The Biology Semester-long Course was developed and piloted at the University of …
The Biology Semester-long Course was developed and piloted at the University of Florida in Fall 2015. Course materials include readings, lectures, exercises, and assignments that expand on the material presented at workshops focusing on SQL and R.
A part of the data workflow is preparing the data for analysis. …
A part of the data workflow is preparing the data for analysis. Some of this involves data cleaning, where errors in the data are identified and corrected or formatting made consistent. This step must be taken with the same care and attention to reproducibility as the analysis. OpenRefine (formerly Google Refine) is a powerful free and open source tool for working with messy data: cleaning it and transforming it from one format into another. This lesson will teach you to use OpenRefine to effectively clean and format data and automatically track any changes that you make. Many people comment that this tool saves them literally months of work trying to make these edits by hand.
The A2DataDive assembled representatives from nonprofit organizations, U-M statistics and data sciences …
The A2DataDive assembled representatives from nonprofit organizations, U-M statistics and data sciences departments, and members of the community to collectively address the data analysis and visualization needs for area nonprofits and local organizations. Open.Michigan was one of the organizers of the A2DataDive, and worked with two School of Information graduate students to scope and implement the event. After identifying two organizations who had data needs:ŰÖFocus HopeŰÖand theŰÖAfrican Health OER Network, this joint community/university datadive took place over a weekend in February 2012 in North Quads space 2435, an adaptable space especially suited to collaborative, participatory work. The A2DataDive was a successful proof-of-concept for a joint collaboration between an academic institution and local organizations and businesses, and demonstrated that sharing skills and expertise to address a need is also a great way to help others.
Databases are useful for both storing and using data effectively. Using a …
Databases are useful for both storing and using data effectively. Using a relational database serves several purposes. It keeps your data separate from your analysis. This means there’s no risk of accidentally changing data when you analyze it. If we get new data we can rerun a query to find all the data that meets certain criteria. It’s fast, even for large amounts of data. It improves quality control of data entry (type constraints and use of forms in Access, Filemaker, etc.) The concepts of relational database querying are core to understanding how to do similar things using programming languages such as R or Python. This lesson will teach you what relational databases are, how you can load data into them and how you can query databases to extract just the information that you need.
This is an alpha lesson to teach Data Management with SQL for …
This is an alpha lesson to teach Data Management with SQL for Social Scientists, We welcome and criticism, or error; and will take your feedback into account to improve both the presentation and the content. Databases are useful for both storing and using data effectively. Using a relational database serves several purposes. It keeps your data separate from your analysis. This means there’s no risk of accidentally changing data when you analyze it. If we get new data we can rerun a query to find all the data that meets certain criteria. It’s fast, even for large amounts of data. It improves quality control of data entry (type constraints and use of forms in Access, Filemaker, etc.) The concepts of relational database querying are core to understanding how to do similar things using programming languages such as R or Python. This lesson will teach you what relational databases are, how you can load data into them and how you can query databases to extract just the information that you need.
Good data organization is the foundation of any research project. Most researchers …
Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it’s the place that many research projects start. We organize data in spreadsheets in the ways that we as humans want to work with the data, but computers require that data be organized in particular ways. In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. Since this is where most research projects start, this is where we want to start too! In this lesson, you will learn: Good data entry practices - formatting data tables in spreadsheets How to avoid common formatting mistakes Approaches for handling dates in spreadsheets Basic quality control and data manipulation in spreadsheets Exporting data from spreadsheets In this lesson, however, you will not learn about data analysis with spreadsheets. Much of your time as a researcher will be spent in the initial ‘data wrangling’ stage, where you need to organize the data to perform a proper analysis later. It’s not the most fun, but it is necessary. In this lesson you will learn how to think about data organization and some practices for more effective data wrangling. With this approach you can better format current data and plan new data collection so less data wrangling is needed.
Data Carpentry lesson to learn how to use command-line tools to perform …
Data Carpentry lesson to learn how to use command-line tools to perform quality control, align reads to a reference genome, and identify and visualize between-sample variation. A lot of genomics analysis is done using command-line tools for three reasons: 1) you will often be working with a large number of files, and working through the command-line rather than through a graphical user interface (GUI) allows you to automate repetitive tasks, 2) you will often need more compute power than is available on your personal computer, and connecting to and interacting with remote computers requires a command-line interface, and 3) you will often need to customize your analyses, and command-line tools often enable more customization than the corresponding GUI tools (if in fact a GUI tool even exists). In a previous lesson, you learned how to use the bash shell to interact with your computer through a command line interface. In this lesson, you will be applying this new knowledge to carry out a common genomics workflow - identifying variants among sequencing samples taken from multiple individuals within a population. We will be starting with a set of sequenced reads (.fastq files), performing some quality control steps, aligning those reads to a reference genome, and ending by identifying and visualizing variations among these samples. As you progress through this lesson, keep in mind that, even if you aren’t going to be doing this same workflow in your research, you will be learning some very important lessons about using command-line bioinformatic tools. What you learn here will enable you to use a variety of bioinformatic tools with confidence and greatly enhance your research efficiency and productivity.
This workbook is a brief introduction to data wrangling. In this book, …
This workbook is a brief introduction to data wrangling. In this book, we introduce core concepts in data wrangling, use the R language, the R Studio interface, and the tidyverse set of packages that are dedicated to getting us to tidy data.
This resource will be updated as needed. For the most recent version, visit: https://cod.pressbooks.pub/datawranglingwithr/
Database Design - 2nd Edition covers database systems and database design concepts. …
Database Design - 2nd Edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, key terms and review exercises at the end of each chapter.
Software Carpentry lesson that teaches how to use databases and SQL In …
Software Carpentry lesson that teaches how to use databases and SQL In the late 1920s and early 1930s, William Dyer, Frank Pabodie, and Valentina Roerich led expeditions to the Pole of Inaccessibility in the South Pacific, and then onward to Antarctica. Two years ago, their expeditions were found in a storage locker at Miskatonic University. We have scanned and OCR the data they contain, and we now want to store that information in a way that will make search and analysis easy. Three common options for storage are text files, spreadsheets, and databases. Text files are easiest to create, and work well with version control, but then we would have to build search and analysis tools ourselves. Spreadsheets are good for doing simple analyses, but they don’t handle large or complex data sets well. Databases, however, include powerful tools for search and analysis, and can handle large, complex data sets. These lessons will show how to use a database to explore the expeditions’ data.
A number of publishers and funders, including PLOS, have recently adopted policies …
A number of publishers and funders, including PLOS, have recently adopted policies requiring researchers to share the data underlying their results and publications. Such policies help increase the reproducibility of the published literature, as well as make a larger body of data available for reuse and re-analysis. In this study, we evaluate the extent to which authors have complied with this policy by analyzing Data Availability Statements from 47,593 papers published in PLOS ONE between March 2014 (when the policy went into effect) and May 2016. Our analysis shows that compliance with the policy has increased, with a significant decline over time in papers that did not include a Data Availability Statement. However, only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy. These findings suggest that additional review of Data Availability Statements or more stringent policies may be needed to increase data sharing.
Review how the decimal number system works before diving into the binary …
Review how the decimal number system works before diving into the binary number system. The decimal number system and binary number system work the same way; the only difference is what each digit represents (0-9 versus 0/1). Created by Pamela Fox.
This video explains the design of the Arecibo Message transmitted in the …
This video explains the design of the Arecibo Message transmitted in the 1970s by SETI pioneers. It explains why humans sent the message and who they hope might receive it. It shows the telescope in Brasil. It plays the audio signal from the message that was sent and shows how that signal can be converted to binary to show an image. It also gives a brief overview of how the binary number system works.
Pharo is a clean, innovative, open-source, live-programming environment. Deep into Pharois the …
Pharo is a clean, innovative, open-source, live-programming environment.
Deep into Pharois the second volume of a series of books covering Pharo. Whereas the first volume is intended for newcomers, this second volume covers deeper topics.You will learn about Pharo frameworks and libraries such as Glamour, PetitParser, Roassal, FileSystem, Regex, and Socket.
You will explore the language with chapters on exceptions, blocks, small integers, and floats.
You will discover tools such as profilers, Metacello and Gofer.
Defend Dissent is an introduction to cryptography paired with the social impacts …
Defend Dissent is an introduction to cryptography paired with the social impacts of surveillance and the protective potential of encryption, with a focus on US social movements. Each chapter ends with a story that brings social context to the material—from surveillance used against contemporary US protests to the African National Congress’s use of partially manual encryption in fighting apartheid in South Africa in the 80s.
This book can be read linearly, or you can pick and choose what you would like to learn about. Each chapter is prefaced with what you should read first (for background) and concludes with what you might want to read next.
The design of concurrent distributed hardware systems is a major challenge for …
The design of concurrent distributed hardware systems is a major challenge for engineers today and is bound to escalate in the future, but engineering education continues to emphasize traditional tools of logic design that are just not up to the job. For engineers tackling realistic projects, improvised attempts at synchronization across multiple clock domains have long been a fact of life. Prone to hazards and metastability, these ad hoc interfaces could well be the least trustworthy aspects of a system, and typically also the least able to benefit from any readily familiar textbook techniques of analysis or verification.
Progress in the long run depends on a change of tactics. Instead of the customary but inevitably losing battle to describe complex systems in terms of their stepwise time evolution, taking their causal relationships and handshaking protocols as a starting point cuts to the chase by putting the emphasis where it belongs. This way of thinking may call for setting aside a hard earned legacy of practice and experience, but it leads ultimately to a more robust and scalable methodology.
Delay insensitive circuits rely on local coordination and control from the ground up. The most remarkable consequence of adhering to this course is that circuits can get useful things done without any clock distribution network whatsoever. Because a handshake acknowledgment concludes each interaction among primitive components and higher level subsystems alike, a clock pulse to mark them would be superfluous. This effect can bring a welcome relief to projects whose timing infrastructure would otherwise tend to create more problems than it solves.
The theory of delay insensitive circuits is not new but has not yet attracted much attention outside of its research community. At best ignored and at worst discouraged in standard curricula, this topic until now has been accessible only by navigating a sea of conference papers and journal articles, some of them paywalled. Popular misconceptions and differing conventions about terminology and notation have posed further barriers to entry. To address this need, this book presents a unified account of delay insensitive circuits from first principles to cutting edge concepts, subject only to an undergraduate-level understanding of discrete math. In an approachable tutorial format with numerous illustrations, exercises, and over three hundred references, it guides an engineering professional or advanced student towards proficiency in this extensive field.
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