SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Information and Knowledge for Data Reuse Lessons from Ecology Ann Zimmerman

What do ecologists and organizations have in common when it comes to sharing data? A lot!

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Ecology Ecology is a “craft” science Single investigators conduct small scale studies Data sets are highly diverse Standard methods are difficult to achieve There is a high level of data ownership

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Standards as Distance Spanners Theodore Porter (1992, 1995) – Quantification as a technology of distance – Standards as a substitute for trust Bruno Latour (1999) – Standard measurements involve a loss of information (reduction) – Reduction turns local knowledge into public knowledge (amplification)

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Factors that Influence Research Methods The scientific question The environment of the study The taxa to be studied Practical considerations: time, money, and skill

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Gathering One’s Own Data Helps with Reuse Ecologists’ experiences as collectors of their own data in the field or laboratory plays an important role in their secondary use of data

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Data Gathering Provides: The ability to understand data The ability to recognize data limitations The ability to visualize potential points of error A ‘sense’ for data

Image from: Using a clinometer to measure tree height Understanding Data

Understanding Data Limitations What frog species live here?How many frogs live here?

Images from: Copepods/Copepods.html Identifying Points of Potential Error

Images from: familyBrachionidae Brachionus variabilis Hempel, 1896Brachionus calyciflorus Pallas, 1766 Identifying Points of Potential Error

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Gaining a ‘Sense’ for Data Nancy: “When you’re in the field, most of what you learn is not the data points you’re collecting – it’s just that sense.” Michael: “The more you actually go out and do these things the more critical you are of the data.”

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Relevance of Findings to Settings Outside of Science Reusing data is hard, and it requires a lot of knowledge Standardization of methods is only part of the solution to address challenges of data sharing It’s important to find ways to incorporate articulated tacit knowledge into data sharing systems