Critic's Choice Essay: Virtual Herbaria Come of Age
(First paragraph of article.) These are exciting times for natural history collections. An international effort is underway to make images and data of biological specimens available in electronic format via digitization. These initiatives are an effort to bring natural history collections out of the dark of museum and herbarium cabinets and into the light of public access for use by stakeholders in government, academia, biodiversity organizations, business, and K-12 education. The democratization of information contained in natural history collections through images and online databases is an important new development to better investigate our natural world and solve important social and environmental problems (Scoble 2010).
The US Virtual Herbarium: working with individual herbaria to build a national resource
Abstract The goal of the US Virtual Herbarium (USVH) project is to digitize (database, image, georeference) all specimens in all US herbaria, enabling them to be made available through a single portal. Herbaria house specimens of plants, fungi, and algae, so USVH will offer a rich portrait of biodiversity in the US and in the other countries represented in US herbaria. Equally importantly, working towards this goal will engage people with herbaria and the organisms they house, expanding their appreciation of both the power of biodiversity informatics and the demands that it places on data providers while developing improved communication among those working in and with herbaria. The project is not funded but has strong support among those working in herbaria. It works through regional herbarium networks, some of which existed prior to the USVH project, while others are still in gestation. It differs from most digitization projects in its emphasis on helping those involved with herbaria become part of a national enterprise, an aspect that is seen as critical to creating the resources needed to develop and sustain the project. In this paper, we present some of the lessons we have learned and the difficulties we have encountered during the first few years of the project.
Understanding the 'Intensive' in 'Data Intensive Research': Data Flows in Next Generation Sequencing and Environmental Networked Sensors
Genomic and environmental sciences represent two poles of scientific data. In the first, highly parallel sequencing facilities generate large quantities of sequence data. In the latter, loosely networked remote and field sensors produce intermittent streams of different data types. Yet both genomic and environmental sciences are said to be moving to data intensive research. This paper explores and contrasts data flow in these two domains in order to better understand how data intensive research is being done. Our case studies are next generation sequencing for genomics and environmental networked sensors. Our objective was to enrich understanding of the ‘intensive’ processes and properties of data intensive research through a ‘sociology’ of data using methods that capture the relational properties of data flows. Our key methodological innovation was the staging of events for practitioners with different kinds of expertise in data intensive research to participate in the collective annotation of visual forms. Through such events we built a substantial digital data archive of our own that we then analysed in terms of three traits of data flow: durability, replicability and metrology. Our findings are that analysing data flow with respect to these three traits provides better insight into how doing data intensive research involves people, infrastructures, practices, things, knowledge and institutions. Collectively, these elements shape the topography of data and condition how it flows. We argue that although much attention is given to phenomena such as the scale, volume and speed of data in data intensive research, these are measures of what we call ‘extensive’ properties rather than intensive ones. Our thesis is that extensive changes, that is to say those that result in non-linear changes in metrics, can be seen to result from intensive changes that bring multiple, disparate flows into confluence. If extensive shifts in the modalities of data flow do indeed come from the alignment of disparate things, as we suggest, then we advocate the staging of workshops and other events with the purpose of developing the ‘missing’ metrics of data flow.