Physical Sciences and Mathematics Commons^™

Evaluating And Implementing Web Scale Discovery Services: Part Two, Jason Vaughan, Tamera Hanken

Library Faculty Presentations

Part Four: Quick Tour of the Current Marketplace:

• "The Big 5"
• Similarities and differences

Part Five: It's Not All Sliced Bread:

• Shortcomings of web scale discovery

Part Six: Implementation (pre launch steps):

• Selecting and preparing implementation staff
• Preparing and communicating process/decisions with all staff
• Working with the vendor (roles, expectations, timeline)
• Workflow changes and implications (technical services)

Part Seven: Specific implementation tasks, issues, and considerations:

• Record loading and mapping (catalog content)
• Harvesting and mapping digital/local content
• Working with central index data (internal & external content)
• Web integration and customization
• Assessment and continuous improvement

Evaluating And Implementing Web Scale Discovery Services: Part One, Jason Vaughan, Tamera Hanken

Library Faculty Presentations

Preface: Before Web Scale Discovery

• A very brief overview

Part 1: What is Web Scale Discovery

• Content
• Technology

Part 2: Why is Web Scale Discovery important?

• What’s the need?
• How is it different from earlier attempts at broad discovery?

Part 3: A Framework for Evaluating Web Scale Discovery Services

• What we did at UNLV
• Other options

Finding Haystacks With Needles: Ranked Search For Data Using Geospatial And Temporal Characteristics, Veronika Margaret Megler, David Maier

Computer Science Faculty Publications and Presentations

The past decade has seen an explosion in the number and types of environmental sensors deployed, many of which provide a continuous stream of observations. Each individual observation consists of one or more sensor measurements, a geographic location, and a time. With billions of historical observations stored in diverse databases and in thousands of datasets, scientists have difficulty finding relevant observations. We present an approach that creates consistent geospatial-temporal metadata from large repositories of diverse data by blending curated and automated extracts. We describe a novel query method over this metadata that returns ranked search results to a query with …