INTEGRASI DATA DAN VISUALISASI MENGGUNAKAN METODE TREEMAP DI PT. CHEVRON PACIFIC INDONESIA

bidang perminyakan dan gas. Sebagai perusahaan besar PT.CPI memerlukan adanya pendataan mengenai setiap kegiatan eksplorasi dan produksi yang dihasilkan, seperti data minyak, gas, air, steam, fluid, LPO (Loss Production Oil), status well, data eksplorasi dan produksi lainnya yang ada pada setiap well di seluruh area dan daerah operasi PT. Chevron Pacific Indonesia. Data hasil eksplorasi dan produksi yang tersedia akan diproses dan dikalkulasikan sesuai kriteria datanya. Dengan banyaknya data yang berasal dari berbagi sumber data diperlukan proses untuk mengintegrasikannya dalam sebuah kesatuan data. Agar hasil data yang telah terintegrasi dapat mudah dilihat, dipahami, dan cepat dalam mengambil keputusan maka dibutuhkan sebuah sistem yang dapat memvisualisasikannya dalam bentuk peta data berdasarkan kebutuhan setiap user (manager dan pimpinan tim). Sistem ini dibangun menggunakan metode Treemap. Metode ini sangat sesuai karena dapat memvisualisasikan data berdasarkan group data dan kategori warna dengan menyeluruh dan detail untuk setiap kondisi data well yang terjadi

Unterstützung des Editierens von Graphen in Visuellen Repräsentationen

The goal of this thesis is to provide solutions for supporting the direct editing of graphs in visual representations for analyzing graphs. For that, a conceptual view on the user's tasks is established first. On this basis, several novel approaches to "visually edit" the different data aspects of graphs - the graph's structure and associated attribute values - are introduced. Thereby, different visual graph representations suitable for communicating the data are considered.Das Ziel der vorliegenden Dissertation ist, Lösungen zur Unterstützung des direkten Editierens von Graphen in visuellen Repräsentationen zur Analyse von Graphen bereitzustellen. Dafür wird zunächst eine konzeptuelle Sicht auf die Aufgaben des Nutzers entwickelt. Auf dieser Basis werden anschließend mehrere neue Verfahren eingeführt, welche das "visuelle Editieren" der verschiedenen Datenaspekte von Graphen - der Struktur sowie dazu assoziierte Attributwerte - ermöglichen. Dabei werden verschiedene visuelle Graphrepräsentationen berücksichtigt, welche die Daten in geeigneter Form kommunizieren

Visualizing Set Relations and Cardinalities Using Venn and Euler Diagrams

In medicine, genetics, criminology and various other areas, Venn and Euler diagrams are used to visualize data set relations and their cardinalities. The data sets are represented by closed curves and the data set relationships are depicted by the overlaps between these curves. Both the sets and their intersections are easily visible as the closed curves are preattentively processed and form common regions that have a strong perceptual grouping effect. Besides set relations such as intersection, containment and disjointness, the cardinality of the sets and their intersections can also be depicted in the same diagram (referred to as area-proportional) through the size of the curves and their overlaps. Size is a preattentive feature and so similarities, differences and trends are easily identified. Thus, such diagrams facilitate data analysis and reasoning about the sets. However, drawing these diagrams manually is difficult, often impossible, and current automatic drawing methods do not always produce appropriate diagrams. This dissertation presents novel automatic drawing methods for different types of Euler diagrams and a user study of how such diagrams can help probabilistic judgement. The main drawing algorithms are: eulerForce, which uses a force-directed approach to lay out Euler diagrams; eulerAPE, which draws area-proportional Venn diagrams with ellipses. The user study evaluated the effectiveness of area- proportional Euler diagrams, glyph representations, Euler diagrams with glyphs and text+visualization formats for Bayesian reasoning, and a method eulerGlyphs was devised to automatically and accurately draw the assessed visualizations for any Bayesian problem. Additionally, analytic algorithms that instantaneously compute the overlapping areas of three general intersecting ellipses are provided, together with an evaluation of the effectiveness of ellipses in drawing accurate area-proportional Venn diagrams for 3-set data and the characteristics of the data that can be depicted accurately with ellipses

Digital traces and urban research : Barcelona through social media data

Most of the world’s population now resides in urban areas, and it is expected that almost all of the planet’s growth will be concentrated in them for the next 30 years, making the improvement of the quality of life in the cities one of the big challenges of this century. To that end, it is crucial to have information on how people use the spaces in the city, and allows urban planning to successfully respond to their needs. This dissertation proposes using data shared voluntarily by the millions of users that make up social network’s communities as a valuable tool for the study of the complexity of the city, because of its capacity of providing an unprecedented volume of urban information, with geographic, temporal, semantic and multimedia components. However, the volume and variety of data raises important challenges regarding its retrieval, manipulation, analysis and representation, requiring the adoption of the best practices in data science, using a multi-faceted approach in the field of urban studies with a strong emphasis in the reproducibility of the developed methodologies. This research focuses in the case of study of the city of Barcelona, using the public data collected from Panoramio, Flickr, Twitter and Instagram. After a literature review, the methods to access the different services are discussed, along with their available data and limitations. Next, the retrieved data is analyzed at different spatial and temporal scales. The first approximation to data focuses on the origins of users who took geotagged pictures of Barcelona, geocoding the hometowns that appear in their Flickr public profiles, allowing the identification of the regions, countries and cities with the largest influx of visitors, and relating the results with multiple indicators at a global scale. The next scale of analysis discusses the city as a whole, developing methodologies for the representation of the spatial distribution of the collected locations, avoiding the artifacts produced by overplotting. To this end, locations are aggregated in regular tessellations, whose size is determined empirically from their spatial distribution. Two spatial statistics techniques (Moran’s I and Getis-Ord’s G*) are used to visualize the local spatial autocorrelation of the areas with exceptionally high or low densities, under a statistical significance framework. Finally, the kernel density estimation is introduced as a non-parametric alternative. The third level of detail follows the official administrative division of Barcelona in 73 neighborhoods and 12 districts, which obeys to historical, morphological and functional criteria. Micromaps are introduced as a representation technique capable of providing a geographical context to commonly used statistical graphics, along with a methodology to produce these micromaps automatically. This technique is compared to annotated scatterplots to relate picture intensity with different urban indicators at a neighborhood scale. The hypothesis of spatial homogeneity is abandoned at the most detailed scale, focusing the analysis on the street network. Two techniques to assign events to road segments in the street graph are presented (direct by shortest distance or by proxy through the postal addresses), as well as the generalization of the kernel density estimation from the Euclidean space to a network topology. Beyond the spatial domain, the interactions of three temporal cycles are further analyzed using the timestamps available in the picture metadata: daytime/nighttime (daily cycle), work/leisure (weekly cycle) and seasonal (yearly cycle).La major part de la població mundial resideix actualment en àrees urbanes, i es preveu que pràcticament tot el creixement del planeta es concentri en elles en els propers 30 anys, convertint la millora de la qualitat de vida a les ciutats en un dels grans reptes del present segle. És per tant imprescindible disposar d'informació sobre les activitats que les persones desenvolupen en elles, que permetin al planejament donar resposta a les seves necessitats. Aquesta tesi proposa l'ús de dades compartides de manera voluntària pels milions d'usuaris que conformen les comunitats de les xarxes socials com una valuosa eina per a l'estudi de la complexitat de la ciutat, per la seva capacitat de proporcionar un volum d'informació urbana sense precedents, reunint components tant geogràfics, temporals, semàntics i multimèdia. No obstant això, aquest volum i varietat de les dades planteja grans reptes pel que fa a la seva obtenció, tractament, anàlisi i representació, requerint adoptar les millors pràctiques de la ciència de dades, aplicades des de múltiples punts de vista al camp dels estudis urbans, posant sempre l'èmfasi en la reproductibilitat de les metodologies desenvolupades. Aquesta investigació se centra en el cas d'estudi de la ciutat de Barcelona, a partir de les dades públiques obtingudes de Panoramio, Flickr, Twitter i Instagram. Després d'una revisió de l'estat de l'art, es desenvolupa l'operativa d'accés als diferents serveis, revisant les dades disponibles i les seves limitacions. A continuació, s'analitzen les dades obtingudes en diferents escales espacials i temporals. La primera aproximació a les dades es desenvolupa a partir de l'origen dels usuaris que han pres fotografies geolocalitzades de Barcelona, a través de la geocodificació de les ubicacions que apareixen en els seus perfils públics de Flickr, permetent identificar les regions, països i ciutats amb major afluència de visitants i relacionar els resultats amb diferents indicadors a escala global. La següent escala d'anàlisi es centra en la ciutat en el seu conjunt, desenvolupant metodologies per a la representació de la distribució espacial de les localitzacions obtingudes, evitant els artefactes produïts per la superposició de mostres. Per a això s'agreguen les localitzacions en tesselacions regulars, la mida de les quals es determina empíricament a partir de la seva distribució espacial. S'utilitzen dues tècniques d'estadística espacial (I de Moran i G* de Getis-Ord) per a visualitzar l'autocorrelació espacial local dels àmbits amb densitats excepcionalment altes o baixes, seguint un criteri de significança estadística. Finalment s'introdueix com a alternativa no paramètrica l'estimació de la densitat. El tercer nivell de detall coincideix amb la delimitació administrativa oficial de Barcelona en 73 barris i 12 districtes, realitzada a partir de criteris històrics, morfològics i funcionals. S'introdueixen els micromapes com a tècnica de representació capaç d'aportar un context geogràfic a gràfics estadístics d'ús comú, juntament amb una metodologia per produir aquests micromapes de manera automàtica. Es compara aquesta tècnica amb diagrames de dispersió anotats per a relacionar la intensitat de fotografies amb diferents indicadors urbans a escala de barri. En l'escala més detallada s'abandona la hipòtesi d'homogeneïtat espacial i es trasllada l'anàlisi al sistema viari. Es presenten dues tècniques d'atribució de localitzacions a trams de carrer del graf vial (directa per distància o indirecta a través de les adreces postals), així com la generalització de l'estimació de la densitat d'un espai euclidià a una topologia de xarxa. Fora del context espacial, s'analitzen les interaccions de tres cicles temporals a partir de les metadades del moment en què van ser preses les fotografies: diürn/nocturn (cicle diari), treball/oci (cicle setmanal) i estacional (cicle anual).Postprint (published version

Digital traces and urban research : Barcelona through social media data

Most of the world’s population now resides in urban areas, and it is expected that almost all of the planet’s growth will be concentrated in them for the next 30 years, making the improvement of the quality of life in the cities one of the big challenges of this century. To that end, it is crucial to have information on how people use the spaces in the city, and allows urban planning to successfully respond to their needs. This dissertation proposes using data shared voluntarily by the millions of users that make up social network’s communities as a valuable tool for the study of the complexity of the city, because of its capacity of providing an unprecedented volume of urban information, with geographic, temporal, semantic and multimedia components. However, the volume and variety of data raises important challenges regarding its retrieval, manipulation, analysis and representation, requiring the adoption of the best practices in data science, using a multi-faceted approach in the field of urban studies with a strong emphasis in the reproducibility of the developed methodologies. This research focuses in the case of study of the city of Barcelona, using the public data collected from Panoramio, Flickr, Twitter and Instagram. After a literature review, the methods to access the different services are discussed, along with their available data and limitations. Next, the retrieved data is analyzed at different spatial and temporal scales. The first approximation to data focuses on the origins of users who took geotagged pictures of Barcelona, geocoding the hometowns that appear in their Flickr public profiles, allowing the identification of the regions, countries and cities with the largest influx of visitors, and relating the results with multiple indicators at a global scale. The next scale of analysis discusses the city as a whole, developing methodologies for the representation of the spatial distribution of the collected locations, avoiding the artifacts produced by overplotting. To this end, locations are aggregated in regular tessellations, whose size is determined empirically from their spatial distribution. Two spatial statistics techniques (Moran’s I and Getis-Ord’s G*) are used to visualize the local spatial autocorrelation of the areas with exceptionally high or low densities, under a statistical significance framework. Finally, the kernel density estimation is introduced as a non-parametric alternative. The third level of detail follows the official administrative division of Barcelona in 73 neighborhoods and 12 districts, which obeys to historical, morphological and functional criteria. Micromaps are introduced as a representation technique capable of providing a geographical context to commonly used statistical graphics, along with a methodology to produce these micromaps automatically. This technique is compared to annotated scatterplots to relate picture intensity with different urban indicators at a neighborhood scale. The hypothesis of spatial homogeneity is abandoned at the most detailed scale, focusing the analysis on the street network. Two techniques to assign events to road segments in the street graph are presented (direct by shortest distance or by proxy through the postal addresses), as well as the generalization of the kernel density estimation from the Euclidean space to a network topology. Beyond the spatial domain, the interactions of three temporal cycles are further analyzed using the timestamps available in the picture metadata: daytime/nighttime (daily cycle), work/leisure (weekly cycle) and seasonal (yearly cycle).La major part de la població mundial resideix actualment en àrees urbanes, i es preveu que pràcticament tot el creixement del planeta es concentri en elles en els propers 30 anys, convertint la millora de la qualitat de vida a les ciutats en un dels grans reptes del present segle. És per tant imprescindible disposar d'informació sobre les activitats que les persones desenvolupen en elles, que permetin al planejament donar resposta a les seves necessitats. Aquesta tesi proposa l'ús de dades compartides de manera voluntària pels milions d'usuaris que conformen les comunitats de les xarxes socials com una valuosa eina per a l'estudi de la complexitat de la ciutat, per la seva capacitat de proporcionar un volum d'informació urbana sense precedents, reunint components tant geogràfics, temporals, semàntics i multimèdia. No obstant això, aquest volum i varietat de les dades planteja grans reptes pel que fa a la seva obtenció, tractament, anàlisi i representació, requerint adoptar les millors pràctiques de la ciència de dades, aplicades des de múltiples punts de vista al camp dels estudis urbans, posant sempre l'èmfasi en la reproductibilitat de les metodologies desenvolupades. Aquesta investigació se centra en el cas d'estudi de la ciutat de Barcelona, a partir de les dades públiques obtingudes de Panoramio, Flickr, Twitter i Instagram. Després d'una revisió de l'estat de l'art, es desenvolupa l'operativa d'accés als diferents serveis, revisant les dades disponibles i les seves limitacions. A continuació, s'analitzen les dades obtingudes en diferents escales espacials i temporals. La primera aproximació a les dades es desenvolupa a partir de l'origen dels usuaris que han pres fotografies geolocalitzades de Barcelona, a través de la geocodificació de les ubicacions que apareixen en els seus perfils públics de Flickr, permetent identificar les regions, països i ciutats amb major afluència de visitants i relacionar els resultats amb diferents indicadors a escala global. La següent escala d'anàlisi es centra en la ciutat en el seu conjunt, desenvolupant metodologies per a la representació de la distribució espacial de les localitzacions obtingudes, evitant els artefactes produïts per la superposició de mostres. Per a això s'agreguen les localitzacions en tesselacions regulars, la mida de les quals es determina empíricament a partir de la seva distribució espacial. S'utilitzen dues tècniques d'estadística espacial (I de Moran i G* de Getis-Ord) per a visualitzar l'autocorrelació espacial local dels àmbits amb densitats excepcionalment altes o baixes, seguint un criteri de significança estadística. Finalment s'introdueix com a alternativa no paramètrica l'estimació de la densitat. El tercer nivell de detall coincideix amb la delimitació administrativa oficial de Barcelona en 73 barris i 12 districtes, realitzada a partir de criteris històrics, morfològics i funcionals. S'introdueixen els micromapes com a tècnica de representació capaç d'aportar un context geogràfic a gràfics estadístics d'ús comú, juntament amb una metodologia per produir aquests micromapes de manera automàtica. Es compara aquesta tècnica amb diagrames de dispersió anotats per a relacionar la intensitat de fotografies amb diferents indicadors urbans a escala de barri. En l'escala més detallada s'abandona la hipòtesi d'homogeneïtat espacial i es trasllada l'anàlisi al sistema viari. Es presenten dues tècniques d'atribució de localitzacions a trams de carrer del graf vial (directa per distància o indirecta a través de les adreces postals), així com la generalització de l'estimació de la densitat d'un espai euclidià a una topologia de xarxa. Fora del context espacial, s'analitzen les interaccions de tres cicles temporals a partir de les metadades del moment en què van ser preses les fotografies: diürn/nocturn (cicle diari), treball/oci (cicle setmanal) i estacional (cicle anual)

Interactive Exploration of Temporal Event Sequences

Life can often be described as a series of events. These events contain rich information that, when put together, can reveal history, expose facts, or lead to discoveries. Therefore, many leading organizations are increasingly collecting databases of event sequences: Electronic Medical Records (EMRs), transportation incident logs, student progress reports, web logs, sports logs, etc. Heavy investments were made in data collection and storage, but difficulties still arise when it comes to making use of the collected data. Analyzing millions of event sequences is a non-trivial task that is gaining more attention and requires better support due to its complex nature. Therefore, I aimed to use information visualization techniques to support exploratory data analysis---an approach to analyzing data to formulate hypotheses worth testing---for event sequences. By working with the domain experts who were analyzing event sequences, I identified two important scenarios that guided my dissertation: First, I explored how to provide an overview of multiple event sequences? Lengthy reports often have an executive summary to provide an overview of the report. Unfortunately, there was no executive summary to provide an overview for event sequences. Therefore, I designed LifeFlow, a compact overview visualization that summarizes multiple event sequences, and interaction techniques that supports users' exploration. Second, I examined how to support users in querying for event sequences when they are uncertain about what they are looking for. To support this task, I developed similarity measures (the M&M measure 1-2) and user interfaces (Similan 1-2) for querying event sequences based on similarity, allowing users to search for event sequences that are similar to the query. After that, I ran a controlled experiment comparing exact match and similarity search interfaces, and learned the advantages and disadvantages of both interfaces. These lessons learned inspired me to develop Flexible Temporal Search (FTS) that combines the benefits of both interfaces. FTS gives confident and countable results, and also ranks results by similarity. I continued to work with domain experts as partners, getting them involved in the iterative design, and constantly using their feedback to guide my research directions. As the research progressed, several short-term user studies were conducted to evaluate particular features of the user interfaces. Both quantitative and qualitative results were reported. To address the limitations of short-term evaluations, I included several multi-dimensional in-depth long-term case studies with domain experts in various fields to evaluate deeper benefits, validate generalizability of the ideas, and demonstrate practicability of this research in non-laboratory environments. The experience from these long-term studies was combined into a set of design guidelines for temporal event sequence exploration. My contributions from this research are LifeFlow, a visualization that compactly displays summaries of multiple event sequences, along with interaction techniques for users' explorations; similarity measures (the M&M measure 1-2) and similarity search interfaces (Similan 1-2) for querying event sequences; Flexible Temporal Search (FTS), a hybrid query approach that combines the benefits of exact match and similarity search; and case study evaluations that results in a process model and a set of design guidelines for temporal event sequence exploration. Finally, this research has revealed new directions for exploring event sequences

Neuroinformatics in Functional Neuroimaging

This Ph.D. thesis proposes methods for information retrieval in functional neuroimaging through automatic computerized authority identification, and searching and cleaning in a neuroscience database. Authorities are found through cocitation analysis of the citation pattern among scientific articles. Based on data from a single scientific journal it is shown that multivariate analyses are able to determine group structure that is interpretable as particular “known ” subgroups in functional neuroimaging. Methods for text analysis are suggested that use a combination of content and links, in the form of the terms in scientific documents and scientific citations, respectively. These included context sensitive author ranking and automatic labeling of axes and groups in connection with multivariate analyses of link data. Talairach foci from the BrainMap ™ database are modeled with conditional probability density models useful for exploratory functional volumes modeling. A further application is shown with conditional outlier detection where abnormal entries in the BrainMap ™ database are spotted using kernel density modeling and the redundancy between anatomical labels and spatial Talairach coordinates. This represents a combination of simple term and spatial modeling. The specific outliers that were found in the BrainMap ™ database constituted among others: Entry errors, errors in the article and unusual terminology

Edge Equalized Treemaps

Abstract-Treemap is a visualization method for hierarchical structures in which nodes are drawn as rectangles and arranged in a nested style. Several variations of Treemap have been developed to represent different types of data. In this paper, we propose an Edge Equalized Treemap, a representation that embeds visual data such as a bar chart in leaf rectangles. This representation is characterized by leaf rectangles of equal widths. Because their widths are equal, the scale intervals of charts in a leaf rectangle can be unified, meaning that we can compare charts simply by looking at them. We compare the Edge Equalized Treemap with existing layout methods, and demonstrate the usefulness of our approach