2,341 research outputs found

    DuckPGQ: Efficient property graph queries in an analytical RDBMS

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    In the past decade, property graph databases have emerged as a growing niche in data management. Many native graph systems and query languages have been created, but the functionality and performance still leave much room for improvement. The upcoming SQL:2023 will introduce the Property Graph Queries (SQL/PGQ) sub-language, giving relational systems the opportunity to standard- ize graph queries, and provide mature graph query functionality. We argue that (i) competent graph data systems must build on all technology that makes up a state-of-the-art relational system, (ii) the graph use case requires the addition to that of a many- source/destination path-finding algorithm and compact graph rep- resentation, and (iii) incites research in practical worst-case-optimal joins and factorized query processing techniques. We outline our design of DuckPGQ that follows this recipe, by adding efficient SQL/PGQ support to the popular open-source “embeddable analytics” relational database system DuckDB, also originally developed at CWI. Our design aims at minimizing techni- cal debt using an approach that relies on efficient vectorized UDFs. We benchmark DuckPGQ showing encouraging performance and scalability on large graph data sets, but also reinforcing the need for future research under (iii)

    Facilitating prosociality through technology: Design to promote digital volunteerism

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    Volunteerism covers many activities involving no financial rewards for volunteers but which contribute to the common good. There is existing work in designing technology for volunteerism in HumanComputer Interaction (HCI) and related disciplines that focuses on motivation to improve performance, but it does not account for volunteer wellbeing. Here, I investigate digital volunteerism in three case studies with a focus on volunteer motivation, engagement, and wellbeing. My research involved volunteers and others in the volunteering context to generate recommendations for a volunteer-centric design for digital volunteerism. The thesis has three aims: 1. To investigate motivational aspects critical for enhancing digital volunteers’ experiences 2. To identify digital platform attributes linked to volunteer wellbeing 3. To create guidelines for effectively supporting volunteer engagement in digital volunteering platforms In the first case study I investigate the design of a chat widget for volunteers working in an organisation with a view to develop a design that improves their workflow and wellbeing. The second case study investigates the needs, motivations, and wellbeing of volunteers who help medical students improve their medical communication skills. An initial mixed-methods study was followed by an experiment comparing two design strategies to improve volunteer relatedness; an important indicator of wellbeing. The third case study looks into volunteer needs, experiences, motivations, and wellbeing with a focus on volunteer identity and meaning-making on a science-based research platform. I then analyse my findings from these case studies using the lens of care ethics to derive critical insights for design. The key contributions of this thesis are design strategies and critical insights, and a volunteer-centric design framework to enhance the motivation, wellbeing and engagement of digital volunteers

    The Politics of Platformization: Amsterdam Dialogues on Platform Theory

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    What is platformization and why is it a relevant category in the contemporary political landscape? How is it related to cybernetics and the history of computation? This book tries to answer such questions by engaging in multidisciplinary dialogues about the first ten years of the emerging fields of platform studies and platform theory. It deploys a narrative and playful approach that makes use of anecdotes, personal histories, etymologies, and futurable speculations to investigate both the fragmented genealogy that led to platformization and the organizational and economic trends that guide nowadays platform sociotechnical imaginaries

    Machine-Readable Lives or ‘Troubled Families’? Classification, categorisation and stereotyping in data collection and sharing in children’s social care in England

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    Critical data studies examines how the collection and use of data interact with systems of power: they shape who can know what about the world, and to what uses this knowledge can be put. This thesis uses feminist and queer approaches to consider the human rights impact of the collection and sharing of data in children’s services in England. I draw on a wide range of critical literature to situate and explore a case study: the ‘Troubled/Supporting Families Programme’ which plays a key role in children’s social care, and in the wider project of public sector datafication in England. In this thesis, I use the concepts of classification - segmentation of the world - and categorisation - naming the segments - to surface how the collection and sharing of data is not neutral but the outcome of human decision-making. I situate the collection and sharing of data within the history of information-gathering and decision-making in children’s services and with the political choices which have shaped service delivery and datafication. Classification and categorisation are used to define the ‘family’ as a unit of analysis, which enables the identification of the ‘problem family,’ and further its definition as implicitly outside of the norm. Through examining the ways in which data systems classify, categorise and stereotype individuals who are known to social services based on their gender, I show how the expectation that individual and family lives are legible to computers is used to normalise certain forms of families, and stereotype those who do not comply as ‘troubled.

    Automatic characterization and generation of music loops and instrument samples for electronic music production

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    Repurposing audio material to create new music - also known as sampling - was a foundation of electronic music and is a fundamental component of this practice. Currently, large-scale databases of audio offer vast collections of audio material for users to work with. The navigation on these databases is heavily focused on hierarchical tree directories. Consequently, sound retrieval is tiresome and often identified as an undesired interruption in the creative process. We address two fundamental methods for navigating sounds: characterization and generation. Characterizing loops and one-shots in terms of instruments or instrumentation allows for organizing unstructured collections and a faster retrieval for music-making. The generation of loops and one-shot sounds enables the creation of new sounds not present in an audio collection through interpolation or modification of the existing material. To achieve this, we employ deep-learning-based data-driven methodologies for classification and generation.Repurposing audio material to create new music - also known as sampling - was a foundation of electronic music and is a fundamental component of this practice. Currently, large-scale databases of audio offer vast collections of audio material for users to work with. The navigation on these databases is heavily focused on hierarchical tree directories. Consequently, sound retrieval is tiresome and often identified as an undesired interruption in the creative process. We address two fundamental methods for navigating sounds: characterization and generation. Characterizing loops and one-shots in terms of instruments or instrumentation allows for organizing unstructured collections and a faster retrieval for music-making. The generation of loops and one-shot sounds enables the creation of new sounds not present in an audio collection through interpolation or modification of the existing material. To achieve this, we employ deep-learning-based data-driven methodologies for classification and generation

    Timbral Analysis and Recording Parameter Transformations of Snare Drums

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    A snare drum is capable of producing a wide range of timbres influenced by playing technique, its physical construction, and the recording methods used. When a recording engineer configures drums and studio equipment, they adjust a plethora of real-world recording parameters to achieve the desired timbre. These recording parameters impart their own timbral properties by varying amounts, and in most cases the only way to modify these properties is to re-record the audio with changes applied to the real-world variables. This thesis examines methods for computational transformations of snare drum recordings to elicit perceptual changes that mimic modification of real-world recording variables. This is achieved through four main investigations, presented throughout this thesis, two which cover timbral analysis of snare drum recordings, and two which explore post-hoc recording parameter transformations. Strike velocity and microphone selection are factors known to affect snare drum timbre, the first study analyses timbral differences associated with snare drum strike velocity. Results show that listeners are able to distinguish between high and low velocity strikes using timbral cues alone, with microphone selection having no influence on this perceptual identification. Audio analysis reveals distinct temporal and spectral features, with higher velocity strikes producing greater energy in the lower mid-range and significantly longer decay times. The second study aims to demystify the subjective preference of different microphones for snare drum recording. For the majority of microphones, preference does not change between isolated strikes and those with the presence of bleed from the hi-hat and kick drum. On average, preference is higher for condenser microphones compared to dynamic. Additionally, spectral centroid and an objective measure of brightness positively correlate with subjective scores. The ability to perceptually modify drum recording parameters in a post-recording process would be of great benefit to engineers limited by time or equipment. The first post-hoc recording parameter transformation study focuses on microphone selection, mapping the spectral features from highly-preferred microphones onto a microphone with less favourable timbral characteristics. This investigation also details the development and evaluation of a robotic drum arm for consistent strike velocity. Subjective assessment reveals that participants show no preferences between recordings from highly-preferred microphones and those from a transformed least-preferred microphone. The last study employs a data-driven approach for post-recording modification of dampening and microphone position. The system consists of a autoencoder that analyses an audio input and predicts optimal parameters of one or more third-party audio effects, which process the audio to produce the desired transformations. Two novel audio effects are proposed and compared against existing audio plugins. Perceptual quality of transformations is assessed through a subjective listening test and an object evaluation is used to measure system performance, positive results demonstrate a capacity to emulate snare dampening

    Transgressive Positivity in Four Online Multiplayer Games

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    Online games have a reputation for toxicity. Forms of play that have been theorized as transgressive from the perspective of idealized play have become highly normalized within the toxic space of online gaming. In this context, positivity in online gaming takes on a transgressive quality that challenges the common behaviours, the norms of communication, and their underlying ideologies found within online gaming communities. Through an ethnography of four massively multiplayer online game spaces - DOTA 2, Lost Ark, Destiny 2, and World of Warcraft - this project examines the effects of positivity in play on others who share these game worlds to consider ways that positivity might be leveraged to impact gaming’s toxic culture. Positivity is approached through different scales, from smaller individual actions like friendly greetings and helpful gestures not often seen in these particular games, to larger community formations that promote positivity and inclusivity within these gaming communities. This study finds that positivity across these scales produces substantial and proportional resistance to positive deviations from the toxic norms within these games and their linked community sites. Players actively trying to resist toxicity through positivity add varying levels of labor to their leisure and are frequent targets for harassment, leading to burnout or self-exclusion from these online games. Transgressive positivity in online play can produce alternatives to self-exclusion from gaming by producing ephemeral connections and networks of support between players. Enclaves built on positivity can form, but they are always under threat when they intersect with the mainstream culture across each of these four games. Ultimately, there are severe systemic issues within these communities - reinforced by trends within the games industry and in online game design - that undercut player-led positivity initiatives. While positivity can be a useful strategy for some to connect with others and to persist in spite of these toxic environments, positivity’s transgressive quality in online play produces substantial vulnerability for those who actively pursue it as a strategy of resistance or cultural intervention

    Self-service business intelligence and analytics application scenarios: A taxonomy for differentiation

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    Self-service business intelligence and analytics (SSBIA) empowers non-IT users to create reports and analyses independently. SSBIA methods and processes are discussed in the context of an increasing number of application scenarios. However, previous research on SSBIA has made distinctions among these scenarios only to a limited extent. These scenarios include a wide variety of activities ranging from simple data retrieval to the application of complex algorithms and methods of analysis. The question of which dimensions are suitable for differentiating SSBIA application scenarios remains unanswered. In this article, we develop a taxonomy to distinguish among SSBIA applications more effectively by analyzing the relevant scientific literature and current SSBIA tools as well as by conducting a case study in a company. Both researchers and practitioners can use this taxonomy to describe and analyze SSBIA scenarios in further detail. In this way, the opportunities and challenges associated with SSBIA application can be identified more clearly. In addition, we conduct a cluster analysis based on the SSBIA tools thus analyzed. We identify three archetypes that describe typical SSBIA tools. These archetypes identify the application scenarios that are addressed most frequently by SSBIA tool providers. We conclude by highlighting the limitations of this research and suggesting an agenda for future research

    TikTok Battlefield: Comparative Analysis of English and Arabic Language Representations of The 2022 Russian Ukrainian Conflict On TikTok

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    This study extends the growing political communication research on TikTok platform through studying the representation of a major political conflict in modern history; the 2022 Russian Ukrainian conflict. The study is providing a cross cultural comparison by studying the perspectives of English and Arabic speakers about the conflict. The study is based on the analysis of the 500 most liked TikTok videos - in one month duration that starts with the day of the Russian invasion - with top hashtags about the conflict in order to find the common message themes. The study uses a multi-dimensional analysis approach of connective action, collective action, and issue-specific frames to understand how TikTok was used as a social mobilization tool in reference to the conflict and how the users\u27 languages affected these frames. The study also looked at the use of technology affordances to create memetic dimensions of content, form, and stance. As each political conflict represents its own circumstances and dynamics, unlike TikTok’s nature, this study found that the artistic / humorous message theme did not represent the most prominent theme in both Arabic and English language videos. Also, message themes of victims and activists’ reference were more prevalent in English language videos in comparison to Arabic language videos. The results also revealed that connective action frames (personal experiences and emotional commentary) and collective action frames (perceived injustice and agency) were widely utilized in English language videos. However, issue-specific frames (problem definition) were widely found in Arabic language videos. Additionally, the most prominent tone of communication was found to be “serious” in both English and Arabic language videos, and the most prominent communicative function was “referential communication”. The most important finding of this study was the change in TikTok usual usage of playful communication in favor of serious and informative content. Moreover, TikTok unique affordances of association “Duets and stitches” were rarely used in the examined videos. The practical implication of this study is to understand TikTok’s position on the map of social media political expression, given the application’s unique affordances. The present research coming from the MENA region and comparing it with the other world aims at crossing the gap in comparative research by examining how the playful platform is used among English and Arabic speakers posting about a political conflict of a global impact
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