51��������

By Vanessa Raymond
Feb. 17. 2023

Often what lies behind a dataset is a story, or a set of stories. Sometimes, it’s an epic saga complete with heroes, foes, trials and tribulations. Like all great stories, there are periods of woe and periods of triumph. Data stories are inextricable from human stories, with all the high drama that accompanies funding cycles, trends in research, and the crucial role that charismatic, passionate movers and shakers can have. 

Working with data, as dry as that may sound to some, is actually quite an emotional process. Anyone who has spent any amount of time creating or collecting data, analyzing it, managing it, describing it, sharing, or re-using it can tell you how frustrating and exciting the process is. The challenges may stem from an ethical concern, a data quality concern, or a technical concern. Below read three data vignettes, accompanied by some bigger picture framing from data academics, featuring some of ACEP’s data champions: Michelle Wilber, Emily Richmond, and Dylan Palmieri.

Michelle Wilber, an ACEP researcher describes the care and caution she brings to her data work on electric vehicles in Alaska:

Michelle describes how ACEP researchers, through their relationships and networks, maintain the trust of research partners and collaborations by protecting the people behind the data. Michelle also touches on the fact that when a larger spotlight is shone on research, the tools and techniques for managing the data may need to change to address the change in the scale of the interest, or the politicization of a research topic.

ACEP researchers seek to go above and beyond the requirements with their data relationships and networks, because, sometimes, behind the data we find the faintest whispers of peoples’ lives. Proceeding with caution, care, and empathy is the only just way to approach this. Wilber describes how even with powerhouse data, data that comes from an electric utility about the electrical output of the powerhouse, we can have a people-centric approach.

This situation illustrates how, even when we are using powerhouse data from communities we firmly believe that data belongs to the people who created it and the organization who shared it. Beyond just the personal protections, there’s the whole other challenge to ensure we are supporting energy sovereignty. At that level it’s not just personal data, it’s a relationship we try to make sure it’s respectful of another entity in total, be it a tribal council or community. 

Michelle’s work echoes the thinking and cautioning of the biggest thinkers in data ethics, such as Kate Crawford, who speaks about the new harms introduced by big data and data science, challenging traditional research ethics guidelines:

Sometimes, the data story is just one of cleaning, or fixing. Like tinkerers outside of the data sphere, the headaches are numerous, unexpected, and can be quite vexing. ACEP’s data science analyst, Emily Richmond, is super annoyed with data right now. Why? Well she just discovered that some (but not all) of the data points she has been building an analysis off of are off by a decimal point. She vents because, to put it simply, she needs the story behind the data just as much as she needs the data itself.

Emily’s challenge is a familiar one in the data world. We inherit a dataset that’s incredibly valuable, however we don’t have the decoder ring - we can’t understand or verify how the data was made, that the data is accurate, and what decisions were made along the way to result in this dataset. Without good documentation, metadata, and some standard best practices being employed, it sometimes renders valuable data insights unusable for statistical analysis or other data science pursuits, just because of the high degree of uncertainty the data product introduces into the research process. The gold standard for datasets is that we receive a source or raw data file, the script that did the analysis, the data product that comes from the analysis, and we also receive metadata about the dataset: the who, what, when, where, and why, or the data’s origin story.

Mimi Onuoha is a data artist who has written at length about missing data, and in her 2018 essay “What is Missing Is Still There” ² she attempts to define and describe data. 

Emily, in her work with ACEP, has chanced upon another type of data, the dataset that got forgotten. The data we used to care about, or perhaps that we used to be able to measure but can no longer.

ACEP’s Dylan Palmieri, Winter 2022 graduate of 51��������’s computer science master's degree program, is tackling a different data challenge right now. Dylan’s challenge is one of documentation. It requires digging deep, really deep, into the way some air quality sensors were designed to understand the way the data is being created by the sensor. And if that wasn’t hard enough, he then needs to write code to translate this data into a format that ACEP researchers can easily understand in order to analyze the data coming out of the sensors.

“I basically want to write this software so that no one, and I mean no one, ever has to do what I have had to do” says Dylan. “I guess we can call it data democratization. It shouldn’t require a degree in computer science to draw conclusions from this data.” He goes on to describe his process further:

Dylan’s work to fully understand a piece of hardware, write software and create data processes, and also document the way the data is structured and the outputs of the data is what makes research possible. It allows ACEP’s energy researchers and fuel cost research teams to focus on the analysis, bringing to bear all their subject matter expertise, to the research question at hand. This “invisible work” is also a time saving and cost saving measure that gets the data into a usable shape, without others also having to go down the rabbit hole later on.

Like Dylan, leading thinkers in data ethics, and specifically data feminists, are looking at this same concept of invisible work and data supply chains. Writes Catherine D’Ignazio and Lauren Klein in chapter “Show Your Work” from their 2020 book Data Feminism,

The dangers in invisible work is if it is also siloed work, work that researchers, funders, community partners, or university stakeholders don’t see or understand. In this context, the invisible work can be underestimated in terms of time it takes to get from raw outputs from a sensor to a beautiful and compelling data visualization, in terms of the cost for clean and preparing data, and in terms of the skills and human capacity needed on a data-capable research team, to produce reliable data assets for research activities that solve some of Alaska’s most complex and pressing questions about the shape of our world today, and in the future.

ACEP enters 2023 with a deep commitment to Alaska’s energy data ecosystem that extends beyond individual grants and research projects to create a broader network of support of energy data in Alaska, one of the most unique and data rich energy landscapes in the nation. Under the direction of executive director Jeremy Kasper and executive officer Jennifer Harris, ACEP is poised to hire a cohort of data experts including devops system engineers who can create and maintain a data infrastructure that allows ACEP researchers to more easily receive and rely on data collected across remote communities in Alaska, and data science analysts like Emily Richmond who can support research teams at ACEP to clean and analyze data. In addition to creating these positions, ACEP is also launching a new initiative to have a data librarian internship project as part of the ACEP Undergraduate Summer Internship (AUSI) program, pilot a data club for high schoolers, and engage a cohort of computer science students in data, geospatial, and programming tasks related to energy data. 

ACEP has also invested in a Data Governance Lead to facilitate the dynamic data rich environment of ACEP’s researchers.  The data governance lead’s role is to create a culture and norms around data decisions at all levels of ACEP’s research enterprise to create some consistent, best practices for ethical and, where appropriate, accessible energy data products that benefit Alaskan remote communities, Alaskan energy researchers, and researchers around the world. As part of this effort, ACEP has joined the Interagency Arctic Research Policy Committee (IARPC) as co-chair of the Data Management team.