Content Matters Interview: The Montana State Library | The Signal
In this installment of the Content Matters interview series of the National Digital Stewardship Alliance Content Working Group we’re featuring an interview with Diane Papineau, a geographic information systems analyst at the Montana State Library.
In addition to a traditional role of supporting public libraries and collecting state publications, the Montana State Library (MSL) hosts the Natural Resource Information System (NRIS), which is staffed by GIS Analysts.
NRIS was established by the Montana Legislature in 1983 to catalog the natural resource and water information holdings of Montana state agencies. In 1987, NRIS gained momentum (and funding) from the federal Environmental Protection Agency and Montana Department of Health and Environmental Sciences to support their mining clean-up work on the Superfund sites along the Clark Fork River between Butte and Missoula. This project generated a wealth of GIS data such as work area boundaries, contaminated area locations, and soil sampling sites, which NRIS used to make a multitude of maps for reports and project management. Storing the data and resulting maps at MSL made sense because it is a library and therefore a non-regulatory, neutral agency. Making the maps and data available via a library democratized a large collection of timely and important geographic information and minimized duplication of effort.
GIS was first employed at NRIS in 1987; from that point forward, NRIS functioned as the state’s GIS data clearinghouse, generating and collecting GIS data. NRIS operated for a decade essentially as a GIS service bureau for state government; during this period, NRIS grew into a comprehensive GIS facility, unique among state libraries. In fact, in the mid-1990s, NRIS participated in the first national effort to provide automated search and retrieval of map data. Today, beyond data clearinghouse activities, MSL is involved with state GIS Coordination as well as GIS leadership and education. We also are involved with data creation or maintenance for 10 of the 15 framework datasets (cadastral, transportation, hydrography, etc.) for Montana, and also host a GIS data archive, thanks to our participation as a full partner in the Geospatial Multistate Archive and Preservation Partnership (GeoMAPP)—a project of the National Digital Stewardship Alliance (NDSA).
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GIS data creation is expensive. By preserving geographic data via archiving, we store that investment of time and money. GIS data is often used to create public policy. Montana has incredibly strong “right to know” laws so preserving data that was once available to decision makers supports later inquiry about current laws and policies. Furthermore, making superseded data discoverable and accessible promotes historically-informed public policy decisions, wise land use planning, and effective natural disaster planning to name just a few use cases. From a state government perspective, the published GIS datasets created by state agencies are considered state publications. Our agency is statutorily mandated to preserve state publications and make them permanently accessible to the public.
To guide us in this modernization, MSL developed data management standards, policies, and procedures that require data preservation using archivists’ best practices. I’ll discuss a few highlights from these standards that illustrate our particular organizational needs as a GIS data collector and producer.
In order to appeal to the greater GIS community in Montana, we decided to use more GIS-friendly terms in place of the three “package” terms from the OAIS model. We think of a Submission Information Package (SIP) as “working data,” a Dissemination Information Package (DIP) as a Published Data Package, and an Archive Information Packages (AIP), as an Archive Data Package.
MSL chose to take a “library collection development policy” approach to managing a GIS data collection rather than a “records management” approach, which makes use of records retention schedules. What this means is we’re on the lookout for data we want to collect—appraisal happens at the point of collection. If we take the data, we both archive it (creating an AIP) and make DIPs at the same time. The archive is just another data file repository, though a special one with its own rules. If the data acquired is not quite ready for distribution, we modify it from a SIP (our “working data”) to make it publishable. We do not archive the SIP.
Montana State Library Data Collection Management Flow
We’re employing the library discipline’s construct of series’ and collections and their associated parent/child metadata records, which is new to the GIS group here at MSL. In turn, that decision influenced the file structure of our archive. Though ISO topic categories were GeoMAPP suggestions for both data storage as well as for data discovery, MSL chose instead to organize archive data storage by the time period of content unless the data is part of a series (i.e. cadastral) or if it was generated as part of a discrete project and is considered a collection (i.e the Superfund data). Additional consistency and structure should also come from the use of a new file naming convention ().
MSL is archiving data in its original formats rather than converting all data to an archival format (i.e. shapefile) because each data model offers useful spatial characteristics that we did not want to strip from the archived copy. For archive data packaging, we use the Library of Congress tool “Bagger” and we specifically chose to zip all the associated files together before “bagging” to save space in the archive. Zipping the data also permits us to produce one checksum for the entire package, which simplifies dataset management and dataset integrity checking in the workflow. We decided not to use Bagger’s zip function for this because the resulting AIP produced an excessively deep file structure, burying the data in multiple folder levels. To document the AIP in our data management system, we’ve established new archive metadata fields such as date archived, checksum, data format, and data format version.
Part 1
http://blogs.loc.gov/digitalpreservation/2013/12/content-matters-intervi...
Part 2
http://blogs.loc.gov/digitalpreservation/2013/12/content-matters-intervi...