2b:null 2c:["$","title",null,{"children":"AuthorNet: Exploring Author Collaborations in IEEE VIS (1990-2023) | Northeastern University John A. Guerra Gomez classes | Observable"}] 31:T491,## Introduction In academia, connections and collaborations are crucial for innovation and growth. Researchers work together, share intellgence, and build on each other’s ideas to push the boundaries of knowledge. However, identifying these collaborative networks—such as which researchers frequently work together or who connects different groups—is not always easy. This kind of information is essential not only for understanding how research communities form but also for helping new researchers find potential collaborators and build their own networks. This project, AuthorNet: Exploring Author Collaborations in IEEE VIS (1990-2023), provides a tool for visualizing and analyzing author co-occurrence within IEEE VIS papers from the past 30 years. It allows users to explore how authors are connected, discover clusters of frequent collaborators, and see how different groups are formed within the field of data visualization. By doing this, AuthorNet acts as a guide to the academic landscape, helping researchers identify collaboration opportunities and recognize influential research groups, and gain insights into how collaborations shape the field. 32:T501,## Table of Contents * [Real insights](https://observablehq.com/d/b7fa9181a2c6279c#cell-669) * [Target audience](https://observablehq.com/d/b7fa9181a2c6279c#cell-547) * [Task abstraction](https://observablehq.com/d/b7fa9181a2c6279c#cell-553) * [Example made-up insights (Hypothesis) and considerations](https://observablehq.com/d/b7fa9181a2c6279c#cell-560) * [Tasks](https://observablehq.com/d/b7fa9181a2c6279c#cell-583) * [How abstraction](https://observablehq.com/d/b7fa9181a2c6279c#cell-555) * [Data Abstraction](https://observablehq.com/d/b7fa9181a2c6279c#cell-405) * [Data source](https://observablehq.com/d/b7fa9181a2c6279c#cell-487) * [Dataset discription](https://observablehq.com/d/b7fa9181a2c6279c#cell-494) * [Overview of data using Navio](https://observablehq.com/d/b7fa9181a2c6279c#cell-411) * [Data availability](https://observablehq.com/d/b7fa9181a2c6279c#cell-529) * [Attributes Used](https://observablehq.com/d/b7fa9181a2c6279c#cell-531) * [Data processing](https://observablehq.com/d/b7fa9181a2c6279c#cell-141) * [Appendix: The public libraries used in this project](https://observablehq.com/d/b7fa9181a2c6279c#cell-413) * [tweet](https://x.com/cherryflaneur/status/1855396807574274087) & [video](https://youtu.be/LP-LZ3sXyM0) explaining the project33:T45d,### 1.1 Example made-up insights (Hypothesis) and considerations * Authors from fields like computer science, psychology, and cognitive science are more likely to collaborate on research topics related to human-computer interaction within data visualization. * Considerations * I would need data on each author’s research area, especially in fields like computer science, psychology, and cognitive science. * Additionally, I would need data on each publication by topic. * For the Idiom, I need to build a network showing author co-occurrence in IEEE VIS papers within the fields mentioned above.

* [Selected] Two close collaborators may each have their own separate collaboration circles, and these circles might not intersect with each other. * Considerations * I would need data on the frequency of collaborations between authors to determine the strength of each connection. * For the visualization, I need to build a network showing the strength of author connections, with edges weighted by the number of collaborations to highlight stronger partnerships.34:[{"id":"37776b748b7dcfd4bd1996a63ff03e9a7540f6bd437b5b9633116320082566ea9638cfb2600e78a8568485a5e41aa3fff49ba24061ae126331eac9c47763260a","href":"https://static.observableusercontent.com/files/37776b748b7dcfd4bd1996a63ff03e9a7540f6bd437b5b9633116320082566ea9638cfb2600e78a8568485a5e41aa3fff49ba24061ae126331eac9c47763260a","name":"11.png","type":"image/png","lastModified":1731193141370.699,"size":186053},{"id":"360e7061424f3ca31b3f3eab61654e82a929c6ef1de87946f3f72530b83c1d92126db0d26b5133faf78fd6e63d27f24b23cf61f84b1f8befc10f2d88122e375b","href":"https://static.observableusercontent.com/files/360e7061424f3ca31b3f3eab61654e82a929c6ef1de87946f3f72530b83c1d92126db0d26b5133faf78fd6e63d27f24b23cf61f84b1f8befc10f2d88122e375b","name":"IEEE_VIS_papers_Main dataset@1.csv","type":"text/csv","lastModified":1730971608635.534,"size":6767296}] 2f:{"id":"b7fa9181a2c6279c","slug":null,"title":"AuthorNet: Exploring Author Collaborations in IEEE VIS (1990-2023)","thumbnail":"483c89910c1a2cdfc271b3efee2367f3d9e037e2cd38db99d851d16fb6bc58b7","access_level":"public","create_time":"$D2024-11-07T06:55:36.085Z","update_time":"$D2024-11-23T02:30:27.530Z","view_time":null,"first_public_time":"$D2024-11-08T00:49:24.595Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"afbaa6d30585fd36","login":"nujguerra","name":"Northeastern University John A. 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Guerra Gomez classes","avatar_url":"https://avatars-next.observableusercontent.com/04e5ef72b3edcda1296894b5d1ecaa9c92ef5d52d69e65e4c115de5534928fe9","tier":"education_2026","role":"viewer"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"AuthorNet: Exploring Author Collaborations in IEEE VIS (1990-2023)","cells":[{"id":0,"value":"# AuthorNet: Exploring Author Collaborations in IEEE VIS (1990-2023)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":137,"value":"This is a data visuzalization project made by [Shufan Chai](https://observablehq.com/user/@shufan-chai) from Northeastern University for the course [CS7295: Information Visualization](https://johnguerra.co/classes/data_visualization_fall_2024/) Fall 2024 under [Professor John Alexis Guerra Gomez](https://johnguerra.co/).\n ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":272,"value":"viewof selectedAuthors = searchCheckbox(authorNames, {label: \"Select authors\", value: [\"Ben Shneiderman\"], height: 100})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":541,"value":"##### Note: Check and uncheck boxes to include/exclude authors","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":96,"value":"viewof networkChart = ForceGraph(network, {\n nodeRadius: 5,\n nodeStrength: -200,\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":402,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":680,"value":"$32","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":669,"value":"## Real insights\nTwo authors who frequently collaborate with each other may still maintain their own distinct collaboration circles, each consisting of other co-authors with whom they work regularly. These individual collaboration networks can remain largely separate, with little or no overlap between them. This suggests that even within a tightly connected academic community, authors often have unique, specialized networks that do not intersect. Such a pattern reveals specialized subgroups or research niches within a larger field, where certain collaborators are central to their own circle but do not collaborate extensively outside of it.\n\nSee the example below:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":673,"value":"untitled = FileAttachment(\"11.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":547,"value":"## Target audience\n* For early-career researchers, finding the right collaborators can be difficult. AuthorNet provides a clear view of existing networks, making it easier for newcomers to identify researchers with similar interests and potentially start collaborations.\n* Experienced researchers can use AuthorNet to see their place within the network and find potential collaborators who bring complementary skills. By connecting with new groups, they can expand their reach and influence in their research area.\n* For institutions and funding bodies, understanding collaboration networks is valuable for promoting impactful research. AuthorNet helps identify key research groups and collaboration patterns, which can inform strategic planning and resource allocation to support productive partnerships.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":553,"value":"## 1. Task abstraction\n ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":560,"value":"$33","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":583,"value":"### 1.2 Tasks\nT1: Identify the primary collaborators for each author within the network. (Identify, topology)\n * T1.1: Compare the structure of collaboration circles around closely connected authors to see if they overlap or remain separate. (Compare, topology)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":555,"value":"## 2. How abstraction\n* Marks: Point, Line\n* Channel:\n * Position: Each node’s position reflects its connections with other nodes, allowing users to quickly perceive clusters and separate collaboration groups.\n * Expressiveness: This spatial arrangement allows viewers to immediately understand which authors are closely connected and which form separate groups.\n * Effectiveness: Position allows viewers to immediately recognize patterns, clusters, and relative distances between nodes, helping identify which authors are closely connected and which are in isolated clusters.\n ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":405,"value":"## 3. Data Abstraction","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":487,"value":"### 3.1 Data source\nLink to the dataset: https://sites.google.com/site/vispubdata/home?pli=1\n\nThis is a Visualization publications dataset that contains information on IEEE Visualization (IEEE VIS) publications from 1990-2023 as well as IEEE TVCG and IEEE CG&A article published at IEEE VIS. \n\nThe dataset has three tabs: Main Dataset, Journal Papers Presented at VIS, and Paper Numbers and Acceptance Rates. This project only uses the Main Dataset.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":494,"value":"### 3.2 Dataset discription\nThe original dataset is a Table, and it was converted to a Network for the visualization. See the network and table below.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":520,"value":"#### 3.2.1 Network","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":246,"value":"network","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":523,"value":"#### 3.2.2 Table","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":500,"value":"data","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":411,"value":"### 3.3 Overview of data using Navio\nNavio is a data exploration widget created by [Professor John Alexis Guerra Gomez](https://observablehq.com/@john-guerra/navio), which you can use to explore the dataset.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":13,"value":"viewof selectedData = navio(data)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":529,"value":"### 3.4 Data availability\nStatic","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":531,"value":"### 3.5 Attributes Used - The attributes were converted to nodes and links\n* AuthorNames_Deduped (Categorical attribute): The authors who published the paper.\n* Count (Quantitative attribute, derived attribute): The number of collaborations between two authors. This attribute is used to link authors if they published the paper together.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":141,"value":"## 4. Data processing\nThis process used D3.js to manipulate the original tabel dataset and derive the network for visualization. Below is the step-by-step process.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":287,"value":"authorNames = dataUnrolled\n .groupby(\"fromList\")\n .count()\n .filter((d) => d.count > 1)\n .objects()\n .map((d) => d.fromList)\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"viewof dataUnrolled = aq\n .from(data)\n .select([\"Title\", \"DOI\", \"AuthorNames_Deduped\"])\n .derive({\n fromList: (d) => op.split(d.AuthorNames_Deduped, \";\"),\n toList: (d) => op.split(d.AuthorNames_Deduped, \";\")\n })\n .unroll(\"fromList\")\n .unroll(\"toList\")\n.view();\n","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":284,"value":"viewof dataUnrolledSampled = dataUnrolled\n .filter(\n aq.escape(\n (d) =>\n selectedAuthors.includes(d.fromList) ||\n selectedAuthors.includes(d.toList)\n )\n )\n .view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":52,"value":"### Create links","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":46,"value":"viewof groupedAuthor = dataUnrolledSampled\n .join(dataUnrolledSampled, (a, b) => op.equal(a.DOI, b.DOI))\n .groupby([\"fromList_1\",\"toList_2\"])\n .rollup({\n count: d => op.distinct(d.DOI_1)\n })\n .rename({\"fromList_1\": \"source\", \"toList_2\": \"target\"})\n .view()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":62,"value":"groupedAuthor.groupby(\"source\").count().objects().map(d => d.source)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":68,"value":"### Get the targets","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":70,"value":"groupedAuthor.groupby(\"target\").count().objects().map(d => d.target)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":74,"value":"### Get the nodes","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":76,"value":"nodes = [\n ...new Set(\n groupedAuthor\n .groupby(\"source\")\n .count()\n .objects()\n .map((d) => d.source)\n .concat(\n groupedAuthor\n .groupby(\"target\")\n .count()\n .objects()\n .map((d) => d.target)\n )\n )\n].map((d) => ({ id: d }))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":55,"value":"### Create network","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":57,"value":"network = ({\n nodes: nodes,\n links: groupedAuthor.objects()\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"network.nodes","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":133,"value":"network.links","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"data = FileAttachment(\"IEEE_VIS_papers_Main dataset@1.csv\").csv()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"d3 = require(\"d3@6\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":413,"value":"## Appendix: The public libraries used in this project","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":7,"value":"import { navio } from \"@john-guerra/navio\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"import {aq, op} from \"@uwdata/arquero\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":87,"value":"import {ForceGraph} from \"@john-guerra/force-directed-graph\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":312,"value":"import {searchCheckbox} from \"@john-guerra/search-checkbox\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W34","stdlib":"1"}} 30:"$2f:body"