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The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as “data factoring” emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing. The book proposes a research-development agenda that can undergird an ideal data factory approach. Several programmatic chapters discuss specialized issues involved in data factoring (documentation, meta-data specification, building flexible, yet comprehensive data ontologies, usability issues involved in collaborative tools, etc.). The book also presents case studies for data factoring and processing that can lead to building better scientific collaboration and data sharing strategies and tools. Finally, the book presents the teaching utility of data factoring and the ethical and privacy concerns related to it. Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com.

Computer science. --- Big data. --- Research --- Data mining. --- Application software. --- Bioinformatics. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Big Data/Analytics. --- Computer Appl. in Social and Behavioral Sciences. --- Research Ethics. --- Moral and ethical aspects. --- Data warehousing. --- Data sets, Large --- Large data sets --- Information warehousing --- Warehousing, Data --- Database management --- Management information systems --- Multidimensional databases --- Social sciences --- Research-Moral and ethical aspec. --- Data processing. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data sets --- Data processing --- Research ethics --- Research—Moral and ethical aspects. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software