These are a collection of XLSX sheets containing some of my favorite Excel tricks to reformat data to make analysis easier. I often use these to reformat column formatted data into plate layout or vice versa to better visualize and understand my data.

This repository was created to store, organize, and share data collected for the Eastern Kentucky Project, focusing on hydrological research in the region. It serves as a centralized platform to manage data efficiently and facilitate collaboration among researchers and stakeholders involved in the project.

The repository primarily contains data from level loggers, which are crucial for monitoring and recording water levels, temperature, and other hydrological parameters over time. The collected data has been carefully extracted, processed, and stored in Excel files to ensure compatibility with various analysis tools. This structured format enables easy access and seamless integration into research workflows.

In addition to providing secure storage, the repository is designed to support efficient data sharing, transparency, and interdisciplinary collaboration. By offering a well-organized dataset, it enables researchers to analyze and build upon existing data, promoting high-quality research outputs. The repository ultimately aims to advance understanding and inform decision-making in water resource management for Eastern Kentucky.

1. Software Tools for Data Processing: (1) Data Analysis Software: Tools such as Origin and Excel were used to organize, plot, and analyze experimental data from the dataset. (2) Material characterization data analysis software: For structural and morphological characterization data such as XRD, SEM, and TEM, specialized software is required for data processing and analysis. For example, MDI Jade 6 software is employed for phase structure analysis of XRD data to determine crystal structure and phase composition; Avantage software is used for XPS data analysis; Project FIVE 5.2 is utilized for Raman spectroscopy data analysis. (3) Electrochemical testing data analysis software: such as Zview for electrochemical impedance spectroscopy analysis, and Neware testing system for electrochemical data analysis.2. Data File Contents and Descriptions: Based on the arrangement of data files in the main text and the SI (Supporting Information), each dataset has been assigned a unique identifier, where one file corresponds to one figure. For example, Fig. 1 corresponds to Figure 1 in the main text, and Fig. S1 corresponds to Figure S1 in the SI. Additionally, each image within a file has been labeled accordingly. For instance, Fig. 1a, Fig. 1b... correspond to Fig. 1a, Fig. 1b... in the main text, respectively. Similarly, Fig. S1a, Fig. S1b... correspond to Fig. S1a, Fig. S1b... in the SI, respectively.

The Ontario government, generates and maintains thousands of datasets. Since 2012, we have shared data with Ontarians via a data catalogue. Open data is data that is shared with the public. Click here to learn more about open data and why Ontario releases it. Ontario’s Open Data Directive states that all data must be open, unless there is good reason for it to remain confidential. Ontario’s Chief Digital and Data Officer also has the authority to make certain datasets available publicly. Datasets listed in the catalogue that are not open will have one of the following labels: If you want to use data you find in the catalogue, that data must have a licence – a set of rules that describes how you can use it. A licence: Most of the data available in the catalogue is released under Ontario’s Open Government Licence. However, each dataset may be shared with the public under other kinds of licences or no licence at all. If a dataset doesn’t have a licence, you don’t have the right to use the data. If you have questions about how you can use a specific dataset, please contact us. The Ontario Data Catalogue endeavors to publish open data in a machine readable format. For machine readable datasets, you can simply retrieve the file you need using the file URL. The Ontario Data Catalogue is built on CKAN, which means the catalogue has the following features you can use when building applications. APIs (Application programming interfaces) let software applications communicate directly with each other. If you are using the catalogue in a software application, you might want to extract data from the catalogue through the catalogue API. Note: All Datastore API requests to the Ontario Data Catalogue must be made server-side. The catalogue's collection of dataset metadata (and dataset files) is searchable through the CKAN API. The Ontario Data Catalogue has more than just CKAN's documented search fields. You can also search these custom fields. You can also use the CKAN API to retrieve metadata about a particular dataset and check for updated files. Read the complete documentation for CKAN's API. Some of the open data in the Ontario Data Catalogue is available through the Datastore API. You can also search and access the machine-readable open data that is available in the catalogue. How to use the API feature: Read the complete documentation for CKAN's Datastore API. The Ontario Data Catalogue contains a record for each dataset that the Government of Ontario possesses. Some of these datasets will be available to you as open data. Others will not be available to you. This is because the Government of Ontario is unable to share data that would break the law or put someone's safety at risk. You can search for a dataset with a word that might describe a dataset or topic. Use words like “taxes” or “hospital locations” to discover what datasets the catalogue contains. You can search for a dataset from 3 spots on the catalogue: the homepage, the dataset search page, or the menu bar available across the catalogue. On the dataset search page, you can also filter your search results. You can select filters on the left hand side of the page to limit your search for datasets with your favourite file format, datasets that are updated weekly, datasets released by a particular organization, or datasets that are released under a specific licence. Go to the dataset search page to see the filters that are available to make your search easier. You can also do a quick search by selecting one of the catalogue’s categories on the homepage. These categories can help you see the types of data we have on key topic areas. When you find the dataset you are looking for, click on it to go to the dataset record. Each dataset record will tell you whether the data is available, and, if so, tell you about the data available. An open dataset might contain several data files. These files might represent different periods of time, different sub-sets of the dataset, different regions, language translations, or other breakdowns. You can select a file and either download it or preview it. Make sure to read the licence agreement to make sure you have permission to use it the way you want. Read more about previewing data. A non-open dataset may be not available for many reasons. Read more about non-open data. Read more about restricted data. Data that is non-open may still be subject to freedom of information requests. The catalogue has tools that enable all users to visualize the data in the catalogue without leaving the catalogue – no additional software needed. Have a look at our walk-through of how to make a chart in the catalogue. Get automatic notifications when datasets are updated. You can choose to get notifications for individual datasets, an organization’s datasets or the full catalogue. You don’t have to provide and personal information – just subscribe to our feeds using any feed reader you like using the corresponding notification web addresses. Copy those addresses and paste them into your reader. Your feed reader will let you know when the catalogue has been updated. The catalogue provides open data in several file formats (e.g., spreadsheets, geospatial data, etc). Learn about each format and how you can access and use the data each file contains. A file that has a list of items and values separated by commas without formatting (e.g. colours, italics, etc.) or extra visual features. This format provides just the data that you would display in a table. XLSX (Excel) files may be converted to CSV so they can be opened in a text editor. How to access the data: Open with any spreadsheet software application (e.g., Open Office Calc, Microsoft Excel) or text editor. Note: This format is considered machine-readable, it can be easily processed and used by a computer. Files that have visual formatting (e.g. bolded headers and colour-coded rows) can be hard for machines to understand, these elements make a file more human-readable and less machine-readable. A file that provides information without formatted text or extra visual features that may not follow a pattern of separated values like a CSV. How to access the data: Open with any word processor or text editor available on your device (e.g., Microsoft Word, Notepad). A spreadsheet file that may also include charts, graphs, and formatting. How to access the data: Open with a spreadsheet software application that supports this format (e.g., Open Office Calc, Microsoft Excel). Data can be converted to a CSV for a non-proprietary format of the same data without formatted text or extra visual features. A shapefile provides geographic information that can be used to create a map or perform geospatial analysis based on location, points/lines and other data about the shape and features of the area. It includes required files (.shp, .shx, .dbt) and might include corresponding files (e.g., .prj). How to access the data: Open with a geographic information system (GIS) software program (e.g., QGIS). A package of files and folders. The package can contain any number of different file types. How to access the data: Open with an unzipping software application (e.g., WinZIP, 7Zip). Note: If a ZIP file contains .shp, .shx, and .dbt file types, it is an ArcGIS ZIP: a package of shapefiles which provide information to create maps or perform geospatial analysis that can be opened with ArcGIS (a geographic information system software program). A file that provides information related to a geographic area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open using a GIS software application to create a map or do geospatial analysis. It can also be opened with a text editor to view raw information. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format for sharing data in a machine-readable way that can store data with more unconventional structures such as complex lists. How to access the data: Open with any text editor (e.g., Notepad) or access through a browser. Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A text-based format to store and organize data in a machine-readable way that can store data with more unconventional structures (not just data organized in tables). How to access the data: Open with any text editor (e.g., Notepad). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. A file that provides information related to an area (e.g., phone number, address, average rainfall, number of owl sightings in 2011 etc.) and its geospatial location (i.e., points/lines). How to access the data: Open with a geospatial software application that supports the KML format (e.g., Google Earth). Note: This format is machine-readable, and it can be easily processed and used by a computer. Human-readable data (including visual formatting) is easy for users to read and understand. This format contains files with data from tables used for statistical analysis and data visualization of Statistics Canada census data. How to access the data: Open with the Beyond 20/20 application. A database which links and combines data from different files or applications (including HTML, XML, Excel, etc.). The database file can be converted to a CSV/TXT to make the data machine-readable, but human-readable formatting will be lost. How to access the data: Open with Microsoft Office Access (a database management system used to develop application software). A file that keeps the original layout and

Excel spreadsheet containing, in separate sheets, the underlying numerical data and statistical analysis for Fig panels 3A, 4B-4D, 4F-4K, 5A, 5D-5E, 5H-5J, 6A, 6D, 6F-6H, 6J, 6M, 6O-6Q, 7F, S2B-S2D, S2F-S2H, S3B-S3D, S3F-S3H, S4C-S4G, S5A-S5B, S5G-S5H, and S5J-S5L.

Excel spreadsheets contain the underlying numerical data for Figs 1B, 1C, 2B, 2C, 3A, 3B, 3C, 3D, 3E, 3F, 3G, 4B, 4D, 6A, 6B, 6D, 6E, 6F, S2B, S2D, S3, S4A and S4B.

Excel spreadsheet containing the underlying numerical data and statistical analysis for all figures and tables.

Excel spreadsheet containing, in separate sheets, the underlying numerical data for Figure panels 1A, 1B, 1C, 1E, 1F, 2A, 2B, 2C, 2D, 2E, 3E, 3G, 3I, 4A, 4B, 4D, 4E, 4J, 4L, 4N, 5A, 5B, 5D, 5F, 5H and 5J.

Excel output from Invivo 12 analysis of mothers interviews.