UKSG 2023 - #dataSOS: What&#x27;s going on with Library data &amp; what can we do about it?

This document discusses reliance on data in education and calls for more responsibility and ethics regarding data collection and usage. It questions how user data is used by electronic systems and wants publishers/suppliers to be more involved. The document suggests taking action through a cross-sector audit of electronic systems and group work on revising license terms to ensure user rights are protected against intolerable surveillance of activity.

Education

Context
Reliance on data
Scale of collection
Nature of pedagogy
Lack of knowledge

What can we do?
Take responsibility for
systems & agreements
Ethics demand a commitment
to ensure users rights
Push back against
intolerable surveiliance
of activity

Survey
No
No
No
We do not do any
deep dive analysis
Don’t have time
currently
No, we don’t use any
deep dive analytics
No
No
We analyse
concurrency access
levels
Turnaway
stats
Turnawa
y
reports
Standard
COUNTER
section
requests
No No

Survey
No
No, but would
like to
In a rather
haphazard and
inconsistent
way
Number of
downloads
Access on
document level
No
No time to
evaluate
Not at the
moment
Only collect
these
No
No
Deep dive
once a month

Survey
No No
No, no time
No
We use turnaway
data
Turnaways every
so often
Regularly
review
turnaways
Turnaways
Turnaway data Info about
turnaways
Not really
Not
systematically
No, no time

Survey
No
No deep dive analysis
No
Turnaways every
so often
Occasionally,
no staff
time/resources
Trying but no
time
No
No
Standard COUNTER stats
A work in
progress
Yearly
collection
and analysis
Whatever is
available
through
OpenAthens
and EZProxy
data
No

Survey
No No
Yes No
Growing area
Engagement
with reading
lists
Time consuming
to collate and
maintain
Yes
Not really, all a
bit much
Not
currently
but may do
in future
No
Still
working on
collecting
this type
of data

Structural
Imbalance
Affects all e-
resources we
have
Questionable
benefits
Data neutral
systems must be
explored

Key Questions
What actually happens
to our data?
Who uses it?
Where does it go?
How is it monetized?
What value does it
have?

Call to action
Cross sector audit of
electronic systems
Group work on licence
terms
Publishers/supplier
involvement

UKSG 2023 - #dataSOS: What's going on with Library data & what can we do about it?

The document outlines All Children's Hospital Foundation's process of developing a Prospect Management Model (PMM) to better track and manage donor prospects. They realized the need for a PMM to support a large upcoming fundraising campaign. They analyzed their existing data and systems, defined key metrics to track, and built out their database and business intelligence tools. This included developing a "Q Report" to provide a centralized view of key prospect information. The PMM helped increase accountability, projections, and collaboration across teams. Initial results included growth in major gift pledges and portfolio sizes.

Survey Research 101

Sam Ladner

This document provides an overview of online surveys, including what they are, when they are the right research method to use, how to design good survey questions, sampling techniques, analyzing survey results, and the skills needed to conduct surveys. Some key points covered include: surveys involve asking structured questions to summarize opinions in numerical format and generalize to a population; good questions are mutually exclusive, exhaustive, and focus on opinions rather than usability; probability sampling allows for predicting accuracy and generalizing, while non-probability provides some insight; descriptive statistics summarize responses and variation, while inferential statistics predict behavior and influences; and surveys have limitations in explaining reasons and characteristics.

T3 data collecting techniques

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Survey Resaerch

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This document outlines the key aspects of survey research. It defines a survey, explains why surveys are used, and describes the characteristics and steps involved in survey research. It discusses tools for surveys such as interviews and questionnaires. It also covers survey research designs like cross-sectional and longitudinal studies. Finally, it summarizes the strengths and limitations of survey research.

Surveys & Qualitative Data Capture & Analysis

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This document discusses challenges with qualitative and quantitative data collection in school counseling and provides tips for effective use and presentation of data. It addresses: 1) Common types of qualitative data counselors collect and how to code it to find patterns and themes. 2) Potential pitfalls of quantitative data like non-response bias and issues with reliability/validity. 3) Strategies for presenting qualitative and quantitative data together using tools like Sign-Up Genius, Google Forms, Survey Monkey, and mandatory surveys. The goal is to use mixed methods and data to improve counseling programs and services.

CSI: Clinical Site Intelligence

goBalto

This document summarizes a discussion between Christy Gilchrist from Wellspan Health and Todd Tullis from goBalto on using site intelligence and predictive analytics to improve clinical trial feasibility assessments, site selection, startup, and performance evaluation. Some key points discussed include: 1) Using data analysis of electronic health records and epidemiological models to better predict patient enrollment expectations and feasibility at sites. 2) Measuring site and sponsor responsiveness to startup tasks in real-time to facilitate faster resolution of issues. 3) Evaluating site performance against enrollment goals, compliance goals, and business goals to help sites improve for future trials. 4) Sharing post-study performance data with sites to build

Collaborative work part IV DATA COLLECTION INSTRUMENTS

andrevallejo1217

This document discusses selecting appropriate data collection instruments for project evaluations. It provides an overview of various instruments including interviews, focus groups, surveys, observations, tests, concept maps, documents/product reviews, and case studies. It notes the strengths and weaknesses of each instrument and considers what types of audiences and projects each instrument is best suited for. The key aspects to match are the type of information needed, the audience being assessed, and the nature of the project or activity being evaluated. Selecting the right instrument requires understanding these context factors.

This document provides an introduction to quantitative and qualitative research methods. It explains that the research approach chosen depends on the research questions, underlying philosophy, and skills of the researcher. Quantitative research uses numerical data and statistical analysis, while qualitative research uses words and focuses on understanding phenomena. Both have advantages and limitations. The document also discusses research design principles, data sources, analysis techniques, and key aspects to consider for quantitative and qualitative approaches.

Types of data and research

National Information Standards Organization (NISO)

Primary research involves directly collecting new data through methods like surveys and focus groups, but can be time consuming and may not provide accurate results. Secondary research analyzes existing sources like books, newspapers and the internet, making it quicker but risking outdated or incomplete information. Qualitative research focuses on opinions and views through flexible and cheaper methods like interviews, but cannot quantify responses or generalize findings, while quantitative research collects factual data from large randomized samples but requires more funding and planning.

Consider The Evidence Tpu Ti Cs

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This document discusses using data and evidence to make decisions to improve teaching and learning in Teen Parent Units. It considers what data is collected, why, and how it is used. Evidence-driven decision making requires analyzing data to understand patterns and insights that can inform changes to improve student achievement. The document outlines a cycle for evidence-based inquiry including speculating about issues, exploring the evidence, questioning, assembling data, analyzing, intervening, evaluating the impact of changes, and reflecting on lessons learned. Teachers are encouraged to use this process to set goals for improving their practice using an evidence-based approach.

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This document discusses challenges related to curating and providing access to open access collections. It outlines the author's institution's response which involves curating and vetting open access resources using a rubric. Some things that are working well include continued ingestion and discoverability. Areas for improvement include increasing automation for metadata and tracking usage. Going forward, the author proposes fully integrating open access into digital library collections and exploring additional access points, while continuing to focus on metadata and tracking for open access resources.

Data Informed Design - Good Tech Test - May 2018

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When it comes to design, everyone has an opinion! However, during reviews and discussions it’s those with more than an opinion that fair the best. Successful design solutions require a deep understanding of audiences, clear strategy, and good ole data. In this session you’ll learn: - Common data sources for design - How to build a data-informed approach (not data-driven) - What data-informed design looks like in the wild (aka case studies). Whether you’re trying to prove a point, make an improvement, or discover something new, data-informed design moves your team from gut-feelings to fact-based decisions.

Designing Indicators

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The document discusses survey design and data collection. It covers several key topics in 3 sentences or less: 1. What should be measured including characteristics, channels, outcomes and assumptions based on a theory of change. Accurate and precise indicators are important. 2. Methods of data collection such as surveys, qualitative methods, and tests. Good measures are accurate without bias and precise without random error. 3. Challenges in measurement including things people don't know well or want to talk about, abstract concepts, things not directly observable, and things best directly observed through protocols. Data collection requires reliability, validity, integrity, accuracy and timeliness.

How to select the right database to empower your fundraising

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This document provides guidance on selecting and managing a fundraising database. It discusses key considerations when reviewing a new database including staff needs, fundraising goals, functionality requirements, timing, funding, and more. It emphasizes the importance of designating database ownership, keeping data clean, training staff, establishing clear data entry policies and procedures, and generating effective reports. The overall message is that a well-managed database should be a nonprofit's biggest fundraising asset.

MSC III_Research Methodology and Statistics - Data Collection.pdf

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Types of data and research

There are three main types of data for research: primary data, secondary data, and qualitative data. Primary data involves directly collecting information through surveys or questionnaires, but it requires conducting the research yourself. Secondary data analyzes previously collected data, which is quicker and easier to access for free, but the information may not be tailored to your needs or accurate. Qualitative data describes characteristics through flexible interviews with small samples, allowing for depth, but the findings cannot be generalized to larger audiences. Quantitative data involves statistically valid surveys to generalize results to populations, but has limitations in probing answers and potential response biases.

Modern Quality Thoughts About Quality Reviews

CRRC-Armenia

The document discusses modern approaches to quality reviews of statistical organizations. It recommends affirming good work, taking a systems thinking approach, and supporting continuous improvement rather than criticism. Quality reviews should focus on prevention of issues rather than reworking problems. The National Statistics Service of Armenia has done good work but could benefit from more systematic quality improvements through adopting approaches like Kaizen. The reviewer plans to work with local partners to examine both process and quality of work over the coming year and support incremental improvements.

Types of data and research

North Carolina Virtual Public School

Primary research involves directly collecting new data through methods like surveys and interviews, but can be time consuming and may not provide accurate results. Secondary research analyzes existing sources like books, newspapers and the internet, making it easier and faster but risking outdated or incomplete information. Qualitative research focuses on opinions and views through flexible methods like interviews, while quantitative research deals with factual data that requires large sample sizes and funding for statistical generalization.

The five data questions

This document outlines the five key questions that should be answered when analyzing data from courses: 1) What does the data tell us? 2) What doesn't the data tell us? 3) What are the celebrations about the data? 4) What opportunities for improvement does the data allow? 5) Based on the analysis, what are the next steps and timeline? Answering these questions will help ensure a thorough examination of the data from all relevant perspectives.

The Five Data Questions

Cedp 402 assessment lectures

Ryan Sain

This document discusses behavior modification assessment and treatment programs. It covers the following key points: 1) Behavioral assessment focuses on gathering objective data about behaviors rather than suspicions. Baseline data is collected to establish stability before treatment. 2) An intake phase determines if the client is in the right treatment setting and informs them about the program policies. Crisis situations require immediate treatment. 3) Treatment programs are developed based on a functional assessment that identifies the controlling variables influencing problem behaviors. Programs are evaluated based on objective behavior data to determine effectiveness.

The Five Data Questions

The document outlines five questions to consider when analyzing data from courses: 1) What does the data tell you? 2) What does the data not tell you? 3) What are the celebrations about the data? 4) What opportunities for improvement does the data allow? 5) Based on your analysis, what are the next steps and timeline? It provides guidance on focusing the analysis to find both positive and negative trends, missing information, areas for celebration or improvement, and developing an action plan.

Lesson1

MariaAnnBernardino

The document describes characteristics, strengths, and weaknesses of quantitative research. It differentiates types of variables and their uses, and contrasts different kinds of quantitative research. Specifically, it defines quantitative research, explores its characteristics, and examines strengths and weaknesses. It also contrasts quantitative and qualitative research and describes different types of quantitative research designs including descriptive research, correlational research, and experimental research. Finally, it discusses classifications of variables and experimental variables.

Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...

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Dear viewers Check Out my other piece of works at___ https://healthkura.com Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Assessment of Qualitative Data, Qualitative & Quantitative Data, Data Processing Presentation Contents: - Introduction to data - Classification of data - Collection of data - Methods of data collection - Assessment of qualitative data - Processing of data - Editing - Coding - Tabulation - Graphical representation If anyone is really interested about research related topics particularly on data collection, this presentation will be the best reference. For Further Reading - Biostatistics by Prem P. Panta - Fundamentals of Research Methodology and Statistics by Yogesh k. Singh - Research Design by J. W. Creswell - Internet

Presentation final.pptx

komalsharma581366

The document discusses the process of data analysis undertaken by a team to improve employee retention. [1] The analysts first defined goals and gathered data through employee surveys. [2] They then cleaned the data, analyzed it to find key indicators of satisfaction like hiring and feedback processes, and carefully shared results. [3] Recommendations like standardizing processes improved retention rates, showing the analysis was successful.

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CERIFY

Review of Evaluation Methods

ltownson

The document discusses various methods for collecting data for program evaluations, including surveys, interviews, focus groups, tests, observations, rubrics, and document analysis. It provides details on the strengths and limitations of each method with considerations for things like population size, accessibility, costs, and measuring outcomes versus processes. The document encourages selecting multiple methods to increase validity and writing rich impact statements. It includes an exercise for small groups to discuss the best methods for their evaluation and begin filling out an evaluation plan table.

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UKSG 2024 Plenary Session 3 - There is No List: (How) Can We Combat “Predator...

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