Beyond shape – An exploration in alternative forms for data visualization

This thesis explores the topic of alternative forms in data visualization and the ways visualization affects the communication of data it is based on. It does this through the creation of a machine learning based data visualization system prototype. It examines norms and ideals of data visualization as a set of systems aimed for simplification, situating visualization as a tool with the potential power to affect how we perceive the complexity of the world by either highlighting or obscuring information. It aims to critically highlight these norms by taking an exploratory aim to visualizing information by increasing potential interpretations of a particular set of data instead of reducing them. Norms prevalent in the field of data visualization are explored, and through this, the concept of alternative is defined. Then the dataset to visualize is defined through an exploration of current discussions around issues of increasing amounts of data, the complexity of the systems producing that data and the interpretations they enforce through the data they produce. Through this, the concept of machine detected human emotions in a text is chosen as a particular example of computational reduction to be explored through the prototype. In order to counteract this identified reduction in complexity, a system which produces a mapping between visual attributes and detected emotional attributes is proposed. The design of this system utilizes recognized critical design concepts by creating a type of post-optimal object: A visualization that causes more interpretations in its reader than reading the data itself. The process of visualization follows prevalent norms within the field but applies identified forms of alternativeness in order to create ambiguity in the visual artifacts created by the prototype. Machine learning methods are applied through a collaborative process in order to create an artificially intelligent system that automatically analyses the emotional values of a given text, and maps those to a particular set of figures. Some of the visual artifacts are then tested on a set of users, in order to assess how the visualization might affect the communication of the data it is based on and how it succeeds in increasing interpretational complexity. While not aimed toward conclusive evidence, the result of the test seems to indicate success in increasing interpretational complexity, but a lack of success in communicating the numeric data the visualizations are based on – in this sense leading to the end-result no longer being a functional data visualization, but rather a form of data-driven illustration.Denna avhandling handlar om alternativa former inom datavisualisering och sätten visualisering påverkar kommunicering av data den byggs utav, genom skapandet av en maskininlärningsbaserad datavisualiseringsprototyp. Genom det, undersöks de ideala normerna inom datavisualisering som fält som en samling konventioner med simplifiering som ändamål. Datavisualisering placeras som ett verktyg med förmågan att ändra hur vi uppfattar världens komplexitet genom att antingen framhäva eller undangömma. Genom att ställa ett explorativt mål – att visualisera data genom att utvidga tolkningar istället för att reducera dem då produceringen av den data som visualiseras är komplext är avsikten att kritiskt examinera dessa normer. Först undersöks fältets normer och genom detta definieras vad kunde anses som alternativ datavisualisering. Sedan identifieras ett komplext problem som kunde visualiseras genom en utforskning av aktuella synpunkter runt den växande mängden data I världen omkring oss och komplexiteten av de system som producerar detta data. Genom detta väljs maskinbaserad detektion av människokänslor som ett problem där maskinbaserad reduktion kan forskas genom visualisering. För att motverka reduktionistisk behandling av komplicerade domän, föreslås ett system som producerar översättningar mellan emotionella egenskaper och visuella egenskaper. Konstruktionen av detta system använder sig av kritiska designmetoder genom att bygga ett postoptimalt objekt: En datavisualisering som inte försöker kommunicera data den består utav så klart som möjligt, men istället försöker orsaka en ökande mängd tolkningar i sin läsare. Processen följer de normer som är rådande I fältet, men med ändamålet att orsaka tvetydighet för läsaren. Maskininlärning används för att implementera en kollaborativt framställd översättningsmodell mellan de emotionella och de visuella egenskaperna. Slutligen testas systemet genom en mätning av effekterna på läsare och på så sätt utvärderas visualiseringens förmåga att öka mängden tolkningar. Undersökningen har inte som mål att ge ett slutligt resultat för funktionaliteten av systemet, men skall fungera som guide för nästa iterationer. Undersökningen verkar visa att de producerade visualiseringarna lyckas i att öka mängden tolkningar för en bild till en nivå som påminner om tolkningarna för text, men lyckas inte att kommunicera känslorna från den lästa texten. Detta gör slutresultatet mer av en data-inspirerad illustration, än en datavisualisering som termen konventionellt används

Lukiovertailusovellus

Insinöörityön tavoitteena oli kehittää datajournalistinen lukiovertailusovellus tilaajayritykselle. Pyrkimyksenä oli verkkosovelluksen avulla visualisoida tilaajayrityksen lukiovertailua varten keräämää data-aineistoa ja luoda sovelluksesta datajournalistinen tuote tilaajayrityksen asiakkaille muun aiheeseen liittyvän journalistisen sisällön oheen. Toteutuksen pohjustamiseksi tutkittiin moderneja tapoja toteuttaa verkkosovelluksia pyrkien tarkastelemaan niitä uutistoimitusympäristön tarpeiden ja vaatimusten näkökulmasta. Tä-män tutkimuksen perusteella valittiin teknistä toteutusta varten yhdistelmä moderneja verkkoteknologioita, jotka mahdollistavat uutistoimistoympäristöön sopivan nopean verkko-sovelluskehityksen. Lisäksi tutkittiin ja tarkasteltiin datajournalismin ja datavisualisoinnin käsitteitä ja niiden merkitystä sovelluskehityksen kannalta journalistisessa ympäristössä. Tämä tutkimus antoi kuvan informaatiomuotoilun hyviksi todetuista periaatteista, joita hyödynnettiin sovelluksen suunnittelussa ja arvioinnissa. Sovellus toteutettiin tutkimuksen pohjalta hyödyntäen MongoDB-NOSQL-tietokantaa, Node.js-palvelinympäristöä ja Javascript-pohjaisia datavisualisointikirjastoja. Palvelinsovelluksen ja asiakassovelluksen välinen tiedonsiirto toteutettiin REST-rajapinnan avulla niin, että asiakas- ja palvelinsovellus pidettiin erillisinä toisistaan SPA-arkkitehtuurimallin mukai-sesti. Sovellus visualisoi lukiovertailusta saatavan aineiston karttapohjaisessa näkymässä ja mahdollistaa aineiston vuosikohtaisen vertailun jokaisen lukion kohdalla. Loppuasiakas pystyy myös paikallistamaan sovelluksen maakuntatasolla. Sovellus julkaistiin kevään 2014 ylioppilaskirjoitustulosten julkaisun yhteydessä 31.5.2014. Tilaajayrityksen loppuasiakkaista yksi julkaisi sovelluksen sivullaan. Sovellus on tilaajayrityksen jatkokehityksessä ja sitä käytetään jatkossa ylioppilaskoetulosten julkaisuun: sisällöltään päivitetty versio julkaistiin 26.12.2014 syksyn ylioppilaskirjoitusten yhteydessä ja se keräsi noin 7 500 käyttäjää päivässä.The purpose of this thesis project was to develop a data journalistic web application based on data acquired from a national high school comparison made by the ordering company, STT-Lehtikuva. The aim was to create digital product to accompany the traditional journalistic content regarding the high school comparison. In order to build the application, research was made into modern methods of web application development, with a focus on the aspect of functionality in a newsroom environment. This research was used to choose a combination of web application development tools and technologies that are suitable for rapid development and publishing. Furthermore, the concepts of data journalism and data visualisation were explored, inspecting their meaning for software development in a journalistic environment. This research was used to form an informed view about best practices of visualizing information in a journalistic context, which was utilized in the visual design of the application. The application was built using a MongoDB- NOSQL -database, the Node.js server runtime environment and Javascript-based data visualisation libraries. Communication between the client and the server application was conducted via a REST-API, keeping the client and the server separate as per the SPA-architecture model. The application visualises all Finnish high schools on a map, enabling the user to select specific high schools and view more detailed information about each school. The application was published after the matriculation examination results in the spring of 2014 were released, 31.5.2014. The application is under further development, and will be used for publishing high school comparison results in the future as well. A content-wise up-dated version was published along with the results of the autumn matriculation examination results on the 26th of November, 2014, and it gathered around 7 500 unique visitors in a day.Ändamålet för detta examensarbete var att utveckla en datajournalistisk webbapplikation för uppdragsgivande företaget STT-Lehtikuva (FNB). Applikationens syfte var att visualise-ra data ifrån en nationell gymnasiejämförelse som gjorts av uppdragsgivaren och fungera som en digital produkt för beställarens kunder utöver det traditionella journalistiska utbjudet. För att bygga applikationen, forskades moderna metoder för utveckling av webapplikationer, med särskild fokus på funktionalitet som krävs i en nyhetsredaktionsomgivning. På basis av denna forskning valden en kombination webbteknologier för förverkligandet av applikationen, som möjliggör snabb webbapplikationsutveckling. Förutom det, forskades begreppen datajournalistik och datavisualisering med avsikt att undersöka deras innebörd för mjukvaruutveckling. Detta gav som resultat en bild om vad som anses forma bra informationsdesign för journalistik, vilket togs i beaktan under formgivningen av applikationens visuella användargränssnitt. För förverkligandet av applikationen användes på basis av den gjorda forskningen Node.js-programsystemet, en MongoDB-NOSQL-databas och Javascriptbaserade datavisualiseringsbibliotek. Överföringen av data mellan klient- och serverapplikationen utfördes med i formen av ett REST-gränssnitt, för att hålla de två applikationsdelarna separata enligt SPA-arkitekturmodellen. Applikationen visualiserar gymnasierna i Finland på en karta och möjliggör noggrannare begranskning av datat för enskilda gymnasium. Applikationen publicerades i samband med publiceringen av vårens studentexamensresultat 31.5.2014. Applikationen utvecklas vidare och används också i framtiden för publicerandet av gymnasiejämförelseresultat: En innehållsvis uppdaterad version public-erades 26.11.2014 i samband med höstens studentexamensresultat, och samlade runt 7 500 unika tittare

Explicit behavioral detection of visual changes develops without their implicit neurophysiological detectability

Change blindness is a failure of reporting major changes across consecutive images if separated, e.g., by a brief blank interval. Successful change detection across interrupts requires focal attention to the changes. However, findings of implicit detection of visual changes during change blindness have raised the question of whether the implicit mode is necessary for development of the explicit mode. To this end, we recorded the visual mismatch negativity (vMMN) of the event-related potentials (ERPs) of the brain, an index of implicit pre-attentive visual change detection, in adult humans performing an oddball-variant of change blindness flicker task. Images of 500 ms in duration were presented repeatedly in continuous sequences, alternating with a blank interval (either 100 ms or 500 ms in duration throughout a stimulus sequence). Occasionally (P = 0.2), a change (referring to color changes, omissions, or additions of objects or their parts in the image) was present. The participants attempted to explicitly (via voluntary button press) detect the occasional change. With both interval durations, it took 10–15 change presentations in average for the participants to eventually detect the changes explicitly in a sequence, the 500 ms interval only requiring a slightly longer exposure to the series than the 100 ms one. Nevertheless, prior to this point of explicit detectability, the implicit detection of the changes vMMN could only be observed with the 100 ms intervals. These findings of explicit change detection developing with and without implicit change detection may suggest that the two modes of change detection recruit independent neural mechanisms

Northeast Ocean Planning Baseline Assessment: Marine Resources, Infrastructure, and Economics

This document summarizes the status of coastal and marine resources in the Northeast region of the United States, and how these resources generate economic and ecological value. The Northeast region, for ocean planning purposes, includes the coastal counties of Maine, New Hampshire, Massachusetts, Rhode Island, and Connecticut, and the New York counties (bordering Long Island Sound) of Queens, Bronx, Suffolk, Nassau, and Westchester. The coastal and marine natural resources and coastal infrastructure of the Northeast, and the economic activities and cultural/recreational services that rely them, directly and indirectly support more than 500,000 jobs and $40 billion in economic value (GDP) per year (2013 data) in the region. This represents about 2% of the region’s overall economy. In addition, US Navy and Coast Guard activities in the region support more than 10,000 jobs and account for billions of dollars per year in federal expenditures in the region. The region’s coastal and ocean resources also generate significant ecosystem service value in the region and beyond, though these values are not well quantified. Coastal and marine recreation and tourism account for about half of the region’s ocean economy GDP and for more than 70% of ocean economy employment. The maritime transportation sector account for 16% of ocean economy employment and 29% of ocean economy GDP in the region; ship and boat building accounts for 11% of employment and 13% of GDP; and commercial fisheries and seafood processing account for 6% of employment and 8% of GDP. Information about the spatial distribution and status of coastal and marine resources and the economic activities that make use of them inform and support the Northeast ocean planning process

Modulation of impulsive behaviours using transcranial random noise stimulation

Non peer reviewe

Cardiorespiratory Fitness Estimation Based on Heart Rate and Body Acceleration in Adults With Cardiovascular Risk Factors : Validation Study

Publisher Copyright: © Antti-Pekka E Rissanen, Mirva Rottensteiner, Urho M Kujala, Jari L O Kurkela, Jan Wikgren, Jari A Laukkanen. Originally published in JMIR Cardio (https://cardio.jmir.org), 25.10.2022. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cardio, is properly cited. The complete bibliographic information, a link to the original publication on https://cardio.jmir.org, as well as this copyright and license information must be included.Background: Cardiorespiratory fitness (CRF) is an independent risk factor for cardiovascular morbidity and mortality. Adding CRF to conventional risk factors (eg, smoking, hypertension, impaired glucose metabolism, and dyslipidemia) improves the prediction of an individual's risk for adverse health outcomes such as those related to cardiovascular disease. Consequently, it is recommended to determine CRF as part of individualized risk prediction. However, CRF is not determined routinely in everyday clinical practice. Wearable technologies provide a potential strategy to estimate CRF on a daily basis, and such technologies, which provide CRF estimates based on heart rate and body acceleration, have been developed. However, the validity of such technologies in estimating individual CRF in clinically relevant populations is poorly known. Objective: The objective of this study is to evaluate the validity of a wearable technology, which provides estimated CRF based on heart rate and body acceleration, in working-aged adults with cardiovascular risk factors. Methods: In total, 74 adults (age range 35-64 years; n=56, 76% were women; mean BMI 28.7, SD 4.6 kg/m2) with frequent cardiovascular risk factors (eg, n=64, 86% hypertension; n=18, 24% prediabetes; n=14, 19% type 2 diabetes; and n=51, 69% metabolic syndrome) performed a 30-minute self-paced walk on an indoor track and a cardiopulmonary exercise test on a treadmill. CRF, quantified as peak O2 uptake, was both estimated (self-paced walk: a wearable single-lead electrocardiogram device worn to record continuous beat-to-beat R-R intervals and triaxial body acceleration) and measured (cardiopulmonary exercise test: ventilatory gas analysis). The accuracy of the estimated CRF was evaluated against that of the measured CRF. Results: Measured CRF averaged 30.6 (SD 6.3; range 20.1-49.6) mL/kg/min. In all participants (74/74, 100%), mean difference between estimated and measured CRF was −0.1 mL/kg/min (P = .90), mean absolute error was 3.1 mL/kg/min (95% CI 2.6-3.7), mean absolute percentage error was 10.4% (95% CI 8.5-12.5), and intraclass correlation coefficient was 0.88 (95% CI 0.80-0.92). Similar accuracy was observed in various subgroups (sexes, age, BMI categories, hypertension, prediabetes, and metabolic syndrome). However, mean absolute error was 4.2 mL/kg/min (95% CI 2.6-6.1) and mean absolute percentage error was 16.5% (95% CI 8.6-24.4) in the subgroup of patients with type 2 diabetes (14/74, 19%). Conclusions: The error of the CRF estimate, provided by the wearable technology, was likely below or at least very close to the clinically significant level of 3.5 mL/kg/min in working-aged adults with cardiovascular risk factors, but not in the relatively small subgroup of patients with type 2 diabetes. From a large-scale clinical perspective, the findings suggest that wearable technologies have the potential to estimate individual CRF with acceptable accuracy in clinically relevant populations.Peer reviewe

Stress detection using wearable physiological sensors

As the population increases in the world, the ratio of health carers is rapidly decreasing. Therefore, there is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies, usually due to stressful situations during everyday activities including work. This paper presents a machine learning approach for stress detection on people using wearable physiological sensors with the �final aim of improving their quality of life. The presented technique can monitor the state of the subject continuously and classify it into "stressful" or "non-stressful" situations. Our classification results show that this method is a good starting point towards real-time stress detection