Fwd: Don't Miss This Week's ASIS&T Webinar: Result Assessment Tool (RAT): An Open-Source Toolkit for Conducting Studies based on Search Results

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Hoda Homavandi

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Jun 16, 2026, 11:15:35 AM (2 days ago) Jun 16

to IranLIS (KIS: Knowledge & Information Science), IranKIS (KIS: Knowledge & Information Science), گروه بحث مشهد‎

با سلام و احترام خدمت اعضای محترم گروه بحث،

وبینارها و رویدادهای پیش روی انجمن علوم و فناوری اطلاعات (ASIS&T)، شرکت برای اعضای انجمن رایگان است.

Best regards,

Hoda Homavandi

PhD in Library & Information Science (information retrieval)

Independent Researcher, IRAN

Chair-Elect Middle East Chapter/ SIG-EduLearn Officer- ASIS&T

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---------- Forwarded message ---------
From: ASIS&T Meetings (Edina McAllister) <meet...@asist.org>
Date: Tue, Jun 16, 2026 at 4:52 PM
Subject: Don't Miss This Week's ASIS&T Webinar: Result Assessment Tool (RAT): An Open-Source Toolkit for Conducting Studies based on Search Results
To: <h.hom...@gmail.com>

RESEARCH ASSESMENT TOOL (RAT): AN OPEN-SOURCE TOOLKIT FOR CONDUCTING STUDIES BASED ON SEARCH RESULTS

June 18, 2026

12:00 PM - 1:00 PM ET

Presenter: Prof. Dr. Dirk Lewandowski & Sebastian Sünkler
Moderator: Dr. Aylin Imeri

Find your time here

REGISTER NOW

Free for ASIS&T members; registration is required.

$25 for non-members

Note: You will not receive the webinar link upon registration. Instead, you will receive an email 24 hours prior and one hour prior to the start time with a link for you to join the webinar. Please register by one hour prior to the start time the day of the webinar to receive the link.

About the Webinar

Conducting research with results from commercial search engines and other web-based information retrieval systems is challenging due to the “black-box” nature of these systems and limited data access. The Result Assessment Tool (RAT) addresses this by providing an integrated software environment that unifies modules for study design, automated data collection, manual assessment in a dedicated interface, and automated analysis via an extensible classifier framework. The software is designed to assist with various research tasks, including comparative assessments of result quality, investigations of source variety, and content analysis. It emphasizes transparency in methodologies, reproducibility of outcomes, and responsible data collection.