{"_buckets": {"deposit": "157152c4-3e70-4bf9-a235-d914a5dab167"}, "_deposit": {"created_by": 1, "id": "789", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "789"}, "status": "published"}, "_oai": {"id": "oai:ir.soken.ac.jp:00000789", "sets": ["17"]}, "author_link": ["0", "0", "0"], "item_1_biblio_info_21": {"attribute_name": "書誌情報（ソート用）", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2008-03-19", "bibliographicIssueDateType": "Issued"}, "bibliographic_titles": [{}]}]}, "item_1_creator_2": {"attribute_name": "著者名", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "本多, 啓介"}], "nameIdentifiers": [{"nameIdentifier": "0", "nameIdentifierScheme": "WEKO"}]}]}, "item_1_creator_3": {"attribute_name": "フリガナ", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "ホンダ, ケイスケ"}], "nameIdentifiers": [{"nameIdentifier": "0", "nameIdentifierScheme": "WEKO"}]}]}, "item_1_date_granted_11": {"attribute_name": "学位授与年月日", "attribute_value_mlt": [{"subitem_dategranted": "2008-03-19"}]}, "item_1_degree_grantor_5": {"attribute_name": "学位授与機関", "attribute_value_mlt": [{"subitem_degreegrantor": [{"subitem_degreegrantor_name": "総合研究大学院大学"}]}]}, "item_1_degree_name_6": {"attribute_name": "学位名", "attribute_value_mlt": [{"subitem_degreename": "博士（学術）"}]}, "item_1_description_1": {"attribute_name": "ID", "attribute_value_mlt": [{"subitem_description": "2008043", "subitem_description_type": "Other"}]}, "item_1_description_12": {"attribute_name": "要旨", "attribute_value_mlt": [{"subitem_description": "　　The three dimensional parallel coordinate plot (3-D PCP) is a visualization method \u003cbr /\u003e to detect hidden information in data by using human spatial perception. The 3-D PCP \u003cbr /\u003e proposed in this dissertation can display several characteristics of multiple variables \u003cbr /\u003e simultaneously. First, it can show all the information of each observation at a glance. \u003cbr /\u003e Second, it can make some non-linear structures in data clear. Finally, it is useful to \u003cbr /\u003e find piecewise linear relationships of variables and their conditions. \u003cbr /\u003e　　The basic idea of the 3-D PCP has already appeared in the parallel coordinate plot. \u003cbr /\u003e The parallel coordinate plot can visualize multi dimensional data on a two dimensional \u003cbr /\u003e plane. Coordinates of all variables are set in parallel. In the standard form of parallel \u003cbr /\u003e coordinate plot the bottom position of each axis corresponds to the minimum value of \u003cbr /\u003e each variable, and the top to the maximum value. One observation corresponds to one \u003cbr /\u003e set of connected lines. Parallel coordinate plot can shows the characteristic between \u003cbr /\u003etwo adjoining axes of variables directly. If two variables have a correlation coefficient \u003cbr /\u003eof 1, lines expressing observations are located horizontally. If two variables have \u003cbr /\u003ecorrelation coefficient -l, lines of them cross in one point in the middle between two \u003cbr /\u003eaxes. \u003cbr /\u003e　　However, relations between two variables whose positions are apart more than two \u003cbr /\u003eaxes are not clearly shown immediately. Another serious problem of static parallel \u003cbr /\u003ecoordinate plot is that it is not easy to distinguish one observation from another when \u003cbr /\u003ethe number of observations is large. To solve these problems, several interactive \u003cbr /\u003etechniques have been developed including highlighting by brushing operations. The \u003cbr /\u003e3-D PCP can show the same effect as the highlighting by brushing operation in a \u003cbr /\u003eparallel coordinate plot by extending it into 3-dimensional space. We choose one \u003cbr /\u003evariable as a reference variable, usually a response variable. The 3-D PCP places \u003cbr /\u003econnected lines expressing observations in 3-dimensional spaces by sorting them \u003cbr /\u003eaccording to the values of the reference variable. This observation-wise 3-D PCP \u003cbr /\u003erepresentation is useful for illustrating the characteristics of observations such as \u003cbr /\u003eoutliers. \u003cbr /\u003e　　The 3-D PCP has another representation in which values of observations on each \u003cbr /\u003evariable are connected by lines. It is called variable-wise connection representation \u003cbr /\u003eand is useful to see relations between the reference variable and other variables. For \u003cbr /\u003eexample, the connected lines expressing the variable which has strong linear \u003cbr /\u003erelationships with the reference variable are located around a straight line expressing \u003cbr /\u003ethe reference variable. It is well known that the scatterplot matrix can show \u003cbr /\u003erelationships between variables clearly. However, if the number of variables is large, \u003cbr /\u003ethe single scatterplot elements become too small to be seen properly. The 3-D PCP can \u003cbr /\u003eshow more variables than a scatterplot matrix. It is sometimes more suitable to show \u003cbr /\u003echaracteristics of data simultaneously than using a static representation of scatterplot \u003cbr /\u003ematrlx. \u003cbr /\u003e　　We note that the 3-D PCP can detect particular non-linear relations, i.e. interaction \u003cbr /\u003eby two variables, through observation-wise connection representation. This \u003cbr /\u003erelationship is detected by the special pattern of the angles of connected lines \u003cbr /\u003eexpressing observations. As explained earlier, a correlation coefficient near 1 or -1 \u003cbr /\u003ebetween two variables whose axes are adjacent produces parallel or crossing patterns \u003cbr /\u003ein parallel coordinate plots. Similar patterns can be detected in 3-D PCP. If we find the \u003cbr /\u003echange of such patterns at specific values of the reference variable, we conclude that \u003cbr /\u003ethe structures of data are different for each region of the reference variables. In such \u003cbr /\u003ecases, it is natural to divide the data into several groups in which the structures have \u003cbr /\u003eno more changes. We propose to draw many 3-D PCPs corresponding to the groups \u003cbr /\u003esimultaneously and use a lattice layout, which places many graphs on a grid. We show \u003cbr /\u003ethat they are useful to identify the interaction between two variables by analyzing \u003cbr /\u003esimulation and real data. \u003cbr /\u003e　　We realize our 3-D PCP by using the Java language. Java has several advantages for \u003cbr /\u003eimplementing modern data visualization methods. It is a pure object oriented \u003cbr /\u003eprogramming language and has well-designed standard graphics libraries which are \u003cbr /\u003euseful to realize 2-D and 3-D graphics and interactive graphical user interfaces. These \u003cbr /\u003elibraries can work as useful components of statistical graphics and be in incorporated \u003cbr /\u003eby using so-called design patterns. Design patterns are suggested solutions to common \u003cbr /\u003eproblems often appearing in object-oriented software development. Our \u003cbr /\u003eimplementation is based on several design patterns for generality and reusability. Our \u003cbr /\u003esoftware enables us to analyze data by utilizing advanced interactive operations given \u003cbr /\u003eby Java. We show that the 3-D PCP and the software are expected to lead to new \u003cbr /\u003eachievements in the field of data visualization. \u003cbr /\u003e　　This dissertation is set out as following. Chapter 1 surveys issues of information \u003cbr /\u003evisualization and basic statistical graphics used in multivariate data visualization \u003cbr /\u003esuch as scatterplot, scatterplot matrix, 3-D scatterplot and parallel coordinate plot. It \u003cbr /\u003ealso discusses dynamic techniques of data visualization and existing software products \u003cbr /\u003efor data visualization such as Mondrian, ParallAX, and GGobi. In Chapter 2, 2-D \u003cbr /\u003eparallel coordinate plots are discussed. Important issues at visual data analysis with \u003cbr /\u003eparallel coordinate pIot are considered. We introduce several existing works for \u003cbr /\u003eextending parallel coordinate plot into 3\u0027dimensional spaces. In Chapter 3, we discuss \u003cbr /\u003eour extension of parallel coordinate plot into 3-dimensional space, and several of its \u003cbr /\u003echaracteristics. We show usefulness of lattice layout to display several 3-D PCP at a \u003cbr /\u003etime in Chapter 4. Chapter 5 analyzes three data sets by using our 3-D PCP. In \u003cbr /\u003eChapter 6, we explain details of our software design. Finally, concluding remarks are \u003cbr /\u003egiven in Chapter 7. \u003cbr /\u003e", "subitem_description_type": "Other"}]}, "item_1_description_7": {"attribute_name": "学位記番号", "attribute_value_mlt": [{"subitem_description": "総研大甲第1150号", "subitem_description_type": "Other"}]}, "item_1_select_14": {"attribute_name": "所蔵", "attribute_value_mlt": [{"subitem_select_item": "有"}]}, "item_1_select_8": {"attribute_name": "研究科", "attribute_value_mlt": [{"subitem_select_item": "複合科学研究科"}]}, "item_1_select_9": {"attribute_name": "専攻", "attribute_value_mlt": [{"subitem_select_item": "15 統計科学専攻"}]}, "item_1_text_10": {"attribute_name": "学位授与年度", "attribute_value_mlt": [{"subitem_text_value": "2007"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "HONDA, Keisuke", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "0", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2016-02-17"}], "displaytype": "simple", "download_preview_message": "", "file_order": 0, "filename": "甲1150_要旨.pdf", "filesize": [{"value": "321.7 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_11", "mimetype": "application/pdf", "size": 321700.0, "url": {"label": "要旨・審査要旨", "url": "https://ir.soken.ac.jp/record/789/files/甲1150_要旨.pdf"}, "version_id": "57279c47-633f-4607-abc4-07e87fc600d0"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "thesis", "resourceuri": "http://purl.org/coar/resource_type/c_46ec"}]}, "item_title": "A 3-Dimensional Extension of Parallel Coordinate Plot", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "A 3-Dimensional Extension of Parallel Coordinate Plot"}, {"subitem_title": "A 3-Dimensional Extension of Parallel Coordinate Plot", "subitem_title_language": "en"}]}, "item_type_id": "1", "owner": "1", "path": ["17"], "permalink_uri": "https://ir.soken.ac.jp/records/789", "pubdate": {"attribute_name": "公開日", "attribute_value": "2010-02-22"}, "publish_date": "2010-02-22", "publish_status": "0", "recid": "789", "relation": {}, "relation_version_is_last": true, "title": ["A 3-Dimensional Extension of Parallel Coordinate Plot"], "weko_shared_id": -1}