"Happiness is
like a cloud, if you stare at it long enough, it evaporates” --
Sarah McLachlan (Canadian Singer and Songwriter, b.1968)
While Google® makes it easy to search for virtually anything you need to know
about laboratory design, the one thing you won’t find is the importance of good
library support. From
the Library to the Laboratory: A New Future for the Science Librarian
(https://net.educause.edu/ir/library/pdf/PUB7202r.pdf)
is a notable exception.
It is one chapter in a larger work:
The Tower and the Cloud: Higher Education in the Age
of Cloud
Computing
Richard N. Katz, Editor
2008 EDUCAUSE
ISBN 978-0-9672853-9-9
Free Full Text Source: http://www.educause.edu/research-and-publications/books/tower-and-cloud
Mary Marlino and Tamara Sumner, the authors of From the Library to the Laboratory: A New Future for the Science
Librarian? describe the challenges facing researchers and the librarians
who support them.
Here is an excerpt from From the Library
to the Laboratory.
///////
From the Library to the Laboratory: A New
Future for the Science Librarian?
Mary Marlino and Tamara Sumner
The mission of academic libraries is to support research, education, and scholarship.
Historically, libraries have supported this mission by organizing and providing
access to information, curating and preserving special collections, and
creating physical spaces for collaboration and scholarship. While the broad
mission of academic libraries is largely unchanged, transformations in
technology, media, and culture are driving fundamental changes in the
production and consumption of information and the practice of scholarship. As a
result, academic libraries are rethinking their strategies and services to meet
the challenges of the digital world and the demands of the “born digital”
generation.
Science libraries, in particular, are confronting these challenges as the
nature of scientific practice is being dramatically transformed by information
technologies. These technologies enable scientific data to be collected,
distributed, and archived on an unprecedented scale. The challenge of
collecting, managing, and providing access to information not traditionally
curated by libraries is compounded by the sheer volume of data, issues of
interoperability, documentation, acknowledgment, and authentication.
The term e-science is often used to describe new forms of data-driven science
enabled by information technologies. Data-driven science is characterized by
the analyses of increasingly large quantities of data from distributed sources.
E-science methodologies include the identification and visualization of
patterns, anomalies, and trends from the mining and analysis of data, coupled
with the ability to share the results of analysis processes through the
immediacy of the Internet. Within the United States, the term
cyberinfrastructure is often used interchangeably with e-science.
Currently, e-science is often associated with “big science,” that is, large
national or international projects such as the Terragrid, the Biomedical
Informatics Research Network (BIRN), or the Linked Environments for Atmospheric
Discovery (LEAD) project. These projects are developing sophisticated,
distributed technical infrastructures, often based on “grid” technologies,
which support domain-specific tools and services facilitating data acquisition,
data analysis, and data management. This infrastructure is often housed at
major research facilities or national laboratories, and user access to these
advanced research services is managed by these groups and made available to
individual researchers through the project portal.
Data-driven science, however, is not confined exclusively to these large
disciplinary efforts. A closer look at what is happening on university campuses
and in small research labs today reveals that e-science practices are
increasingly common and being applied to a wide range of scholarly endeavors in
the sciences, social sciences, and humanities.2 For instance, a master’s thesis
in urban planning examining the correlation between indigenous plants, property
prices, and neighborhood activism may draw on diverse data sources—such as the
university’s special herbarium collection, the county property tax records and
land use data, and records of local voting behaviors—to create an innovative
geographic information visualization that can be used by policy makers debating
future planning scenarios. In this case, the student is not using custom, discipline-specific
e-science tools but is leveraging increasingly available Web 2.0 capabilities;
that is, many organizations are now routinely exposing data through public APIs
and web services. Tim O’Reilly highlights this “innovation by assembly”
phenomenon as a key Web 2.0 principle, commenting that “… when commodity
components are abundant, you can create value simply by assembling them in
novel or effective ways.”
Promises and Challenges for Science
Libraries
The examples above illustrate both the promises and the challenges facing
e-science and libraries. The promises include the following: the potential for
new scientific discoveries that are possible only through large-scale,
computational analyses; a new era of transparency and replicability in scientific
methods and results; and the potential for widespread democratization of
scientific research, given the increasing ubiquity of open access data sources
and protocols. However, hidden in these examples are several challenges for
universities and their libraries.
The first challenge concerns the sheer volume of scientific data. In the LEAD
example, how does our scientist locate the required data from the various
ground stations and radars? In the master’s thesis example, how does the
student locate the multiple data sets distributed across local government and
university servers?
The second challenge concerns data interoperability. In the LEAD example,
merging data from different sources into a uniform data collection requires
significant, specialized expertise in all the different data formats and a
small army of graduate students. The thesis example, on the other hand,
illustrates a new form of scholarly literacy: namely, students need
“lightweight” programming skills to combine and remix data from multiple
sources.
The third challenge relates to preserving and documenting the intermediate
products. Whose task is it to save these intermediate products for posterity
and to document them so that others can find and reuse them? In the LEAD
example, what is the university library’s role in selecting and preserving
original and derivative data sets for future reanalysis? In the thesis example,
the student has created a richly annotated version of the library’s special
herbarium collection, adding new information about the geographic locations of
particular species. How does the library incorporate this user-generated
content back into its carefully managed special collection?
Finally, the demands of digital scholarship are requiring new levels of
documentation, acknowledgement, and authentication that are often beyond the
immediate capabilities or interests of faculty or students. In the LEAD
example, when the researcher’s final report and associated data and artifacts
are put into the university’s institutional repository, who will be responsible
for ensuring that the university has the appropriate intellectual property
rights to post and disseminate this information? In the thesis example, the
student’s thesis consists of written documentation, software codes for the
visualization, and several public data sets. Many campus libraries are tasked
with preserving and archiving student theses and dissertations. Again, as in
the LEAD case, the library will be challenged to develop stewardship policies
and procedures to support the archival and preservation demands of multimedia
forms of scholarship.
New Roles for University Libraries
As a first step, libraries should prioritize making the collections that
they manage available to library users through open and documented web service
protocols supporting programmatic access to both primary content and metadata.
Currently, most libraries support individual users to access collections only
through manual, query-driven interfaces. For instance, access to the herbarium
collection used in the master’s thesis is probably available only through a
special web interface enabling users to search the metadata records using
keywords and other criteria to generate a fairly traditional list of search
results. However, for data-driven science, students and faculty need to be able
to run computations over the entire collection and not just access individual
records. The visualization created as part of the master’s thesis is a
relatively simple, yet still challenging, example. In this case, the student
wants to construct a visualization that enables users to select a geographic
area and view all of the different kinds of plant species located in that area;
that is, the visualization needs to dynamically query the library’s collection
and repackage this information as appropriate for this special application.
Today, many of the systems that libraries have put in place to enable access to
collections are simply not architected to support programmatic access of any
kind, thus severely limiting the usefulness of library collections for these
new forms of scholarship.
Libraries are increasingly being asked to play a leadership role in helping
universities capture and organize their intellectual assets, such as faculty
publications, student dissertations, project reports, and scientific data sets.
As illustrated in our examples, the library is often called on at the end of
the scholarly process: the researcher needs to include the final report in the
institutional repository, or the student has graduated and the dissertation
needs to be archived. At this point in the cycle, it takes a significant amount
of time, effort, and expense to examine each multimedia scholarly artifact,
parse out the constituent components, and decide which of these should be
preserved. Too often, libraries are called upon to make these decisions on a
case-by-case basis.
E-science and Web 2.0 technologies are promoting and enabling scholars to
create new works that build on data from multiple sources. As described in our
examples, viewing these works and archiving these works can potentially infringe
on the intellectual property rights of the creators of the original data sets.
As libraries take on responsibilities for hosting and/or archiving these new
works, they will also need to take on new responsibilities for rights
management. Specifically, library staff must develop expertise in tracing
intellectual property rights, negotiating clearances as appropriate, and
communicating the rights and terms of use of digital artifacts to library
users. Traditionally, these activities have been the purview of legal
departments. However, as new forms of scholarship proliferate, relying on the
university’s legal counsel will not scale and will be very expensive.
Conclusion
The discussions above illustrate many of the major challenges on the horizon
for academic libraries in the years ahead. Libraries have an opportunity to
build on their significant collections and content, their expertise in
information management, and their historical role in supporting scholarship to
become essential players in e-science in the academic enterprise. Barriers
along the way include lack of leadership and vision, the more pedestrian issues
of lack of technical expertise and money, the strategic pitfalls of inadequate
long-term planning, and the all-too-human tendency to keep doing what you know
how to do and not acknowledge that the world has changed.
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TIP #1: When designing your lab,
consult with a librarian to help create an environment in which your
researchers have access to the services only a library can provide.
TIP #2: Google using the search string: librarian research laboratory. Then
browse through the results to explore how academic and government research
libraries support their research talent.
This is the final post of the TIPSTARTALAB series. Visit http://www.jeansteinhardtconsulting.com/
for more tips on how to maximize the effectiveness of your online research.
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