The dataset represents data used to create tables and figures used in in manuscript. This dataset is associated with the following publication: Lytle, D., D. Wahman, M. Schock, M. Nadagouda, S. Harmon, K. Webster, and J. Botkins. Georgeite: A Rare Copper Mineral with Important Drinking Water Implications. Chemical Engineering Journal. Elsevier BV, AMSTERDAM, NETHERLANDS, 355: 1-10, (2019).

Question Paper Solutions of Word, PowerPoint & Spreadsheet Application with Excel (MIC301A),3rd Semester,Bachelor in Business Administration (Hons.) 2023-2024,Maulana Abul Kalam Azad University of Technology

Spreadsheets for analysis in CEAS Paper 26 October

This is the excel spreadsheet dataset containing our analysis of papers performing mining software repositories research from the conferences ICSE, ESEC/FSE, and MSR from the years 2018 - 2020. The data is broken into columns and can be explained at a high-level as follows:

Column Content

1 The paper being analyzed

2 Does the paper state the data they analyzed is available

3 Does the paper perform some sort of data analysis or sampling using data others have compiled in the past

4 Does the paper state a timestamp for when they begin their work

5 Does the paper state the use of systems pre-built to help with MSR work

6 - 18 Forms of sampling researchers may have employed to select their data

19 What datasets (if any) were used in the analysis

20 What tools (if any) were used in the analysis

21 How they performed their data sampling workflow

22 How they performed their data filtering workflow

23 How they performed their data retrieval workflow

24 Did they create any scripts in each of these workflows

25 - 33 Did they publish a replication package and what is contained within

34 Is the paper describing a tool for research or not

35 Short description of the paper read

36 A high-level category of the work performed in each paper

Question Paper Solutions of chapter Word II of Word, PowerPoint & Spreadsheet Application with Excel, 3rd Semester , Bachelor in Business Administration (Hons.) 2023-2024

Get Exam Question Paper Solutions of Word, PowerPoint & Spreadsheet Application with Excel and many more.

The supplementary data consists of spreadsheet files for the four models assessed in the paper. Models included from the paper are K2005A, A2016 (for both confined and unconfined aquifers) and A2016STA (included in the A2016 unconfined model). In addition, K2005B, which uses average instead of harmonic mean to determine cell to cell hydraulic conductance is included.

Data Set S1 (DS01). Spreadsheet model containing both K2005A and K2005B models. Both models use many of the same tabs, with the main differences being how hydraulic conductivity is averaged between cells. In K2005A the harmonic mean is used. K2005B uses the arithmetic mean. File: ds01_Transient Groundwater K2005A_K2005B

Data Set S2 (DS02). Spreadsheet model containing both the K2005B model, and a modified version – K2005M – which incorporates an aquifer thickness variable and initial head values. Both models use many of the same sheets for their datasets. File: ds02_Transient Groundwater K2005M_K2005B

Data Set S3 (DS03). Spreadsheet model A2016 for confined aquifers based on the mathematics and structure of Modflow and using macros for timestep control. File: ds03_Transient Groundwater A2016_confined

Data Set S4 (DS04). Spreadsheet model A2016 for unconfined aquifers, based on the mathematics and structure of Modflow and using macros for timestep control. This spreadsheet also includes data to allow for the application of the specified thickness approximation. File: ds04_Transient Groundwater A2016_unconfined

Updated: 30/07/2018 - Cleaned up some terminology and units. Removed redundant macro button. Updated: 8/8/18 - Added tutorial.

EUSES is the most frequently used spreadsheet corpus, and contains 4,037 spreadsheets. These spreadsheets were extracted from World Wide Web. We applied SpreadCluster to the EUSES and manually validated all groups. Based on the validated result, we built the VEUSES corpus, containing 177 evolution groups and 363 spreadsheets.VEUSES is published associated with our MSR 2017 paper in May 2017. Liang Xu, Wensheng Dou, Chushu Gao, Jie Wang, Jun Wei, Hua Zhong, Tao Huang. SpreadCluster: Recovering Versioned Spreadsheets through Similarity-Based Clustering. In Proceedings of the 14th International Conference on Mining Software Repositories (MSR 2017), May 2017.

This repository contains supplementary materials for the following conference paper:

Valdemar Švábenský, Jan Vykopal, Pavel Čeleda. What Are Cybersecurity Education Papers About? A Systematic Literature Review of SIGCSE and ITiCSE Conferences. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE 2020). https://doi.org/10.1145/3328778.3366816

Preprint available at: https://arxiv.org/abs/1911.11675

How to cite

If you use or build upon the materials, please use the BibTeX entry below to cite the original paper (not only this web link).

@inproceedings{Svabensky2020what, author = {\v{S}v\'{a}bensk\'{y}, Valdemar and Vykopal, Jan and \v{C}eleda, Pavel}, title = {{What Are Cybersecurity Education Papers About? A Systematic Literature Review of SIGCSE and ITiCSE Conferences}}, booktitle = {Proceedings of the 51st ACM Technical Symposium on Computer Science Education}, series = {SIGCSE '20}, location = {Portland, OR, USA}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, month = {03}, year = {2020}, pages = {2--8}, numpages = {7}, isbn = {978-1-4503-6793-6}, url = {https://doi.org/10.1145/3328778.3366816}, doi = {10.1145/3328778.3366816}, }

Attached content

The file "SIGCSE 2020 Literature Review.xlsx" is an Excel spreadsheet with three sheets corresponding to 1) all papers found by automated search, 2) manually excluded papers, and 3) papers included in the literature review. There are also three CSV files that correspond to the three individual sheets.

This dataset contains data collected during a study "Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems" conducted by Martin Lnenicka (University of Hradec Králové, Czech Republic), Anastasija Nikiforova (University of Tartu, Estonia), Mariusz Luterek (University of Warsaw, Warsaw, Poland), Petar Milic (University of Pristina - Kosovska Mitrovica, Serbia), Daniel Rudmark (Swedish National Road and Transport Research Institute, Sweden), Sebastian Neumaier (St. Pölten University of Applied Sciences, Austria), Karlo Kević (University of Zagreb, Croatia), Anneke Zuiderwijk (Delft University of Technology, Delft, the Netherlands), Manuel Pedro Rodríguez Bolívar (University of Granada, Granada, Spain).

As there is a lack of understanding of the elements that constitute different types of value-adding public data ecosystems and how these elements form and shape the development of these ecosystems over time, which can lead to misguided efforts to develop future public data ecosystems, the aim of the study is: (1) to explore how public data ecosystems have developed over time and (2) to identify the value-adding elements and formative characteristics of public data ecosystems. Using an exploratory retrospective analysis and a deductive approach, we systematically review 148 studies published between 1994 and 2023. Based on the results, this study presents a typology of public data ecosystems and develops a conceptual model of elements and formative characteristics that contribute most to value-adding public data ecosystems, and develops a conceptual model of the evolutionary generation of public data ecosystems represented by six generations called Evolutionary Model of Public Data Ecosystems (EMPDE). Finally, three avenues for a future research agenda are proposed.

This dataset is being made public both to act as supplementary data for "Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems ", Telematics and Informatics*, and its Systematic Literature Review component that informs the study.

Description of the data in this data set

PublicDataEcosystem_SLR provides the structure of the protocol

Spreadsheet#1 provides the list of results after the search over three indexing databases and filtering out irrelevant studies

Spreadsheets #2 provides the protocol structure.

Spreadsheets #3 provides the filled protocol for relevant studies.

The information on each selected study was collected in four categories:(1) descriptive information,(2) approach- and research design- related information,(3) quality-related information,(4) HVD determination-related information

Descriptive Information

Article number

A study number, corresponding to the study number assigned in an Excel worksheet

Complete reference

The complete source information to refer to the study (in APA style), including the author(s) of the study, the year in which it was published, the study's title and other source information.

Year of publication

The year in which the study was published.

Journal article / conference paper / book chapter

The type of the paper, i.e., journal article, conference paper, or book chapter.

Journal / conference / book

Journal article, conference, where the paper is published.

DOI / Website

A link to the website where the study can be found.

Number of words

A number of words of the study.

Number of citations in Scopus and WoS

The number of citations of the paper in Scopus and WoS digital libraries.

Availability in Open Access

Availability of a study in the Open Access or Free / Full Access.

Keywords

Keywords of the paper as indicated by the authors (in the paper).

Relevance for our study (high / medium / low)

What is the relevance level of the paper for our study

Approach- and research design-related information

Approach- and research design-related information

Objective / Aim / Goal / Purpose & Research Questions

The research objective and established RQs.

Research method (including unit of analysis)

The methods used to collect data in the study, including the unit of analysis that refers to the country, organisation, or other specific unit that has been analysed such as the number of use-cases or policy documents, number and scope of the SLR etc.

Study’s contributions

The study’s contribution as defined by the authors

Qualitative / quantitative / mixed method

Whether the study uses a qualitative, quantitative, or mixed methods approach?

Availability of the underlying research data

Whether the paper has a reference to the public availability of the underlying research data e.g., transcriptions of interviews, collected data etc., or explains why these data are not openly shared?

Period under investigation

Period (or moment) in which the study was conducted (e.g., January 2021-March 2022)

Use of theory / theoretical concepts / approaches? If yes, specify them

Does the study mention any theory / theoretical concepts / approaches? If yes, what theory / concepts / approaches? If any theory is mentioned, how is theory used in the study? (e.g., mentioned to explain a certain phenomenon, used as a framework for analysis, tested theory, theory mentioned in the future research section).

Quality-related information

Quality concerns

Whether there are any quality concerns (e.g., limited information about the research methods used)?

Public Data Ecosystem-related information

Public data ecosystem definition

How is the public data ecosystem defined in the paper and any other equivalent term, mostly infrastructure. If an alternative term is used, how is the public data ecosystem called in the paper?

Public data ecosystem evolution / development

Does the paper define the evolution of the public data ecosystem? If yes, how is it defined and what factors affect it?

What constitutes a public data ecosystem?

What constitutes a public data ecosystem (components & relationships) - their "FORM / OUTPUT" presented in the paper (general description with more detailed answers to further additional questions).

Components and relationships

What components does the public data ecosystem consist of and what are the relationships between these components? Alternative names for components - element, construct, concept, item, helix, dimension etc. (detailed description).

Stakeholders

What stakeholders (e.g., governments, citizens, businesses, Non-Governmental Organisations (NGOs) etc.) does the public data ecosystem involve?

Actors and their roles

What actors does the public data ecosystem involve? What are their roles?

Data (data types, data dynamism, data categories etc.)

What data do the public data ecosystem cover (is intended / designed for)? Refer to all data-related aspects, including but not limited to data types, data dynamism (static data, dynamic, real-time data, stream), prevailing data categories / domains / topics etc.

Processes / activities / dimensions, data lifecycle phases

What processes, activities, dimensions and data lifecycle phases (e.g., locate, acquire, download, reuse, transform, etc.) does the public data ecosystem involve or refer to?

Level (if relevant)

What is the level of the public data ecosystem covered in the paper? (e.g., city, municipal, regional, national (=country), supranational, international).

Other elements or relationships (if any)

What other elements or relationships does the public data ecosystem consist of?

Additional comments

Additional comments (e.g., what other topics affected the public data ecosystems and their elements, what is expected to affect the public data ecosystems in the future, what were important topics by which the period was characterised etc.).

New papers

Does the study refer to any other potentially relevant papers?

Additional references to potentially relevant papers that were found in the analysed paper (snowballing).

Format of the file.xls, .csv (for the first spreadsheet only), .docx

Licenses or restrictionsCC-BY

For more info, see README.txt

data for all the figures and tables can be found in excel sheets. Portions of this dataset are inaccessible because: it is hosted on a public site. They can be accessed through the following means: http://doi.org/10.5281/zenodo.5874973. Format: excel spreadsheet.

This dataset is associated with the following publication: Cheng, B., K. Alapaty, Q. Shu, and S. Arunachalam. Dry Deposition Methods Based on Turbulence Kinetic Energy: 2. Extension to Particle Deposition Using a Single-Point Model. JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 127(22): e2022JD037803, (2022).

The survey data file spreadsheet accompanying this article consists of 725 rows and 29 columns. Each row presents an individual's response to a questionnaire.

Data for the paper 'A simple strategy for enhancing the detection limits of blue-green ECL emitters'. The Excel spreadsheet contains the data for each of the figures and are labelled as such. Where traces were smoothed for the paper, both smoothed and unsmoothed data are provided in the spreadsheet. Please refer to the experimental section of the paper for methodology.

Spreadsheet from the paper entitled: Revisiting a Statistical Shortcoming when Fitting the Langmuir Model to Sorption Data by C.H. Bolster, Journal of Environmental Quality, 2008, 37:1986-1992. Spreadsheet has been modified to make a correction to the calculation of E for weighted data. (3/18/2010). Sorption models are commonly used for describing solute and metal sorption to soils. When fitting sorption models to sorption data, however, the user must be aware that certain statistical limitations exist with both linear and nonlinear versions of the models. Ongoing research at the Animal Waste Management Research Unit of the USDA-ARS addresses the effect of these statistical limitations on fitting phosphorus sorption data with various sorption models. This research was originally part of the former USDA-ARS National Program 206: Manure and By-product Utilization. Resources in this dataset:Resource Title: Modified Langmuir Equation Spreadsheet. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=205&modecode=50-40-05-00 download page

The data in this spreadsheet was used to produce the figures in the paper

Andres Parra-Puerto, Kai Ling NG, Kieran Fahy, Angela E Goode, Mary P. Ryan, and Anthony Kucernak

Supported Transition Metal Phosphides: Activity Survey for HER, ORR, OER and Corrosion Resistance in Acid and Alkaline Electrolytes

ACS Catalysis, 2019

DOI: 10.1021/acscatal.9b03359Please cite the above reference if you wish to use this data

The Last Interglacial (MIS 5e, 128-116 ka) is among the most studied past periods in Earth's history. The climate at that time was warmer than today, primarily due to different orbital conditions, with smaller ice sheets and higher sea-level. Field evidence for MIS 5e sea-level was reported from thousands of sites, but often paleo shorelines were measured with low-accuracy techniques and, in some cases, there are contrasting interpretations about paleo sea-level reconstructions. For this reason, large uncertainties still surround both the maximum sea-level attained as well as the pattern of sea-level change throughout MIS 5e. Such uncertainties are exacerbated by the lack of a uniform approach to measuring and interpreting the geological evidence of paleo sea-levels. In this review, we discuss the characteristics of MIS 5e field observations, and we set the basis for a standardized approach to MIS 5e paleo sea-level reconstructions, that is already successfully applied in Holocene sea-level research. Application of the standard definitions and methodologies described in this paper will enhance our ability to compare data from different research groups and different areas, in order to gain deeper insights into MIS 5e sea-level changes. Improving estimates of Last Interglacial sea-level is, in turn, a key to understanding the behavior of ice sheets in a warmer world.

Survey of Victorian recycling industries representing approx 95% of all recycled material in Victoria. Tonnes recycled of different material types recovered (glass, paper, plastics, metals, etc.) by source sector from which they were generated. This excel spreadsheet provides information about total paper & cardboard waste recovered for reprocessing in Victoria.

Spreadsheet with additional results from the paper: More Precise Methods for National Research Citation Impact Comparisons

This paper describes the embedding of ClassSheet models in spreadsheet systems. ClassSheet models are well-known and describe the business logic of spreadsheet data. We embed this domain specific model representation on the (general purpose) spreadsheet system it models. By defining such an embedding, we provide end users a model-driven engineering spreadsheet developing environment. End users can interact with both the model and the spreadsheet data in the same environment. Moreover, we use advanced techniques to evolve spreadsheets and models and to have them synchronized. In this paper we present our work on extending a widely used spreadsheet system with such a model-driven spreadsheet engineering environment.

The supplementary data consists of spreadsheet files for the four models assessed in the paper. Models included from the paper are K2005A, A2016 (for both confined and unconfined aquifers) and A2016STA (included in the A2016 unconfined model). In addition, K2005B, which uses average instead of harmonic mean to determine cell to cell hydraulic conductance is included.

Data Set S1 (DS01). Spreadsheet model containing both K2005A and K2005B models. Both models use many of the same tabs, with the main differences being how hydraulic conductivity is averaged between cells. In K2005A the harmonic mean is used. K2005B uses the arithmetic mean. File: ds01_Transient Groundwater K2005A_K2005B

Data Set S2 (DS02). Spreadsheet model containing both the K2005B model, and a modified version – K2005M – which incorporates an aquifer thickness variable and initial head values. Both models use many of the same sheets for their datasets. File: ds02_Transient Groundwater K2005M_K2005B

Data Set S3 (DS03). Spreadsheet model A2016 for confined aquifers based on the mathematics and structure of Modflow and using macros for timestep control. File: ds03_Transient Groundwater A2016_confined

Data Set S4 (DS04). Spreadsheet model A2016 for unconfined aquifers, based on the mathematics and structure of Modflow and using macros for timestep control. This spreadsheet also includes data to allow for the application of the specified thickness approximation. File: ds04_Transient Groundwater A2016_unconfined

Updated: 30/07/2018 - Cleaned up some terminology and units. Removed redundant macro button. Updated: 8/8/18 - Added tutorial. Updated: 9/5/19 - Updated title to match the paper.