Find research datasets worth reusing

Fig 1 in Incidence of parasitic infection in adult and juvenile Clarias gariepinus in a private fish farm, Yola, Adamawa state

Fig 1: Sex Variation in Prevalence (%) of Parasitic Infection of Culture Clarias gariepinus

Plate 4 in Incidence of parasitic infection in adult and juvenile Clarias gariepinus in a private fish farm, Yola, Adamawa state

Plate 4: Capillaria parasites recovered from the stomach and intestine of C. gariepinu

Plate 6 in Incidence of parasitic infection in adult and juvenile Clarias gariepinus in a private fish farm, Yola, Adamawa state

Plate 6: Piscinoodinium (Dinoflagellate) found on the gill of adult Clarias gariepinus

Plate 2 in Incidence of parasitic infection in adult and juvenile Clarias gariepinus in a private fish farm, Yola, Adamawa state

Plate 2: Internal organ of adult Clarias gariepinus dissection indicating the stomach, intestine

Plate 3 in Incidence of parasitic infection in adult and juvenile Clarias gariepinus in a private fish farm, Yola, Adamawa state

Plate 3: Piscinoodinium (Dinoflagellate) found on the skin of adult Clarias gariepinus

Dataset on the academic performance of students in 12 programmes from a private university

The dataset on the academic performance of students in 12 programmes from a private university. The overall people sampled for the observation is 2490 undergraduates excavated from 12 programmes which are as follows Computer Science (CIS), Mathematics (MAT), Electrical and Electronics Engineering (EEE), Biochemistry (BCH), Mechanical Engineering (MCE), Microbiology (MCB), Civil Engineering (CVE), Computer Engineering (CEN), Chemical Engineering (CHE), Industrial Chemistry (CHM), Information and Communication (ICE), Petroleum Engineering (PET).

Performance Evaluation: Dataset on the scholastic performance of students in 12 programmes from a private university in the south-west geopolitical zone in Nigeria

Dataset of educational performances of college students in 12 programmes in a private university in Nigeria. The overall people sampled for the observation is 2490 undergraduates excavated from 12 programmes which are as follows Computer Science (CIS), Mathematics (MAT), Electrical and Electronics Engineering (EEE), Biochemistry (BCH), Mechanical Engineering (MCE), Microbiology (MCB), Civil Engineering (CVE), Computer Engineering (CEN), Chemical Engineering (CHE), Industrial Chemistry (CHM), Information and Communication (ICE), Petroleum Engineering (PET).

paper Dataset on the academic performance of students in 12 programmes from a private university

Dataset on the academic performance of students in 12 programmes from a private university. The overall people sampled for the observation is 2490 undergraduates excavated from 12 programmes which are as follows Computer Science (CIS), Mathematics (MAT), Electrical and Electronics Engineering (EEE), Biochemistry (BCH), Mechanical Engineering (MCE), Microbiology (MCB), Civil Engineering (CVE), Computer Engineering (CEN), Chemical Engineering (CHE), Industrial Chemistry (CHM), Information and Communication (ICE), Petroleum Engineering (PET).

opencc-by-4.0Aug 2024View details →

Dataset (raw questionnaire data and variable importance results) supplementing the publication "Does Gender Really Matter? How Demographics and Site Characteristics Influence Behavior and Attitudes of German Small-Scale Private Forest Owners"

The dataset contains <ul> <li>a translation of the questionnaire,</li> <li>the questionnaire raw data, and</li> <li>the results of the variable importance analysis</li> </ul> used in the publication "Does Gender Really Matter? How Demographics and Site Characteristics Influence Behavior and Attitudes of Small-Scale Private Forest Owners".

opencc-by-4.0Nov 2024View details →

Yeasts prefer daycares and molds prefer private homes

Indoor fungi can cause negative health effects due to the production of toxins or volatiles that trigger the immune system of the occupants. To what degree indoor fungi (mycobiomes) differ between buildings with different usage is poorly known. <a>Here, we compare the indoor mycobiomes in 123 children’s daycare centers and 214 private homes </a>throughout Norway, as revealed by metabarcoding of DNA extracted from dust samples collected by community scientists. Although the fungal richness per se was similar in dust samples from daycares and homes, the fungal community composition differed. Yeast fungi, distributed mainly across the orders Saccharomycetales, Filobasidiales and Tremellales, were proportionally more abundant in the daycares, while filamentous fungi, including spore-producing molds such as Aspergillus, Penicillum and Cladosporium, were relatively more abundant in homes. Number of occupants, which is considerably higher in daycares, correlated significantly with the fungal community shift. We hypothesize that the density of occupants and their age distribution drive the systematic difference of yeasts and filamentous fungi in the two building types.

opencc-by-4.0Jun 2021View details →

pGAN Synthetic Dataset: A Deep Learning Approach to Private Data Sharing of Medical Images Using Conditional GANs

Synthetic dataset for A Deep Learning Approach to Private Data Sharing of Medical Images Using Conditional GANs  Dataset specification: <ul> <li>MRI images of Vertebral Units labelled based on region</li> <li>Dataset is comprised of 10000 pairs of images and labels</li> <li>Image and label pair number k can be selected by: synthetic_dataset['images'][k] and synthetic_dataset['regions'][k]</li> <li>Images are 3D of size (9, 64, 64)</li> <li>Regions are stored as an integer. Mapping is 0: cervical, 1: thoracic, 2: lumbar</li> </ul> Arxiv paper: <a href="https://arxiv.org/abs/2106.13199">https://arxiv.org/abs/2106.13199</a> Github code: <a href="https://github.com/tcoroller/pGAN/">https://github.com/tcoroller/pGAN/</a> Abstract: Sharing data from clinical studies can facilitate innovative data-driven research and ultimately lead to better public health. However, sharing biomedical data can put sensitive personal information at risk. This is usually solved by anonymization, which is a slow and expensive process. An alternative to anonymization is sharing a synthetic dataset that bears a behaviour similar to the real data but preserves privacy. As part of the collaboration between Novartis and the Oxford Big Data Institute, we generate a synthetic dataset based on COSENTYX Ankylosing Spondylitis (AS) clinical study. We apply an Auxiliary Classifier GAN (ac-GAN) to generate synthetic magnetic resonance images (MRIs) of vertebral units (VUs). The images are conditioned on the VU location (cervical, thoracic and lumbar). In this paper, we present a method for generating a synthetic dataset and conduct an in-depth analysis on its properties of along three key metrics: image fidelity, sample diversity and dataset privacy.

opencc-by-4.0Dec 2020View details →

Dataset (46 analyzed core studies) of the publication "Conservation perspectives of small-scale private forest owners in Europe: A systematic review"

The dataset contains the data collected to conduct the review "Conservation perspectives of small-scale private forest owners in Europe: A systematic review".

opencc-by-4.0Sep 2021View details →

Dataset (n=1671) of the publication "Small-scale private forest owners and the European Natura 2000 conservation network: Perceived ecosystem services, management practices, and nature conservation attitudes"

The excel file contains the replies of small-scale private forest owners in Lower Saxony, Germany, to certain questions of a survey analyzed within the following publication: "Small-scale private forest owners and the European Natura 2000 conservation network: Perceived ecosystem services, management practices, and nature conservation attitudes”. The questions included in this dataset cover their objectives, management activities, attitudes and forest stand structures. Further details can be found in the second sheet of the file called “Code explanation”. More information about the methods of data collection can be found in the before-mentioned publication.

Research Incentive Programs for Closures of Public and Private Grade Crossings

Corresponding data set for Tran-SET Project No. 17PPLSU13. Abstract of the final report is stated below for reference: "Vehicle-train crashes that occur at highway-rail crossings result in injuries, fatalities, and damage to equipment. In order to reduce the number of vehicle-train crashes, Federal Railroad Administration requires states which have challenges with crossing safety, including Louisiana, to develop a State Action Plan to improve grade crossing safety. Consequently, identification of specific solutions for improving safety at crossings was included in the 2015 Louisiana Transportation Plan as one of its objectives. This study seeks to identify and evaluate current and new incentive programs that encourage closure of at-grade railroad crossings to reduce the number of potential vehicle-train collision points, and hence improve safety. To accomplish this, a survey was designed and was distributed to personnel of state and railroad agencies. Survey responses from the DOTs revealed that currently, 16 states had no incentive programs for consolidation or closure of highway-rail crossings. Analysis of the survey data revealed that states without any incentive program had the least proportion of highway-rail crossing closures. The study revealed that cash incentives, while popular are not effective because although the Federal Government contributes to a state’s effort in offering cash incentives for closure of public grade crossings, the amount is not substantial enough to be considered a significant incentive by most local governments. Also, track relocation, while effective is mostly impractical due to the high costs involved. A literature review revealed that having a mathematical model to guide on the selection of crossings for consolidation or closure provides sound scientific basis and are usually welcomed by the community. The research team identified three potential new incentives that could work well for Louisiana namely crime rate reduction incentives, greenness improvement programs, and the development of a grade crossing consolidation model that considers safety, among a plethora of other factors, to be used to prioritize crossings to be closed. However, additional work is required to validate these programs for statewide deployment."

opencc-by-4.0Oct 2022View details →

The Smart City as a Field of Innovation: Effects of Public-Private Data Collaboration on the Innovative Performance of Small and Medium-Sized Enterprises in China

Data is increasingly considered to be a key component in stimulating innovation (Cockburn, Henderson, and Stern, 2019). Numerous promising possibilities have been opened up by rapidly emerging, data-intensive technologies, including the Internet of Things (IoT) and artificial intelligence. The analysis and interpretation of big data are critical in the growth of technology firms in terms of AI training and computing capabilities (Allam and Dhunny, 2019). Small and medium-sized enterprises (SMEs), with their limited resources internally, particularly face a serious challenge of implementing innovation that depends upon data. The smart city provides an important opportunity for creating data-driven innovation. Significant amounts of data are increasingly available from various sources through sophisticated devices and equipment scattered in smart cities. Many smart city projects across the globe provide rich opportunities for SMEs to explore data-driven innovation (Bresciani, Ferraris, and Del Giudice, 2018). China, in particular, has recently been active in collecting and utilizing various kinds of data in smart cities. The availability of and access to data help to improve the software development of firms in China, where massive amounts of data resources are held by the government (Beraja, Yang, and Yuchtman, 2022). In the process of smart city development, there are also many tasks that are complementary to each other, including connecting databases, building online platforms that connect different data coming from different data sources, operating online platforms, and providing products and services to citizens. These diverse kinds of tasks involved in smart city projects initiated by local governments have brought about new business opportunities for innovative SMEs in China. To implement the policies of encouraging the development of SMEs by the central government, municipal governments have introduced policies that give priority to SMEs in participating in smart city projects (Ministry of Industry and Information Technology, 2016). Those companies that have access to the data held by government agencies are expected to benefit from utilizing the rich data for creating innovative products and services. There were few empirical studies conducted, however, to examine how data are actually managed and provided in smart cities and how they affect companies’ innovative activities. It remains unclear how public agencies and private enterprises collaborate on data and how that influences the innovation performance of SMEs in China. In smart cities, different types of public-private collaboration are involved, including hardware purchase, platform building, platform operation, and data analysis. It is not yet well-understood how these different types of collaboration influence the innovative performance of SMEs. In this study, we intend to address how data are managed through collaboration between the government and companies in smart cities and how the mode of collaboration influences firms’ performance on innovation. By focusing on the case of SMEs in China, this research aims to shed light on what kinds of data are available and used in smart cities and how the government and enterprises collaborate on data to facilitate innovation. The analysis of this study utilizes data on more than eight million contracts extracted from the official procurement database of the government. Data on companies are assembled with regard to the registered capital, industry, software products, and patents in 1990-2021 from the Tianyancha website. A panel data is established with key characteristics of SMEs, software and patents outputs, and their record on obtaining different government contracts annually. The government contracts are divided into three categories, namely, data analysis, platform building, and equipment supply, based on keyword identifications. To deal with the unbalance between the treatment group (the companies that obtained government contracts) and the control group, we use propensity score matching (one-to-one nearest neighbor matching) to narrow down the sample size of the control group to that of the treatment group. Then we apply the traditional difference-in-difference (DID) and  DID with multiple time periods (Callaway & Sant’Anna, 2021) methods to examine whether there are significant differences in innovative outputs of software products and patents before and after the companies receive government contracts. We also compare how the innovation performance of companies differs based on the types of contracts these companies obtain. That makes it possible to identify what kinds of data collaboration would be effective in improving the innovative performance of SMEs. Our preliminary analysis of average treatment effect suggests that obtaining the government contracts, especially research contracts and platform building type of contracts, can effectively help improve the innovation performance when comparing between the control and treatment group. After checking the common support graph and doing a balance test, the outcome is solid. In general, based on the average treatment effect on the treated group, innovation performance, as measured by the number of patents and software productions, has shown a significant increase for those companies that obtain a research type of contract, whereas the increase is smaller for the platform building contractor and slight for the equipment purchase contractor. Government purchase of equipment that contains data-intensive technologies promotes the use of these products in smart cities. That, however, does not involve any substantive exchange or transfer of data possessed by the government and would not significantly contribute to stimulating innovation at firms. This study will have useful implications for establishing public-private collaboration on data for facilitating innovation in smart cities. Specifically, government procurement should also be viewed as a policy tool for improving China's technological innovation. According to our findings, research and platform development can successfully assist firms in improving their innovation performance. As a result, the government should grant enterprises access to additional data resources and data management related tasks if they want to see more industry structural transformation, as stated in the government documents.

opencc-by-4.0Dec 2022View details →

Time to independence and predator-prey relationships of wild-born, captive-raised cheetahs released into private reserves in Namibia

Data associated with the manuscript: Marker, L.,  Schmidt-Küntzel, A., Walker, E. H., Nghikembua, M., Cristescu, B. Time to independence and predator-prey relationships of wild-born, captive-raised cheetahs released into private reserves in Namibia. Ecological Solutions and Evidence. Contact: Dr. Bogdan Cristescu bogdan@cheetah.org Description: This manuscript estimated the time to independence and cheetah-prey relationships for cheetahs released onto three private reserves in Namibia. The cheetahs were rescued as wild-born cubs, were raised in captivity and went through a rehabilitation process at the Cheetah Conservation Fund, Namibia, and then released with collars to monitor their success post-release in the wild. The data is a MS Excel file that includes separate spreadsheets for: - Time to independence ("TimeToIndependence"): number of weekly supplemental feedings of cheetahs post-release before achieving independence - Prey composition ("PreyComposition"): the species, sex, age class, and size class of prey that cheetahs killed and were recorded during monitoring post-release   - Prey availability ("PreyAvailability"): the prey species recorded along driven dirt road transects, and which were used to estimate prey density in a distance sampling framework  - Habitat use ("HabitatUse"): the number of kills made by released cheetahs that have associated habitat class information, partitioned by chetah reproductive status (SF: solitary female, CF: coalition females, CM: coalition males)

opencc-by-4.0Jan 2023View details →

Maryland private school websites' physical activity promotion

Excel file of 387 Maryland (USA) private schools' websites' mentioning of PE (the term physical education, PE teacher, PE curriculum, PE dosage) and physical activity (intramural physical activity, interscholastic sports, physical activity images)

opencc-by-4.0Jan 2023View details →

Private vehicles greenhouse gas emissions at street level for Berlin based on open data

We estimated the annual average daily GHG emissions from individual motor traffic for the OSM road network in Berlin by combining the estimated Annual Average Daily Traffic Volume (AADTV) with respective emission factors. The AADTV was calculated by simulating car trips with the open routing engine Openrouteservice, weighted by activity functions based on statistics of the German Mobility Panel.