Experiences in deploying metadata analysis tools for institutional repositories

Current institutional repository software provides few tools to help metadata librarians understand and analyze their collections. In this article, we compare and contrast metadata analysis tools that were developed simultaneously, but independently, at two New Zealand institutions during a period of national investment in research repositories: the Metadata Analysis Tool (MAT) at The University of Waikato, and the Kiwi Research Information Service (KRIS) at the National Library of New Zealand. The tools have many similarities: they are convenient, online, on-demand services that harvest metadata using OAI-PMH; they were developed in response to feedback from repository administrators; and they both help pinpoint specific metadata errors as well as generating summary statistics. They also have significant differences: one is a dedicated tool wheres the other is part of a wider access tool; one gives a holistic view of the metadata whereas the other looks for specific problems; one seeks patterns in the data values whereas the other checks that those values conform to metadata standards. Both tools work in a complementary manner to existing Web-based administration tools. We have observed that discovery and correction of metadata errors can be quickly achieved by switching Web browser views from the analysis tool to the repository interface, and back. We summarize the findings from both tools' deployment into a checklist of requirements for metadata analysis tools

Models for GTPase membrane cycling.

<p>The asterisk represents the product between binding rates and concentration of GDI (subscripts that carry the numbers 1 and 3) or effector proteins <i>Eff</i> (subscript 5). In all models presented, the numbers used as subscripts for the cycling rates are consistent: 1 stands for interactions between membrane bound GTPase and GDI; 2 for membrane cycling of the complex GTPase-GDI; 3 for interactions between cytosolic GTPase and GDI; and 4 for membrane cycling of GTPase free from GDI. A. Detailed model. B. GDI dependent and independent GTPase cycling. Rates with subscript “+” represent binding (to GDI, effector proteins or membrane). C. Apparent membrane dissociation rate (<i>k_offAp</i>) normalized by the GDI mediated dissociation rate <i>k₂₋</i> as a function of <i>K_D1</i>, <i>K_D5</i>, <i>GDI</i> and <i>Eff</i>.</p

Membrane fraction of Rac before and after increase in sGDI due to stimulus.

<p>A–C. Horizontal lines delimit <i>K_Dm</i> for minimum and maximum GEF/GAP based on values in Section Detailed model, for a cell with (B) Sfc/Vol = 0.544/µm, corresponding to NIH3T3 cells or the surface area of only the plasma membrane of β-cell, or (C) Sfc/Vol = 4.8/µm, corresponding to the surface area of both plasma and granular membranes of the β-cell. At time 0, <i>r0_f</i> = 0.28 (solid bold curve), and at 20 minutes <i>r0_f</i> = 0.57 (dashed black curve). Arrows represent effective trajectories that satisfy the 70% increase in sGDI and 40% decrease in cytosolic Rac. Arrow type for fold increase in dissociation constant between Rac and sGDI in comparison to unphosphorylated GDI (see text): 5, solid; 10, dashed; 100 (B) and 1000 (C), bold (solid and dotted). For solid arrowheads, GDI bound to Cdc42 was considered inert. White arrowheads consider the effect of phosphorylation of GDI bound to Cdc42. All arrows, 0.15 µM cytosolic Cdc42 bound to GDI, but for dotted, 0.25 µM. D) Transient translocation of Rac between cytosol (Rac_c), plasma (Rac_PM) and granular membranes (Rac_gr) due to change in K_DGDI only (cross), plus increased affinity for plasma membrane (star, b>0) and granular membrane (circle, c>0).</p

Dependence of fraction of GTPase at the membrane r0, membrane dissociation rate <i>k_offAp</i>, and fraction of active Rac on GDI concentration.

<p>A–B. effect of GEF/GAP ratio. C–D. Effect of Rac concentration, relative to experimental condition ‘wt’. Vertical lines: GDI concentration for ‘wt’ (solid), and for ‘wt−GDI’ (dashed). While the fraction of active Rac doubled for ‘wt−GDI’, the total amount of active Rac is the same when Rac concentration is decreased by half (curve with crosses relative to open circles).</p

Variables and parameters used in lumped and detailed models.

<p>Variables and parameters used in lumped and detailed models.</p

Model for analysis of fraction of GTPase at the membrane.

<p>A. Model for lumped variables and rates. The term in the dotted box includes effector bound GTPases. The dashed arrows represent the GDI mediated membrane cycling of GTPases. B–F. Fraction of GTPase at the membrane free from GDI as <i>ρ_Eq</i> ranges from 0 to 10. The upper contour corresponds to 9% fraction at the membrane, while the lowest line represents 89%. Each pair of neighboring lines is 10% apart in membrane fraction. When <i>ρ_Eq</i> = 0, all membrane bound GTPase is free from GDI (<i>r0</i> = <i>r0_f</i>). The total fraction of GTPase at the membrane <i>r0</i> is represented by the dashed lines when <i>ρ_Eq</i>>0.</p

Variables and parameters used in ‘Application to Rac cycling in pancreatic β-cells’.

<p>Variables and parameters used in ‘Application to Rac cycling in pancreatic β-cells’.</p

Analysis of FLIM images.

<p>Left: Fluorescence decay histograms acquired from artificial membranes stained with PY3304 (A), PY3174 (B) and PY3184 (C) showing longer lifetimes in ordered membranes (red) than disordered membranes (black). Middle: Plots of residuals from fitting fluorescence decay histograms. (D-F) Right: Fluorescence lifetime images of live HeLa cells stained with PY3304 (D), PY3174 (E), PY3184 (F). Images show an increased order at the plasma membrane in agreement with the spectral measurements and previously published results. Scale bar  = 10 μm.</p

Analysis of live HeLa cells.

<p>Left: GP images of live HeLa cells stained with PY3304 (A), PY3174 (B), PY3184 (C). GP images are in false color and run over the range indicated by the color bars to indicate a higher degree of membrane order (predominately colored red) in the plasma membrane compared to intracellular membranes (predominately colored green). Scale bars 10 µm. Middle: Histograms of the GP values obtained from GP images of live HeLa cells stained with PY3304 (A), PY3174 (B), PY3184 (C). Histograms obtained from ROIs for plasma membrane (red line) and intracellular membranes (black) were normalized to the total number of pixels. Right: Staining profile of Live HeLa cells. HeLa cells were incubated with PY3304 (A), PY3174 (B) and PY3184 (C) for 30 min. Confocal intensity images were acquired at 30 s, 10 min, 20 min, and 30 min after dyes were added. Images show complete staining of all cellular membranes after 30 min. Scale bars 50 µm.</p

Analysis of live Zebrafish embryos.

<p>Top: Histograms of the GP values obtained from GP images of live Zebrafish embryos stained with PY3304 (A), PY3174 (B), PY3184 (C). Histograms obtained from ROIs for plasma membrane (red line) and intracellular membranes (black) were normalized to the total number of pixels. Bottom: GP images are in false color and run over the range indicated by the color bars to indicate a higher degree of membrane order (predominately colored red) in the plasma membrane compared to intracellular membranes (predominately colored green). Embryos were stained with PY3304 (left), PY3174 (middle), PY3184 (right) excited by multi-photon excitation at 1040 nm for PY3304, 900 nm for PY 3174, 1000 nm for PY 3184. Scale bars  = 10 µm.</p