Task Oriented Data Exploration with Human-in-the-Loop. A Data Center Migration Use Case
| Autor: | Steve Welch, Alfredo Alba, Anna Lisa Gentile, Linda Kato, Kau Chris, Deluca Chad, Daniel Gruhl, Petar Ristoski |
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| Rok vydání: | 2019 |
| Předmět: |
Data exploration
business.industry Computer science media_common.quotation_subject computer.software_genre Task (project management) Subject-matter expert Virtual machine Human–computer interaction Node (computer science) Human-in-the-loop Graph (abstract data type) Data center Function (engineering) business computer media_common |
| Zdroj: | WWW (Companion Volume) |
| Popis: | Data exploration is a task that inherently requires high human interaction. The subject matter expert looks at the data to identify a hypothesis, potential questions, and where to look for answers in the data. Virtually all data exploration scenarios can benefit from a tight human-in-the-loop paradigm, where data can be visualized and reshaped, but also augmented with missing semantic information - that the subject matter expert can supplement in itinere. In this demo we show a novel graph-based data exploration model where the subject matter expert can annotate and maneuver the data to answer specific questions. This demo specifically focuses on the task of migrating data centers, logically and/or physically, where the subject matter expert needs to identify the function of each node - a server, a virtual machine, a printer, etc - in the data center, which is not necessarily directly available in the data and to be able to plan a safe switch-off and relocation of a cluster of nodes. We show how the novel human-in-the-loop data exploration and enrichment paradigm helps designing the data center migration plan. |
| Databáze: | OpenAIRE |
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