRS is an important first step. Some fNIRS studies have investigated key language processes in healthy adults, yet findings are challenging to interpret in the context of methodological limitations. This pilot study used fNIRS to capture brain activation during language and domain-general processing in neurotypicals and individuals with aphasia. These findings will serve as a reference when interpreting treatment-related changes in brain activation patterns in post-stroke aphasia in the future. Twenty-four young healthy controls, seventeen older healthy controls, and six individuals with left hemisphere stroke-induced aphasia completed two language tasks (i.e., semantic feature, picture naming) and one domain-general cognitive task (i.e., arithmetic) twice during fNIRS. The probe covered bilateral frontal, parietal, and temporal lobes and included short-separation detectors for scalp signal nuisance regression. Younger and older healthy controls activated core language regions during semantic feature processing (e.g., left inferior frontal gyrus pars opercularis) and lexical retrieval (e.g., left inferior frontal gyrus pars triangularis) and domain-general regions (e.g., bilateral middle frontal gyri) during hard versus easy arithmetic as expected. Consistent with theories of post-stroke language recovery, individuals with aphasia activated areas outside the traditional networks: left superior frontal gyrus and left supramarginal gyrus during semantic feature judgment; left superior frontal gyrus and right precentral gyrus during picture naming; and left inferior frontal gyrus pars opercularis during arithmetic processing. The preliminary findings in the stroke group highlight the utility of using fNIRS to study language and domain-general processing in aphasia.

Abstract Swedish makes use of tonal accents (Accents 1 and 2) to contrast words, but the functional load is very low, with some regional dialects not even exhibiting the contrast. In particular given the low number of minimal pairs, the question is whether tonal word accent is used in lexical access. Here we present two cross-modal fragment semantic priming studies in order to address this question. Both experiments use first syllable fragments in order to prime semantically related targets. Experiment 1 utilises words whose first syllable occurs with both accent patterns, creating a situation in which there is lexical competition between words that differ solely in terms of accent. Experiment 2 removes this competition by using words that have no such accent competitors. Our results show that native speakers of Swedish use tonal word accent in lexical access: Accent mispronunciations failed to prime semantically related targets, regardless of whether primes had accent competitors or not. Results for a group of early bilingual speakers (who grew up with one Swedish-speaking parent and one other non-tonal language) showed no differences in processing compared to the monolinguals. This indicates that the extraction of accent features during acquisition and their use in lexical access is robust, even in a scenario where multiple input languages lead to tonal word accent being a useful feature for only some of the lexical items that are being acquired. There is no doubt that the accent system is well entrenched into the bilinguals’ phonological system.

DiSSCo, the Distributed System of Scientific Collections, is a pan-European Research Infrastructure (RI) mobilising, unifying bio- and geo-diversity information connected to the specimens held in natural science collections and delivering it to scientific communities and beyond. Bringing together 120 institutions across 21 countries and combining earlier investments in data interoperability practices with technological advancements in digitisation, cloud services and semantic linking, DiSSCo makes the data from natural science collections available as one virtual data cloud, connected with data emerging from new techniques and not already linked to specimens. These new data include DNA barcodes, whole genome sequences, proteomics and metabolomics data, chemical data, trait data, and imaging data (Computer-assisted Tomography (CT), Synchrotron, etc.), to name but a few; and will lead to a wide range of end-user services that begins with finding, accessing, using and improving data. DiSSCo will deliver the diagnostic information required for novel approaches and new services that will transform the landscape of what is possible in ways that are hard to imagine today. With approximately 1.5 billion objects to be digitised, bringing natural science collections to the information age is expected to result in many tens of petabytes of new data over the next decades, used on average by 5,000 – 15,000 unique users every day. This requires new skills, clear policies and robust procedures and new technologies to create, work with and manage large digital datasets over their entire research data lifecycle, including their long-term storage and preservation and open access. Such processes and procedures must match and be derived from the latest thinking in open science and data management, realising the core principles of 'findable, accessible, interoperable and reusable' (FAIR). Synthesised from results of the ICEDIG project ("Innovation and Consolidation for Large Scale Digitisation of Natural Heritage", EU Horizon 2020 grant agreement No. 777483) the DiSSCo Conceptual Design Blueprint covers the organisational arrangements, processes and practices, the architecture, tools and technologies, culture, skills and capacity building and governance and business model proposals for constructing the digitisation infrastructure of DiSSCo. In this context, the digitisation infrastructure of DiSSCo must be interpreted as that infrastructure (machinery, processing, procedures, personnel, organisation) offering Europe-wide capabilities for mass digitisation and digitisation-on-demand, and for the subsequent management (i.e., curation, publication, processing) and use of the resulting data. The blueprint constitutes the essential background needed to continue work to raise the overall maturity of the DiSSCo Programme across multiple dimensions (organisational, technical, scientific, data, financial) to achieve readiness to begin construction. Today, collection digitisation efforts have reached most collection-holding institutions across Europe. Much of the leadership and many of the people involved in digitisation and working with digital collections wish to take steps forward and expand the efforts to benefit further from the already noticeable positive effects. The collective results of examining technical, financial, policy and governance aspects show the way forward to operating a large distributed initiative i.e., the Distributed System of Scientific Collections (DiSSCo) for natural science collections across Europe. Ample examples, opportunities and need for innovation and consolidation for large scale digitisation of natural heritage have been described. The blueprint makes one hundred and four (104) recommendations to be considered by other elements of the DiSSCo Programme of linked projects (i.e., SYNTHESYS+, COST MOBILISE, DiSSCo Prepare, and others to follow) and the DiSSCo Programme leadership as the journey towards organisational, technical, scientific, data and financial readiness continues. Nevertheless, significant obstacles must be overcome as a matter of priority if DiSSCo is to move beyond its Design and Preparatory Phases during 2024. Specifically, these include: Organisational: Strengthen common purpose by adopting a common framework for policy harmonisation and capacity enhancement across broad areas, especially in respect of digitisation strategy and prioritisation, digitisation processes and techniques, data and digital media publication and open access, protection of and access to sensitive data, and administration of access and benefit sharing. Pursue the joint ventures and other relationships necessary to the successful delivery of the DiSSCo mission, especially ventures with GBIF and other international and regional digitisation and data aggregation organisations, in the context of infrastructure policy frameworks, such as EOSC. Proceed with the explicit aim of avoiding divergences of approach in global natural science collections data management and research. Strengthen common purpose by adopting a common framework for policy harmonisation and capacity enhancement across broad areas, especially in respect of digitisation strategy and prioritisation, digitisation processes and techniques, data and digital media publication and open access, protection of and access to sensitive data, and administration of access and benefit sharing. Pursue the joint ventures and other relationships necessary to the successful delivery of the DiSSCo mission, especially ventures with GBIF and other international and regional digitisation and data aggregation organisations, in the context of infrastructure policy frameworks, such as EOSC. Proceed with the explicit aim of avoiding divergences of approach in global natural science collections data management and research. Technical: Adopt and enhance the DiSSCo Digital Specimen Architecture and, specifically as a matter of urgency, establish the persistent identifier scheme to be used by DiSSCo and (ideally) other comparable regional initiatives. Establish (software) engineering development and (infrastructure) operations team and direction essential to the delivery of services and functionalities expected from DiSSCo such that earnest engineering can lead to an early start of DiSSCo operations. Adopt and enhance the DiSSCo Digital Specimen Architecture and, specifically as a matter of urgency, establish the persistent identifier scheme to be used by DiSSCo and (ideally) other comparable regional initiatives. Establish (software) engineering development and (infrastructure) operations team and direction essential to the delivery of services and functionalities expected from DiSSCo such that earnest engineering can lead to an early start of DiSSCo operations. Scientific: Establish a common digital research agenda leveraging Digital (extended) Specimens as anchoring points for all specimen-associated and -derived information, demonstrating to research institutions and policy/decision-makers the new possibilities, opportunities and value of participating in the DiSSCo research infrastructure. Establish a common digital research agenda leveraging Digital (extended) Specimens as anchoring points for all specimen-associated and -derived information, demonstrating to research institutions and policy/decision-makers the new possibilities, opportunities and value of participating in the DiSSCo research infrastructure. Data: Adopt the FAIR Digital Object Framework and the International Image Interoperability Framework as the low entropy means to achieving uniform access to rich data (image and non-image) that is findable, accessible, interoperable and reusable (FAIR). Develop and promote best practice approaches towards achieving the best digitisation results in terms of quality (best, according to agreed minimum information and other specifications), time (highest throughput, fast), and cost (lowest, minimal per specimen). Adopt the FAIR Digital Object Framework and the International Image Interoperability Framework as the low entropy means to achieving uniform access to rich data (image and non-image) that is findable, accessible, interoperable and reusable (FAIR). Develop and promote best practice approaches towards achieving the best digitisation results in terms of quality (best, according to agreed minimum information and other specifications), time (highest throughput, fast), and cost (lowest, minimal per specimen). Financial Broaden attractiveness (i.e., improve bankability) of DiSSCo as an infrastructure to invest in. Plan for finding ways to bridge the funding gap to avoid disruptions in the critical funding path that risks interrupting core operations; especially when the gap opens between the end of preparations and beginning of implementation due to unsolved political difficulties. Broaden attractiveness (i.e., improve bankability) of DiSSCo as an infrastructure to invest in. Plan for finding ways to bridge the funding gap to avoid disruptions in the critical funding path that risks interrupting core operations; especially when the gap opens between the end of preparations and beginning of implementation due to unsolved political difficulties. Strategically, it is vital to balance the multiple factors addressed by the blueprint against one another to achieve the desired goals of the DiSSCo programme. Decisions cannot be taken on one aspect alone without considering other aspects, and here the various governance structures of DiSSCo (General Assembly, advisory boards, and stakeholder forums) play a critical role over the coming years.

Introduction In December 2010, Nespresso, the world’s leading brand of premium-portioned coffee, opened a flagship “boutique” in Sydney’s Pitt Street Mall. This was Nespresso’s fifth boutique opening of 2010, after Brussels, Miami, Soho, and Munich. The Sydney debut coincided with the mall’s upmarket redevelopment, which explains Nespresso’s arrival in the city: strategic geographic expansion is key to the brand’s growth. Rather than panoramic ubiquity, a retail option favoured by brands like McDonalds, KFC and Starbucks, Nespresso opts for iconic, prestigious locations. This strategy has been highly successful: since 2000 Nespresso has recorded year-on-year per annum growth of 30 per cent. This has been achieved, moreover, despite a global financial downturn and an international coffee market replete with brand variety. In turn, Nespresso marks an evolution in the coffee market over the last decade. The Nespresso Story Founded in 1986, Nespresso is the fasting growing brand in the Nestlé Group. Its headquarters are in Lausanne, Switzerland, with over 7,000 employees worldwide. In 2012, Nespresso had 270 boutiques in 50 countries. The brand’s growth strategy involves three main components: premium coffee capsules, “mated” with specially designed machines, and accompanied by exceptional customer service through the Nespresso Club. Each component requires some explanation. Nespresso offers 16 varieties of Grand Crus coffee: 7 espresso blends, 3 pure origin espressos, 3 lungos (for larger cups), and 3 decaffeinated coffees. Each 5.5 grams of portioned coffee is cased in a hermetically sealed aluminium capsule, or pod, designed to preserve the complex, volatile aromas (between 800 and 900 per pod), and prevent oxidation. These capsules are designed to be used exclusively with Nespresso-branded machines, which are equipped with a patented high-pressure extraction system designed for optimum release of the coffee. These machines, of which there are 28 models, are developed with 6 machine partners, and Antoine Cahen, from Ateliers du Nord in Lausanne, designs most of them. For its consumers, members of the Nespresso Club, the capsules and machines guarantee perfect espresso coffee every time, within seconds and with minimum effort—what Nespresso calls the “ultimate coffee experience.” The Nespresso Club promotes this experience as an everyday luxury, whereby café-quality coffee can be enjoyed in the privacy and comfort of Club members’ homes. This domestic focus is a relatively recent turn in its history. Nestlé patented some of its pod technology in 1976; the compatible machines, initially made in Switzerland by Turmix, were developed a decade later. Nespresso S. A. was set up as a subsidiary unit within the Nestlé Group with a view to target the office and fine restaurant sector. It was first test-marketed in Japan in 1986, and rolled out the same year in Switzerland, France and Italy. However, by 1988, low sales prompted Nespresso’s newly appointed CEO, Jean-Paul Gillard, to rethink the brand’s focus. Gillard subsequently repositioned Nespresso’s target market away from the commercial sector towards high-income households and individuals, and introduced a mail-order distribution system; these elements became the hallmarks of the Nespresso Club (Markides 55). The Nespresso Club was designed to give members who had purchased Nespresso machines 24-hour customer service, by mail, phone, fax, and email. By the end of 1997 there were some 250,000 Club members worldwide. The boom in domestic, user-friendly espresso machines from the early 1990s helped Nespresso’s growth in this period. The cumulative efforts by the main manufacturers—Krups, Bosch, Braun, Saeco and DeLonghi—lowered the machines’ average price to around US $100 (Purpura, “Espresso” 88; Purpura, “New” 116). This paralleled consumers’ growing sophistication, as they became increasingly familiar with café-quality espresso, cappuccino and latté—for reasons to be detailed below. Nespresso was primed to exploit this cultural shift in the market and forge a charismatic point of difference: an aspirational, luxury option within an increasingly accessible and familiar field. Between 2006 and 2008, Nespresso sales more than doubled, prompting a second production factory to supplement the original plant in Avenches (Simonian). In 2008, Nespresso grew 20 times faster than the global coffee market (Reguly B1). As Nespresso sales exceeded $1.3 billion AU in 2009, with 4.8 billion capsules shipped out annually and 5 million Club members worldwide, it became Nestlé’s fastest growing division (Canning 28). According to Nespresso’s Oceania market director, Renaud Tinel, the brand now represents 8 per cent of the total coffee market; of Nespresso specifically, he reports that 10,000 cups (using one capsule per cup) were consumed worldwide each minute in 2009, and that increased to 12,300 cups per minute in 2010 (O’Brien 16). Given such growth in such a brief period, the atypical dynamic between the boutique, the Club and the Nespresso brand warrants closer consideration. Nespresso opened its first boutique in Paris in 2000, on the Avenue des Champs-Élysées. It was a symbolic choice and signalled the brand’s preference for glamorous precincts in cosmopolitan cities. This has become the design template for all Nespresso boutiques, what the company calls “brand embassies” in its press releases. More like art gallery-style emporiums than retail spaces, these boutiques perform three main functions: they showcase Nespresso coffees, machines and accessories (all elegantly displayed); they enable Club members to stock up on capsules; and they offer excellent customer service, which invariably equates to detailed production information. The brand’s revenue model reflects the boutique’s role in the broader business strategy: 50 per cent of Nespresso’s business is generated online, 30 per cent through the boutiques, and 20 per cent through call centres. Whatever floor space these boutiques dedicate to coffee consumption is—compared to the emphasis on exhibition and ambience—minimal and marginal. In turn, this tightly monitored, self-focused model inverts the conventional function of most commercial coffee sites. For several hundred years, the café has fostered a convivial atmosphere, served consumers’ social inclinations, and overwhelmingly encouraged diverse, eclectic clientele. The Nespresso boutique is the antithesis to this, and instead actively limits interaction: the Club “community” does not meet as a community, and is united only in atomised allegiance to the Nespresso brand. In this regard, Nespresso stands in stark contrast to another coffee brand that has been highly successful in recent years—Starbucks. Starbucks famously recreates the aesthetics, rhetoric and atmosphere of the café as a “third place”—a term popularised by urban sociologist Ray Oldenburg to describe non-work, non-domestic spaces where patrons converge for respite or recreation. These liminal spaces (cafés, parks, hair salons, book stores and such locations) might be private, commercial sites, yet they provide opportunities for chance encounters, even therapeutic interactions. In this way, they aid sociability and civic life (Kleinman 193). Long before the term “third place” was coined, coffee houses were deemed exemplars of egalitarian social space. As Rudolf P. Gaudio notes, the early coffee houses of Western Europe, in Oxford and London in the mid-1600s, “were characterized as places where commoners and aristocrats could meet and socialize without regard to rank” (670). From this sanguine perspective, they both informed and animated the modern public sphere. That is, and following Habermas, as a place where a mixed cohort of individuals could meet and discuss matters of public importance, and where politics intersected society, the eighteenth-century British coffee house both typified and strengthened the public sphere (Karababa and Ger 746). Moreover, and even from their early Ottoman origins (Karababa and Ger), there has been an historical correlation between the coffee house and the cosmopolitan, with the latter at least partly defined in terms of demographic breadth (Luckins). Ironically, and insofar as Nespresso appeals to coffee-literate consumers, the brand owes much to Starbucks. In the two decades preceding Nespresso’s arrival, Starbucks played a significant role in refining coffee literacy around the world, gauging mass-market trends, and stirring consumer consciousness. For Nespresso, this constituted major preparatory phenomena, as its strategy (and success) since the early 2000s presupposed the coffee market that Starbucks had helped to create. According to Nespresso’s chief executive Richard Giradot, central to Nespresso’s expansion is a focus on particular cities and their coffee culture (Canning 28). In turn, it pays to take stock of how such cities developed a coffee culture amenable to Nespresso—and therein lays the brand’s debt to Starbucks. Until the last few years, and before celebrity ambassador George Clooney was enlisted in 2005, Nespresso’s marketing was driven primarily by Club members’ recommendations. At the same time, though, Nespresso insisted that Club members were coffee connoisseurs, whose knowledge and enjoyment of coffee exceeded conventional coffee offerings. In 2000, Henk Kwakman, one of Nestlé’s Coffee Specialists, explained the need for portioned coffee in terms of guaranteed perfection, one that demanding consumers would expect. “In general”, he reasoned, “people who really like espresso coffee are very much more quality driven. When you consider such an intense taste experience, the quality is very important. If the espresso is slightly off quality, the connoisseur notices this immediately” (quoted in Butler 50). What matters here is how this corps of connoisseurs grew to a scale big enough to sustain and strengthen the Nespresso system, in the absence of a robust marketing or educative drive by Nespresso (until very recently). Put simply, the brand’s ascent was aided by Starbucks, specifically by the latter’s success in changing the mainstream coffee market during the 1990s. In establishing such a strong transnational presence, Starbucks challenged smaller, competing brands to define themselves with more clarity and conviction. Indeed, working with data that identified just 200 freestanding coffee houses in the US prior to 1990 compared to 14,000 in 2003, Kjeldgaard and Ostberg go so far as to state that: “Put bluntly, in the US there was no local coffee consumptionscape prior to Starbucks” (Kjeldgaard and Ostberg 176). Starbucks effectively redefined the coffee world for mainstream consumers in ways that were directly beneficial for Nespresso. Starbucks: Coffee as Ambience, Experience, and Cultural Capital While visitors to Nespresso boutiques can sample the coffee, with highly trained baristas and staff on site to explain the Nespresso system, in the main there are few concessions to the conventional café experience. Primarily, these boutiques function as material spaces for existing Club members to stock up on capsules, and therefore they complement the Nespresso system with a suitably streamlined space: efficient, stylish and conspicuously upmarket. Outside at least one Sydney boutique for instance (Bondi Junction, in the fashionable eastern suburbs), visitors enter through a club-style cordon, something usually associated with exclusive bars or hotels. This demarcates the boutique from neighbouring coffee chains, and signals Nespresso’s claim to more privileged patrons. This strategy though, the cultivation of a particular customer through aesthetic design and subtle flattery, is not unique. For decades, Starbucks also contrived a “special” coffee experience. Moreover, while the Starbucks model strikes a very different sensorial chord to that of Nespresso (in terms of décor, target consumer and so on) it effectively groomed and prepped everyday coffee drinkers to a level of relative self-sufficiency and expertise—and therein is the link between Starbucks’s mass-marketed approach and Nespresso’s timely arrival. Starbucks opened its first store in 1971, in Seattle. Three partners founded it: Jerry Baldwin and Zev Siegl, both teachers, and Gordon Bowker, a writer. In 1982, as they opened their sixth Seattle store, they were joined by Howard Schultz. Schultz’s trip to Italy the following year led to an entrepreneurial epiphany to which he now attributes Starbucks’s success. Inspired by how cafés in Italy, particularly the espresso bars in Milan, were vibrant social hubs, Schultz returned to the US with a newfound sensitivity to ambience and attitude. In 1987, Schultz bought Starbucks outright and stated his business philosophy thus: “We aren’t in the coffee business, serving people. We are in the people business, serving coffee” (quoted in Ruzich 432). This was articulated most clearly in how Schultz structured Starbucks as the ultimate “third place”, a welcoming amalgam of aromas, music, furniture, textures, literature and free WiFi. This transformed the café experience twofold. First, sensory overload masked the dull homogeny of a global chain with an air of warm, comforting domesticity—an inviting, everyday “home away from home.” To this end, in 1994, Schultz enlisted interior design “mastermind” Wright Massey; with his team of 45 designers, Massey created the chain’s decor blueprint, an “oasis for contemplation” (quoted in Scerri 60). At the same time though, and second, Starbucks promoted a revisionist, airbrushed version of how the coffee was produced. Patrons could see and smell the freshly roasted beans, and read about their places of origin in the free pamphlets. In this way, Starbucks merged the exotic and the cosmopolitan. The global supply chain underwent an image makeover, helped by a “new” vocabulary that familiarised its coffee drinkers with the diversity and complexity of coffee, and such terms as aroma, acidity, body and flavour. This strategy had a decisive impact on the coffee market, first in the US and then elsewhere: Starbucks oversaw a significant expansion in coffee consumption, both quantitatively and qualitatively. In the decades following the Second World War, coffee consumption in the US reached a plateau. Moreover, as Steven Topik points out, the rise of this type of coffee connoisseurship actually coincided with declining per capita consumption of coffee in the US—so the social status attributed to specialised knowledge of coffee “saved” the market: “Coffee’s rise as a sign of distinction and connoisseurship meant its appeal was no longer just its photoactive role as a stimulant nor the democratic sociability of the coffee shop” (Topik 100). Starbucks’s singular triumph was to not only convert non-coffee drinkers, but also train them to a level of relative sophistication. The average “cup o’ Joe” thus gave way to the latte, cappuccino, macchiato and more, and a world of coffee hitherto beyond (perhaps above) the average American consumer became both regular and routine. By 2003, Starbucks’s revenue was US $4.1 billion, and by 2012 there were almost 20,000 stores in 58 countries. As an idealised “third place,” Starbucks functioned as a welcoming haven that flattened out and muted the realities of global trade. The variety of beans on offer (Arabica, Latin American, speciality single origin and so on) bespoke a generous and bountiful modernity; while brochures schooled patrons in the nuances of terroir, an appreciation for origin and distinctiveness that encoded cultural capital. This positioned Starbucks within a happy narrative of the coffee economy, and drew patrons into this story by flattering their consumer choices. Against the generic sameness of supermarket options, Starbucks promised distinction, in Pierre Bourdieu’s sense of the term, and diversity in its coffee offerings. For Greg Dickinson, the Starbucks experience—the scent of the beans, the sound of the grinders, the taste of the coffees—negated the abstractions of postmodern, global trade: by sensory seduction, patrons connected with something real, authentic and material. At the same time, Starbucks professed commitment to the “triple bottom line” (Savitz), the corporate mantra that has morphed into virtual orthodoxy over the last fifteen years. This was hardly surprising; companies that trade in food staples typically grown in developing regions (coffee, tea, sugar, and coffee) felt the “political-aesthetic problematization of food” (Sassatelli and Davolio). This saw increasingly cognisant consumers trying to reconcile the pleasures of consumption with environmental and human responsibilities. The “triple bottom line” approach, which ostensibly promotes best business practice for people, profits and the planet, was folded into Starbucks’s marketing. The company heavily promoted its range of civic engagement, such as donations to nurses’ associations, literacy programs, clean water programs, and fair dealings with its coffee growers in developing societies (Simon). This bode well for its target market. As Constance M. Ruch has argued, Starbucks sought the burgeoning and lucrative “bobo” class, a term Ruch borrows from David Brooks. A portmanteau of “bourgeois bohemians,” “bobo” describes the educated elite that seeks the ambience and experience of a counter-cultural aesthetic, but without the political commitment. Until the last few years, it seemed Starbucks had successfully grafted this cultural zeitgeist onto its “third place.” Ironically, the scale and scope of the brand’s success has meant that Starbucks’s claim to an ethical agenda draws frequent and often fierce attack. As a global behemoth, Starbucks evolved into an iconic symbol of advanced consumer culture. For those critical of how such brands overwhelm smaller, more local competition, the brand is now synonymous for insidious, unstoppable retail spread. This in turn renders Starbucks vulnerable to protests that, despite its gestures towards sustainability (human and environmental), and by virtue of its size, ubiquity and ultimately conservative philosophy, it has lost whatever cachet or charm it supposedly once had. As Bryant Simon argues, in co-opting the language of ethical practice within an ultimately corporatist context, Starbucks only ever appealed to a modest form of altruism; not just in terms of the funds committed to worthy causes, but also to move thorny issues to “the most non-contentious middle-ground,” lest conservative customers felt alienated (Simon 162). Yet, having flagged itself as an ethical brand, Starbucks became an even bigger target for anti-corporatist sentiment, and the charge that, as a multinational giant, it remained complicit in (and one of the biggest benefactors of) a starkly inequitable and asymmetric global trade. It remains a major presence in the world coffee market, and arguably the most famous of the coffee chains. Over the last decade though, the speed and intensity with which Nespresso has grown, coupled with its atypical approach to consumer engagement, suggests that, in terms of brand equity, it now offers a more compelling point of difference than Starbucks. Brand “Me” Insofar as the Nespresso system depends on a consumer market versed in the intricacies of quality coffee, Starbucks can be at least partly credited for nurturing a more refined palate amongst everyday coffee drinkers. Yet while Starbucks courted the “average” consumer in its quest for market control, saturating the suburban landscape with thousands of virtually indistinguishable stores, Nespresso marks a very different sensibility. Put simply, Nespresso inverts the logic of a coffee house as a “third place,” and patrons are drawn not to socialise and relax but to pursue their own highly individualised interests. The difference with Starbucks could not be starker. One visitor to the Bloomingdale boutique (in New York’s fashionable Soho district) described it as having “the feel of Switzerland rather than Seattle. Instead of velvet sofas and comfy music, it has hard surfaces, bright colours and European hostesses” (Gapper 9). By creating a system that narrows the gap between production and consumption, to the point where Nespresso boutiques advertise the coffee brand but do not promote on-site coffee drinking, the boutiques are blithely indifferent to the historical, romanticised image of the coffee house as a meeting place. The result is a coffee experience that exploits the sophistication and vanity of aspirational consumers, but ignores the socialising scaffold by which coffee houses historically and perhaps naively made some claim to community building. If anything, Nespresso restricts patrons’ contemplative field: they consider only their relationships to the brand. In turn, Nespresso offers the ultimate expression of contemporary consumer capitalism, a hyper-individual experience for a hyper-modern age. By developing a global brand that is both luxurious and niche, Nespresso became “the Louis Vuitton of coffee” (Betts 14). Where Starbucks pursued retail ubiquity, Nespresso targets affluent, upmarket cities. As chief executive Richard Giradot put it, with no hint of embarrassment or apology: “If you take China, for example, we are not speaking about China, we are speaking about Shanghai, Hong Kong, Beijing because you will not sell our concept in the middle of nowhere in China” (quoted in Canning 28). For this reason, while Europe accounts for 90 per cent of Nespresso sales (Betts 15), its forays into the Americas, Asia and Australasia invariably spotlights cities that are already iconic or emerging economic hubs. The first boutique in Latin America, for instance, was opened in Jardins, a wealthy suburb in Sao Paulo, Brazil. In Nespresso, Nestlé has popularised a coffee experience neatly suited to contemporary consumer trends: Club members inhabit a branded world as hermetically sealed as the aluminium pods they purchase and consume. Besides the Club’s phone, fax and online distribution channels, pods can only be bought at the boutiques, which minimise even the potential for serendipitous mingling. The baristas are there primarily for product demonstrations, whilst highly trained staff recite the machines’ strengths (be they in design or utility), or information about the actual coffees. For Club members, the boutique service is merely the human extension of Nespresso’s online presence, whereby product information becomes increasingly tailored to increasingly individualised tastes. In the boutique, this emphasis on the individual is sold in terms of elegance, expedience and privilege. Nespresso boasts that over 70 per cent of its workforce is “customer facing,” sharing their passion and knowledge with Club members. Having already received and processed the product information (through the website, boutique staff, and promotional brochures), Club members need not do anything more than purchase their pods. In some of the more recently opened boutiques, such as in Paris-Madeleine, there is even an Exclusive Room where only Club members may enter—curious tourists (or potential members) are kept out. Club members though can select their preferred Grands Crus and checkout automatically, thanks to RFID (radio frequency identification) technology inserted in the capsule sleeves. So, where Starbucks exudes an inclusive, hearth-like hospitality, the Nespresso Club appears more like a pampered clique, albeit a growing one. As described in the Financial Times, “combine the reception desk of a designer hotel with an expensive fashion display and you get some idea what a Nespresso ‘coffee boutique’ is like” (Wiggins and Simonian 10). Conclusion Instead of sociability, Nespresso puts a premium on exclusivity and the knowledge gained through that exclusive experience. The more Club members know about the coffee, the faster and more individualised (and “therefore” better) the transaction they have with the Nespresso brand. This in turn confirms Zygmunt Bauman’s contention that, in a consumer society, being free to choose requires competence: “Freedom to choose does not mean that all choices are right—there are good and bad choices, better and worse choices. The kind of choice eventually made is the evidence of competence or its lack” (Bauman 43-44). Consumption here becomes an endless process of self-fashioning through commodities; a process Eva Illouz considers “all the more strenuous when the market recruits the consumer through the sysiphian exercise of his/her freedom to choose who he/she is” (Illouz 392). In a status-based setting, the more finely graded the differences between commodities (various places of origin, blends, intensities, and so on), the harder the consumer works to stay ahead—which means to be sufficiently informed. Consumers are locked in a game of constant reassurance, to show upward mobility to both themselves and society. For all that, and like Starbucks, Nespresso shows some signs of corporate social responsibility. In 2009, the company announced its “Ecolaboration” initiative, a series of eco-friendly targets for 2013. By then, Nespresso aims to: source 80 per cent of its coffee through Sustainable Quality Programs and Rainforest Alliance Certified farms; triple its capacity to recycle used capsules to 75 per cent; and reduce the overall carbon footprint required to produce each cup of Nespresso by 20 per cent (Nespresso). This information is conveyed through the brand’s website, press releases and brochures. However, since such endeavours are now de rigueur for many brands, it does not register as particularly innovative, progressive or challenging: it is an unexceptional (even expected) part of contemporary mainstream marketing. Indeed, the use of actor George Clooney as Nespresso’s brand ambassador since 2005 shows shrewd appraisal of consumers’ political and cultural sensibilities. As a celebrity who splits his time between Hollywood and Lake Como in Italy, Clooney embodies the glamorous, cosmopolitan lifestyle that Nespresso signifies. 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