Curation is the act of individuals with a passion for a content area to find, contextualize, and organize information. Curators provide a consistent update regarding what's interesting, happening, and cool in their focus. Curators tend to have a unique and consistent point of view--providing a reliable context for the content that they discover and organize. To be clear, Pinterest both creates tools to organize the noisy web and, at the same time, creates more instances of information in a different context. So it's both part of the problem, and a solution. The trick is finding the Pinterest pinboards that you like, and tune out the rest.

The Research Data Curation Bibliography includes selected English-language articles and technical reports that are useful in understanding the curation of digital research data in academic and other research institutions. For broader coverage of the digital curation literature, see the author's Digital Curation and Preservation Bibliography 2010.

"You Too Can Become a Data Scientist

So the bottomline is that there is big money looming. Fortunes will be made and lost. Which means you too should attempt to become a data scientist.

The skills have become increasingly easy to acquire, and are getting easier by the week. But at the same time, cultural barriers to people self-classifying into the data scene are being erected.

Redefine yourself while you can. Let me know if you need any pickaxes."

HealthMap, a team of researchers, epidemiologists and software developers at Children's Hospital Boston founded in 2006, is an established global leader in utilizing online informal sources for disease outbreak monitoring and real-time surveillance of emerging public health threats. The freely available Web site 'healthmap.org' and mobile app 'Outbreaks Near Me' deliver real-time intelligence on a broad range of emerging infectious diseases for a diverse audience including libraries, local health departments, governments, and international travelers. HealthMap brings together disparate data sources, including online news aggregators, eyewitness reports, expert-curated discussions and validated official reports, to achieve a unified and comprehensive view of the current global state of infectious diseases and their effect on human and animal health. Through an automated process, updating 24/7/365, the system monitors, organizes, integrates, filters, visualizes and disseminates online information about emerging diseases in nine languages, facilitating early detection of global public health threats.

Check the bibliography.
"DIPIR is an IMLS-funded project led by Dr. Ixchel Faniel and Dr. Elizabeth Yakel. Together with partners at The Inter-university Consortium for Political and Social Research, the University of Michigan Museum of Zoology, and Open Context, they are studying data reuse in three academic disciplines to identify how contextual information about the data that supports reuse can best be created and preserved. The project focuses on research data produced and used by quantitative social scientists, archaeologists, and zoologists. The intended audiences of this project are researchers who use secondary data and the digital curators, digital repository managers, data center staff, and others who collect, manage, and store digital information. Knowledge gained from the study will help guide current and future international practices for curating and preserving digital research data."

"CKAN is the Comprehensive Knowledge Archive Network, a registry of open knowledge packages and projects (and a few closed ones).

CKAN makes it easy to find, share and reuse open content and data, especially in ways that are machine automatable."

"Scientific publishing as it stands is an inefficient way to do science on a global scale. A lot of time and money is being wasted by groups around the world duplicating research that has already been carried out. FigShare allows you to share all of your data, negative results and unpublished figures. In doing this, other researchers will not duplicate the work, but instead may publish with your previously wasted figures, or offer collaboration opportunities and feedback on preprint figures."

"The decision highlights a tension between the need for rigorous peer review of scientific research and the desire to provide as much data as possible to the scientific community.

"More data, in and of itself, is always a good thing -- if there aren't adverse effects," said Maunsell, who is also a neuroscientist at Harvard University. But peer review was becoming less effective because many reviewers failed to evaluate the supplemental materials, which the journal wasn't even required to provide, he explained. "We were taking a hit on peer review for something that wasn't formally our responsibility." "

"The University of North Carolina at Chapel Hill found out last year that, in 2007, someone had hacked into a server holding personal information of 180,000 mammography patients from around the state. The hacker was never found or charged, and did not appear to have copied any of the data, which included 114,000 Social Security numbers. But the university tried to fire -- and is still trying to punish -- the researcher who was in charge of the information."

Anyway, I was asked to present a couple of slides on challenges for open access data repositories ... but clearly I don't believe that such challenges are independent of the science, so I produced a few more slides to give context

Long-term preservation and stewardship of scientific data and research-related information are vitally important to future science and scholarship. Scientific data archives can offer capabilities for managing and preserving disciplinary and interdisciplinary data for research, education, and decision-making activities of future communities of users. Meeting the requirements for a trusted digital repository will help to ensure that today’s collections of scientific data will be available in the future. A continuing self-assessment of a long-term archive for interdisciplinary scientific data is being conducted to identify the additional steps needed for it to become a trustworthy repository. Recommendations include a strategy for collaborative organizational sustainability, a model for submission and workflow to ingest interdisciplinary scientific data into a repository, and a plan for facilitating intra-organizational transfer between repositories.

In 2009, DPC with University of London Computer Centre and Portico carried out an extensive analysis for the JISC Digitisation Programme, examining the projects funded through this programme and assessing their plans for access beyond the existence of their project grants. A scaled down version of the report with analysis is published here and a number of case studies have also been produced.

That’s because it’s difficult to start an “open” biology process from scratch. The cost of entry is still in the tens of millions of dollars to develop a meaningful corpus of data sets one can legally share and analytic tools one can legally place under open source licenses. Even then you’d have to find incentives to get scientists to share their new data, their models of disease, their software tools—when they’re not rewarded for doing so. It is a tall hill to climb.

The OBO Foundry is a collaborative experiment involving developers of science-based ontologies who are establishing a set of principles for ontology development with the goal of creating a suite of orthogonal interoperable reference ontologies in the biomedical domain. The groups developing ontologies who have expressed an interest in this goal are listed below, followed by other relevant efforts in this domain.

My research passion is understanding the prevalence and patterns of research data sharing and reuse. I hope my work contributes to more efficient and effective research data reuse through improved incentives and mandates.

Digital data repositories ought to support immediate operational needs and long-term project goals. This paper presents the Dryad repository's metadata best practice balancing of these two needs. The paper reviews background work exploring the meaning of science, characterizing data, and highlighting data curation metadata challenges. The Dryad repository is introduced, and the initiative's metadata best practice and underlying rationales are described. Dryad's metadata approach includes two prongs: one addressing the long-term goal to align with the Semantic Web via a metadata application profile; and another addressing the immediate need to make content available in DSpace via an extensible markup language (XML) schema. The conclusion summarizes limitations and advantages of the two prongs underlying Dryad's metadata effort.

This paper was prepared as background for a talk given at AGU 2009 on “Data & Libraries.” It summarizes the developments and events from late 2006 through early 2010 that are shaping library roles in scientific data curation while underscoring the range, complexity, and varying granularity of systems, actions, and efforts involved. The main conclusions are: (1) leaders of major research libraries have committed their institutions to support data curation. (2) The library profession has demonstrated significant conceptual progress in characterizing and understanding data curation both in theory and in practice. (3) There has been progress since 2006 in legitimizing library roles in data curation through formal education and certification programs as well as by integrating data curation into established library services and systems.

Mark me well, incidentally: it is unreasonable and unsustainable to expect data archivists to build a whole lot of project-specific shiny stuff. You don't want your data archivists spending their precious development cycles doing that! You want your archivists bothering about machine replacement cycles, geographically-dispersed backups, standards, metadata, access rights, file formats, auditing and repair, and all that good work.

(Submitted on 7 Aug 2002)
Science projects are data publishers. The scale and complexity of current and future science data changes the nature of the publication process. Publication is becoming a major project component. At a minimum, a project must preserve the ephemeral data it gathers.

(Submitted on 2 Feb 2005)
This is a thought piece on data-intensive science requirements for databases and science centers. It argues that peta-scale datasets will be housed by science centers that provide substantial storage and processing for scientists who access the data via smart notebooks.

As digital technologies are expanding the power and reach of research, they are also raising complex issues. These include complications in ensuring the validity of research data; standards that do not keep pace with the high rate of innovation; restrictions on data sharing that reduce the ability of researchers to verify results and build on previous research; and huge increases in the amount of data being generated, creating severe challenges in preserving that data for long-term use.

Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age examines the consequences of the changes affecting research data with respect to three issues - integrity, accessibility, and stewardship-and finds a need for a new approach to the design and the management of research projects.

The National Biological Information Infrastructure (NBII) is a broad, collaborative program to provide increased access to data and information on the nation's biological resources. The NBII links diverse, high-quality biological databases, information products, and analytical tools maintained by NBII partners and other contributors in government agencies, academic institutions, non-government organizations, and private industry.

Parsons Journal for Information Mapping: A Quarterly Publication on Knowledge Visualization Theory and Practice

Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud computing technologies. In The Fourth Paradigm: Data-Intensive Scientific Discovery, the collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.

This page is a catalogue that will be kept up to date pointing to selected sources of code and data related to climate science.

Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age examines the consequences of the changes affecting research data with respect to three issues - integrity, accessibility, and stewardship-and finds a need for a new approach to the design and the management of research projects. The report recommends that all researchers receive appropriate training in the management of research data, and calls on researchers to make all research data, methods, and other information underlying results publicly accessible in a timely manner. The book also sees the stewardship of research data as a critical long-term task for the research enterprise and its stakeholders. Individual researchers, research institutions, research sponsors, professional societies, and journals involved in scientific, engineering, and medical research will find this book an essential guide to the principles affecting research data in the digital age.

The Data Audit Framework (DAF) provides organisations with the means to identify, locate, describe and assess how they are managing their research data assets. DAF combines a set of methods with an online tool to enable data auditors to gather this information. DAF will help ensure that research data produced in UK Higher Education Institutions is preserved and remains accessible in the long term.

The main aim of the project was to examine and make recommendations on the role and career development of data scientists and the associated supply of specialist data curation skills to the research community.

Alma Swan, in a report well worth reading, posits four kinds of data-curation staff: data creators, data managers, data librarians, and data scientists. I'm not sure how far I can go with that. I agree with the skillsets as Swan lays them out; I'm just agog at the idea that any institution or research shop will be able to divvy up these tasks among four whole people!

TalkScience is a series of events hosted by the British Library, providing opportunities to inform, engage, debate and network with scientists and all those who use scientific information.

When even scholars wanting to do the right thing and hand off their work to a responsible party cannot find anywhere to go, when enabling digital communication and the preservation of its results is an altruistic act in libraries instead of the bedrock of our mission, when worthy digital projects die because we in libraries do not notice and reach out to them, when we ourselves can't see our way clear to sustaining digital materials… we have a serious systemic problem.

As digital technologies are expanding the power and reach of research, they are also raising complex issues. These include complications in ensuring the validity of research data

VisTrails is an open-source scientific workflow and provenance management system developed at the University of Utah that provides support for data exploration and visualization.

A hierarchy of needs for data-curation: acquisition, physical medium, bitrot, format viability, usability, fidelity to original.

"Data curation," as it is often called, is my major professional interest in the e-research firmament, so you can expect to see it discussed often here. I am partial to Melissa Cragin's definition: "the active and ongoing management of (research) data through its lifecycle of interest and usefulness to scholarship, science, and education."