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On July 17, 2024 at 11:59:51 AM UTC, Samer Sakor:
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4 | "author": "Harry Li", | 4 | "author": "Harry Li", | ||
5 | "author_email": "harry.li@ll.mit.edu", | 5 | "author_email": "harry.li@ll.mit.edu", | ||
6 | "citation": [ | 6 | "citation": [ | ||
7 | "https://doi.org/10.1109/TVCG.2023.3326904" | 7 | "https://doi.org/10.1109/TVCG.2023.3326904" | ||
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14 | "doi_publisher": "TIB", | 14 | "doi_publisher": "TIB", | ||
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17 | "end_date": "", | 17 | "end_date": "", | ||
18 | "extra_authors": [ | 18 | "extra_authors": [ | ||
19 | { | 19 | { | ||
20 | "extra_author": "Gabriel Appleby", | 20 | "extra_author": "Gabriel Appleby", | ||
21 | "orcid": "https://orcid.org/0000-0003-2436-2121" | 21 | "orcid": "https://orcid.org/0000-0003-2436-2121" | ||
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39 | "https://ieeexplore.ieee.org/document/10360419/authors#authors", | 39 | "https://ieeexplore.ieee.org/document/10360419/authors#authors", | ||
40 | "language": "English", | 40 | "language": "English", | ||
41 | "license_id": "notspecified", | 41 | "license_id": "notspecified", | ||
42 | "license_title": "License not specified", | 42 | "license_title": "License not specified", | ||
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46 | "metadata_created": "2024-07-17T11:56:38.063756", | 46 | "metadata_created": "2024-07-17T11:56:38.063756", | ||
47 | "metadata_modified": "2024-07-17T11:59:51.211415", | 47 | "metadata_modified": "2024-07-17T11:59:51.211415", | ||
48 | "name": | 48 | "name": | ||
49 | haracterizing-their-users-challenges-and-visualization-opportunities", | 49 | haracterizing-their-users-challenges-and-visualization-opportunities", | ||
50 | "notes": "This study presents insights from interviews with nineteen | 50 | "notes": "This study presents insights from interviews with nineteen | ||
51 | Knowledge Graph (KG) practitioners who work in both enterprise and | 51 | Knowledge Graph (KG) practitioners who work in both enterprise and | ||
52 | academic settings on a wide variety of use cases. Through this study, | 52 | academic settings on a wide variety of use cases. Through this study, | ||
53 | we identify critical challenges experienced by KG practitioners when | 53 | we identify critical challenges experienced by KG practitioners when | ||
54 | creating, exploring, and analyzing KGs that could be alleviated | 54 | creating, exploring, and analyzing KGs that could be alleviated | ||
55 | through visualization design. Our findings reveal three major personas | 55 | through visualization design. Our findings reveal three major personas | ||
56 | among KG practitioners \u2013 KG Builders, Analysts, and Consumers | 56 | among KG practitioners \u2013 KG Builders, Analysts, and Consumers | ||
57 | \u2013 each of whom have their own distinct expertise and needs. We | 57 | \u2013 each of whom have their own distinct expertise and needs. We | ||
58 | discover that KG Builders would benefit from schema enforcers, while | 58 | discover that KG Builders would benefit from schema enforcers, while | ||
59 | KG Analysts need customizable query builders that provide interim | 59 | KG Analysts need customizable query builders that provide interim | ||
60 | query results. For KG Consumers, we identify a lack of efficacy for | 60 | query results. For KG Consumers, we identify a lack of efficacy for | ||
61 | node-link diagrams, and the need for tailored domain-specific | 61 | node-link diagrams, and the need for tailored domain-specific | ||
62 | visualizations to promote KG adoption and comprehension. Lastly, we | 62 | visualizations to promote KG adoption and comprehension. Lastly, we | ||
63 | find that implementing KGs effectively in practice requires both | 63 | find that implementing KGs effectively in practice requires both | ||
64 | technical and social solutions that are not addressed with current | 64 | technical and social solutions that are not addressed with current | ||
65 | tools, technologies, and collaborative workflows. From the analysis of | 65 | tools, technologies, and collaborative workflows. From the analysis of | ||
66 | our interviews, we distill several visualization research directions | 66 | our interviews, we distill several visualization research directions | ||
67 | to improve KG usability, including knowledge cards that balance | 67 | to improve KG usability, including knowledge cards that balance | ||
68 | digestibility and discoverability, timeline views to track temporal | 68 | digestibility and discoverability, timeline views to track temporal | ||
69 | changes, interfaces that support organic discovery, and semantic | 69 | changes, interfaces that support organic discovery, and semantic | ||
70 | explanations for AI and machine learning predictions.", | 70 | explanations for AI and machine learning predictions.", | ||
71 | "num_resources": 1, | 71 | "num_resources": 1, | ||
72 | "num_tags": 0, | 72 | "num_tags": 0, | ||
73 | "orcid": "https://orcid.org/0000-0002-2288-6039", | 73 | "orcid": "https://orcid.org/0000-0002-2288-6039", | ||
74 | "organization": { | 74 | "organization": { | ||
75 | "approval_status": "approved", | 75 | "approval_status": "approved", | ||
76 | "created": "2017-11-23T17:30:37.757128", | 76 | "created": "2017-11-23T17:30:37.757128", | ||
77 | "description": "The German National Library of Science and | 77 | "description": "The German National Library of Science and | ||
78 | Technology, abbreviated TIB, is the national library of the Federal | 78 | Technology, abbreviated TIB, is the national library of the Federal | ||
79 | Republic of Germany for all fields of engineering, technology, and the | 79 | Republic of Germany for all fields of engineering, technology, and the | ||
80 | natural sciences.", | 80 | natural sciences.", | ||
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83 | 3conf/ext/tib_tmpl_bootstrap/Resources/Public/images/TIB_Logo_en.png", | 83 | 3conf/ext/tib_tmpl_bootstrap/Resources/Public/images/TIB_Logo_en.png", | ||
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99 | "auto_update_url": "https://github.com/TuftsVALT/KGsInPractice", | 99 | "auto_update_url": "https://github.com/TuftsVALT/KGsInPractice", | ||
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102 | "created": "2024-07-17T11:59:51.024576", | 102 | "created": "2024-07-17T11:59:51.024576", | ||
103 | "description": "The interview codebook", | 103 | "description": "The interview codebook", | ||
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129 | "state": "draft", | 129 | "state": "draft", | ||
130 | "tags": [], | 130 | "tags": [], | ||
131 | "temporal_resolution": "", | 131 | "temporal_resolution": "", | ||
132 | "title": "Knowledge Graphs in Practice: Characterizing their Users, | 132 | "title": "Knowledge Graphs in Practice: Characterizing their Users, | ||
133 | Challenges, and Visualization Opportunities", | 133 | Challenges, and Visualization Opportunities", | ||
134 | "type": "dataset", | 134 | "type": "dataset", | ||
135 | "url": | 135 | "url": | ||
136 | "https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10360419", | 136 | "https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10360419", | ||
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139 | } | 139 | } |