Dataset

This dataset was created by Mark Dobres

Contents

This data is the set of responses to Student Subject Experience Surveys from WEL418 case management for two academics, Katrina Gersbach and Dr Monica Short for the sessions that they taught in the period 2014-17th June 2022.

Dataset

This dataset was created by Oscar NG

Released under CC0: Public Domain

Contents

Qualitative data gathered from interviews that were conducted with case organisations. The data is analysed using a qualitative data analysis tool (AtlasTi) to code and generate network diagrams. Software such as Atlas.ti 8 Windows will be a great advantage to use in order to view these results. Interviews were conducted with four case organisations. The details of the responses from the respondents from case organisations are captured. The data gathered during the interview sessions is captured in a tabular form and graphs were also created to identify trends. Also in this study is desktop review of the case organisations that formed part of the study. The desktop study was done using published annual reports over a period of more than seven years. The analysis was done given the scope of the project and its constructs.

Locations and numbers of past producing metal and coal mining projects in NW US and Canada. This dataset is associated with the following publication: Sergeant, C., E. Sexton, J. Moore, A. Westwood, S. Nagorski, J. Ebersole, D.M. Chambers, S.L. O'Neal, R.L. Malison, R. Hauer, D.C. Whited, J. Weitz, J. Caldwell, M. Capito, M. Connor, C.A. Frissell, G. Knox, E.D. Lowery, R. Macnair, V. Marlatt, J. McIntyre, M.V. McPhee, and N. Skuce. Risks of mining to salmonid-bearing watersheds. Science Advances. American Association for the Advancement of Science (AAAS), Washington, DC, USA, 8(26): eabn0929, (2022).

Preventive healthcare is a crucial pillar of health as it contributes to staying healthy and having immediate treatment when needed. Mining knowledge from longitudinal studies has the potential to significantly contribute to the improvement of preventive healthcare. Unfortunately, data originated from such studies are characterized by high complexity, huge volume, and a plethora of missing values. Machine Learning, Data Mining and Data Imputation models are utilized a part of solving these challenges, respectively. Toward this direction, we focus on the development of a complete methodology for the ATHLOS Project – funded by the European Union’s Horizon 2020 Research and Innovation Program, which aims to achieve a better interpretation of the impact of aging on health. The inherent complexity of the provided dataset lies in the fact that the project includes 15 independent European and international longitudinal studies of aging. In this work, we mainly focus on the HealthStatus (HS) score, an index that estimates the human status of health, aiming to examine the effect of various data imputation models to the prediction power of classification and regression models. Our results are promising, indicating the critical importance of data imputation in enhancing preventive medicine’s crucial role.

This study investigates the extent to which data science projects follow code standards. In particular, which standards are followed, which are ignored, and how does this differ to traditional software projects? We compare a corpus of 1048 Open-Source Data Science projects to a reference group of 1099 non-Data Science projects with a similar level of quality and maturity.results.tar.gz: Extracted data for each project, including raw logs of all detected code violations.notebooks_out.tar.gz: Tables and figures generated by notebooks.source_code_anonymized.tar.gz: Anonymized source code (at time of publication) to identify, clone, and analyse the projects. Also includes Jupyter notebooks used to produce figures in the paper.The latest source code can be found at: https://github.com/a2i2/mining-data-science-repositoriesPublished in ESEM 2020: https://doi.org/10.1145/3382494.3410680Preprint: https://arxiv.org/abs/2007.08978

Financial News Headlines. Visit https://dataone.org/datasets/sha256%3Ade01b1cf5318d53f0296b475ff28734d90acd6240a76f1eee1df39fefda07ef0 for complete metadata about this dataset.

Data Mining Kel 11

## Overview

Data Mining Kel 11 is a dataset for classification tasks - it contains Beras annotations for 59,785 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Dataset

This dataset was created by Will Newt

Contents

Data Mining

## Overview

Data Mining is a dataset for object detection tasks - it contains Uangrupiah annotations for 692 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

The dataset contains a Knowledge Graph (.nq file) of two historical mining documents: “Verleihbuch der Rattenberger Bergrichter” ( Hs. 37, 1460-1463) and “Schwazer Berglehenbuch” (Hs. 1587, approx. 1515) stored by the Tyrolean Regional Archive, Innsbruck (Austria). The user of the KG may explore the montanistic network and relations between people, claims and mines in the late medieval Tyrol. The core regions concern the districts Schwaz and Kufstein (Tyrol, Austria).

The ontology used to represent the claims is CIDOC CRM, an ISO certified ontology for Cultural Heritage documentation. Supported by the Karma tool the KG is generated as RDF (Resource Description Framework). The generated RDF data is imported into a Triplestore, in this case GraphDB, and then displayed visually. This puts the data from the early mining texts into a semantically structured context and makes the mutual relationships between people, places and mines visible.

Both documents and the Knowledge Graph were processed and generated by the research team of the project “Text Mining Medieval Mining Texts”. The research project (2019-2022) was carried out at the university of Innsbruck and funded by go!digital next generation programme of the Austrian Academy of Sciences.

Citeable Transcripts of the historical documents are online available:
Hs. 37 DOI: 10.5281/zenodo.6274562
Hs. 1587 DOI: 10.5281/zenodo.6274928

"The Africa Power–Mining Database 2014 shows ongoing and forthcoming mining projects in Africa categorized by the type of mineral, ore grade, size of the project. The database draws on basic mining data from Infomine surveys, the United States Geological Survey, annual reports, technical reports, feasibility studies, investor presentations, sustainability reports on property-owner websites or filed in public domains, and mining websites (Mining Weekly, Mining Journal, Mbendi, Mining-technology, and Miningmx). Comprising 455 projects in 28 SSA countries with each project’s ore reserve value assessed at more than $250 million, the database collates publicly available and proprietary information. It also provides a panoramic view of projects operating in 2000–12 and anticipated demand in 2020. The analysis is presented over three timeframes: pre-2000, 2001–12, and 2020 (each containing the projects from the previous period except for those closing during that previous period)."

Abstract In the early stage of front-end studies of a Mining Project, the global availability (i.e. number of hours a plant is available for production) and production (number of hours a plant is actually operated with material) time of the process plant are normally assumed based on the experience of the study team. Understanding and defining the availability hours at the early stages of the project are important for the future stages of the project, as drastic changes in work hours will impact the economics of the project at that stage. An innovative high-level dynamic modeling approach has been developed to assist in the rapid evaluation of assumptions made by the study team. This model incorporates systems or equipment that are commonly used in mining projects from mine to product stockyard discharge after the processing plant. It includes subsystems that will simulate all the component handling, and major process plant systems required for a mining project. The output data provided by this high-level dynamic simulation approach will enhance the confidence level of engineering carried out during the early stage of the project. This study discusses the capabilities of the approach, and a test case compared with standard techniques used in mining project front-end studies.

This dataset contains the SQL tables of the training and test datasets used in our experimentation. These tables contain the preprocessed textual data (in a form of tokens) extracted from each training and test project. Besides the preprocessed textual data, this dataset also contains meta-data about the projects, GitHub topics, and GitHub collections. The GitHub projects are identified by the tuple “Owner” and “Name”. The descriptions of the table fields are attached to their respective data descriptions.

Dataset

This dataset was created by Khanh Vương

Contents

This dataset comprises the raw data and R Script for the following published article: Schoderer, M., & Ott, M. (2022). Contested water-and miningscapes–Explaining the high intensity of water and mining conflicts in a meta-study. World Development, 154, 105888. The article seeks to better understand the dynamics of mining and water conflicts, specifically under which (combinations of) conditions environmental defenders step outside the legal framework in their contestation of mining projects, according to existing case study-based research. More information on the methodology is available in the paper.

The file Water and mining conflicts full dataset includes the qualitative information extracted from published articles, the scoring scheme and the normalized scores used in the R analysis. The R Script QCA_Preventive water and mining conflicts describes the fuzzy-set, two-step Qualitative Comparative Analysis conduct to understand under which conditions environmental defenders choose non-legal means in conflicts that occur in the planning or licensing stage of a mining project The CSV file Normalized scores_preventive is the raw data used in the R Script QCA_Preventive water and mining conflicts The R Script QCA_Reactive water and mining conflicts describes the fuzzy-set, two-step Qualitative Comparative Analysis conduct to understand under which conditions environmental defenders choose non-legal means in conflicts that occur when the mining project is already in operation The CSV file Normalized scores_reactive is the raw data used in the R Script QCA_Reactive water and mining conflicts

Retrofitting is an essential element of any comprehensive strategy for improving residential energy efficiency. The residential retrofit market is still developing, and program managers must develop innovative strategies to increase uptake and promote economies of scale. Residential retrofitting remains a challenging proposition to sell to homeowners, because awareness levels are low and financial incentives are lacking. The U.S. Department of Energy's Building America research team, Alliance for Residential Building Innovation (ARBI), implemented a project to increase residential retrofits in Davis, California. The project used a neighborhood-focused strategy for implementation and a low-cost retrofit program that focused on upgraded attic insulation and duct sealing. ARBI worked with a community partner, the not-for-profit Cool Davis Initiative, as well as selected area contractors to implement a strategy that sought to capitalize on the strong local expertise of partners and the unique aspects of the Davis, California, community. Working with community partners also allowed ARBI to collect and analyze data about effective messaging tactics for community-based retrofit programs. ARBI expected this project, called Retrofit Your Attic, to achieve higher uptake than other retrofit projects, because it emphasized a low-cost, one-measure retrofit program. However, this was not the case. The program used a strategy that focused on attics-including air sealing, duct sealing, and attic insulation-as a low-cost entry for homeowners to complete home retrofits. The price was kept below $4,000 after incentives; both contractors in the program offered the same price. The program completed only five retrofits. Interestingly, none of those homeowners used the one-measure strategy. All five homeowners were concerned about cost, comfort, and energy savings and included additional measures in their retrofits. The low-cost, one-measure strategy did not increase the uptake among homeowners, even in a well-educated, affluent community such as Davis. This project has two primary components. One is to complete attic retrofits on a community scale in the hot-dry climate on Davis, CA. Sufficient data will be collected on these projects to include them in the BAFDR. Additionally, ARBI is working with contractors to obtain building and utility data from a large set of retrofit projects in CA (hot-dry). These projects are to be uploaded into the BAFDR.

Abstract The use of dynamic simulation is technically advantageous for the project as shown by various authors. However, is it economically advantageous in the early stages of the project (FEL1 and FEL2)? The methodology to economically evaluate the use of dynamic simulation considers the time and development cost compared with the time and cost spent to change the project in the next phase, considering changes that could be avoided with the use of dynamic simulation. Five process plant projects were evaluated, each one with an estimated CAPEX of US$ 300 million. The saved average is US$ 44,200.00 and US$ 182,400.00 for FEL 1 and FEL 2 respectively. The percentage cost savings for FEL2 (2.0%) and FEL3 (3.1%) are significant. The estimated delay avoided for FEL2 (3 weeks) and FEL3 (8 weeks) is directly related to the implementation delay, whose cost is expressively greater than the savings shown. The study concludes that the use of dynamic simulation is economically advantageous for the project.

This dataset provides information related to the top-spending off-mine-site exploration and deposit appraisal projects in Canada for the given reference year. The dataset is maintained by the Lands and Minerals Sector, Natural Resources Canada, and forms the basis for the annual Map of Top 100 Exploration and Deposit Appraisal Projects in Canada. Related product: - Principal Mineral Areas, Producing Mines, and Oil and Gas Fields (900A)