Resources for Researchers¶
Systematic literature review¶
Parsifal is an online tool designed to support researchers to perform systematic literature reviews within the context of Software Engineering. Geographically distributed researchers can work together within a shared workspace, designing the protocol and conducting the research.
As well as providing a way to document the whole process, the tool will help you remind what is important during a systematic literature review. During the planning phase, Parsifal will help you with the objectives, PICOC, research questions, search string, keywords and synonyms, selecting the sources, the inclusion and exclusion criterias. Will also provide mechanisms to build a quality assessment checklist and data extraction forms.
During the conducting phase, you will be able to import bibtex files and select the studies, find duplicates among all the different sources, execute the quality assessment and extract data from the papers.
Advanced Information Research Skills (AIRS)¶
Advanced Information Research Skills (AIRS) is a coursework for Higher Degree Research (HDR) students enrolled in a Doctor of Philosophy (PhD) or Master of Philosophy (MPhil) at Queensland University of Technology (QUT), Australia. The curriculum content is openly accessible, creative commons licensed and available for use by all.
The curriculum includes:
formulating a good research question
advanced search strategies
sourcing and evaluating quality literature
bibliographic and data management
note-taking strategies
citation analysis and research impact
collaboration tools
authorship and academic integrity
publishing and pathways.
Researcher Academy¶
Researcher Academy provides free access to countless e-learning resources designed to support researchers on every step of their research journey. Browse our extensive module catalogue to uncover a world of knowledge, and earn certificates and rewards as you progress.
RESEARCH PREPARATION
Funding
Research data management
Research collaborations
WRITING FOR RESEARCH
Fundamentals of manuscript preparation
Writing skills
Technical writing skills
Book writing
PUBLICATION PROCESS
Fundamentals of publishing
Finding the right journal
Ethics
Open science
How to publish in premium journals
Publishing in the Chemical Sciences
NAVIGATING PEER REVIEW
Certified Peer Reviewer Course
Fundamentals of peer review
Becoming a peer reviewer
Going through peer review
COMMUNICATING YOUR RESEARCH
Social impact
Ensuring visibility
Inclusion and Diversity for Researchers
Reference managers¶
Reference managers help collect, organize and share references and create citations in various formats. Mendeley and Zotero are free reference managers.
Datasets¶
Mendeley¶
Mendeley Data is a secure cloud-based repository where you can store your data, ensuring it is easy to share, access and cite, wherever you are.
Search 28.1 million datasets from domain-specific and cross-domain repositories.
OpenML¶
The Open Machine Learning is a public repository for machine learning data and experiments, that allows everybody to upload open datasets. It integrates with scikit-learn.
Example:
from sklearn import ensemble
from openml import tasks, flows, Runs
task = tasks.get_task(3954)
clf = ensemble.RandomForestClassifier()
flow = flows.sklearn_to_flow(clf)
run = runs.run_flow_on_task(task, flow)
result = run.publish()
Key features:
Query and download OpenML datasets and use them however you like
Build any sklearn estimator or pipeline and convert to OpenML flows
Run any flow on any task and save the experiment as run objects
Upload your runs for collaboration or publishing
Query, download and reuse all shared runs
Tensorflow Datasets¶
Tensorflow Datasets (TFDS) provides a collection of ready-to-use datasets for use with TensorFlow, Jax, and other Machine Learning frameworks.
https://www.tensorflow.org/datasets/catalog/overview
Google Research¶
Google periodically releases data of interest to researchers in a wide range of computer science disciplines.
Google dataset search¶
Google provides a search engine for datasets. Discover datasets hosted in thousands repositories.
PyTorch¶
Torch Audio: https://pytorch.org/audio/stable/datasets.html
Torchvision: https://pytorch.org/vision/stable/datasets.html
Torch text: https://pytorch.org/text/stable/datasets.html