Introduction to open-data

Editor's Notes

• #4: Idea- experiment – data analyse and writing paper – finally time for some pizza while paper gets reviewed – paper: jeej, al your hard work dissapears
• #5: FROM DATA IN A SCIENTIFIC PIPELINE TO RESEARCH DATA LIFECYCLE Managing data in a research project is a process that runs throughout the project. Good data management is one of the foundations for reproducible research. Good management is essential to ensure that data can be preserved and remain accessible in the long-term, so it can be re-used and understood by future researchers. Begin thinking about how you’ll manage your data before you start collecting it.
• #6: Open data is data that is free to access, reuse, repurpose, and redistribute. The Open Research Data Pilot aims to make the research data generated by selected Horizon 2020 projects accessible with as few restrictions as possible, while at the same time protecting sensitive data from inappropriate access Data sharing restricted data to restricted organisations or individuals. Access to this data is usually restricted because it is sensitive in some way, either because it is personal or because its general release might cause security problems.
• #9: expiration date of mediums and data
• #10: GenBank is a sequence database released in 1982. being one of the earliest bioinformatics community projects on the Internet
• #11: The Bermuda Principles set out rules for the rapid and public release of DNA sequence data. The Human Genome Project, a multinational effort to sequence the human genome, generated vast quantities of data about the genetic make-up of humans and other organisms. But, in some respects, even more remarkable than the impressive quantity of data generated by the Human Genome Project is the speed at which that data has been released to the public. At a 1996 summit in Bermuda, leaders of the scientific community agreed on a groundbreaking set of principles requiring that all DNA sequence data be released in publicly accessible databases within twenty-four hours after generation. These “Bermuda Principles” (also known as the "Bermuda Accord") contravened the typical practice in the sciences of making experimental data available only after publication. These principles represent a significant achievement of private ordering in shaping the practices of an entire industry and have established rapid pre-publication data release as the norm in genomics and other fields. The three principles retained originally were: Automatic release of sequence assemblies larger than 1 kb (preferably within 24 hours). Immediate publication of finished annotated sequences. Aim to make the entire sequence freely available in the public domain for both research and development in order to maximise benefits to society.
• #18: Innovatiion and progres s. a collaborative effort to find the biological markers that show the progression of Alzheimer’s disease in the human brain. But we all realized that we would never get biomarkers unless all of us parked our egos and intellectual-property noses outside the door and agreed that all of our data would be public immediately.” , At first, the collaboration struck many scientists as worrisome — they would be giving up ownership of data, and anyone could use it, publish papers, maybe even misinterpret it and publish information that was wrong.
• #19: Prevents data loss: 80% of data is lost after 10 years. Data is fragile and reproducibility very difficult without data. 2, Maximize usefulness and built much more efficient on previous work: Maximize usefulness: organize, make understandable, reusable and avoid duplication. Preserves data for further research by organizing, Stop drowning in irrelevant stuff. Reproducibility crisis. 3. Fosters creativity, interdisciplinary use of data and meta-analysis 4, public participation in scientific research 5. Promote integrity and increases transparency: managing data is part of good research, avoid accusations of sloppy science 4. Data tend to have a (much!) longer shelf life than interpretation After accounting for other factors affecting citation rate, we find a robust citation benefit from open data.1
• #24: Interoperability: how can my data be combined with other datasets and used in other fields? Licensing: who can access my data and for what perpuse can it be used
• #26: 3 stars: You can manipulate the data in any way you like 4 stars: link to it, bookmark it, reuse parts of the data, combine with other data 5 stars: discover more related data,