Big Data Era: Not just More Data but New Kinds of Data

One aspect of 21st century data literacy is realizing that there is not just more data, but also that there are new kinds of data.

There is a significant shift from the model where ‘all data is salient,’ for example, each entry on a calendar is a relevant appointment, to a model of being able to recognize different kinds of data and appropriate actions related to specific data types. The focus level upshifts to the correlation, trend, and anomaly level of big data abstractions rather than on the unitary level of the data flows themselves.

Daily quantified self-tracking data for example may be useful from a longitudinal perspective and might not need to be reviewed unless there is an anomaly. Another example is that the relevant action might be looking for correlations across multiple data streams. There could be potential linkage between coffee consumption, social interaction, and mood per as this Sen.se multiviz project investigates, finding some correlation between social interaction and mood. 

Discussed at greater length in: Swan, M. Sensor Mania! The Internet of Things, Wearable Computing, Objective Metrics, and the Quantified Self 2.0. J Sens Actuator Netw 2012, 1(3), 217-253.

Polyamory – an Anti-Scarcity Relationship Model for the Future

The first International Academic Polyamory Conference was held in Berkeley CA February 15-17, 2013 with approximately 100 attendees. Polyamory is the practice, desire, or acceptance of having more than one intimate relationship at a time with the knowledge and consent of everyone involved. It is not new or revolutionary that individuals may be involved with more than one other party; what is new is the openness, acknowledgement, and support and encouragement of the situation.

A number of academic studies were presented by researchers from around the world regarding the practice of polyamory. Polyamory is a niche, but increasingly becoming a defined field of sociology research. Theory papers and discussion drew on social movement theory, queer theory, intimacy theory, performance theory, and other aspects of philosophy and sociology. Other conference tracks discussed public education, experiential aspects, and legal and political issues. Some common themes were the notion of plurality and choice in relationship models and a superior level of communications mastery and emotional intelligence.

Plurality of Relationship Models 
There may be many relationship models aside from traditional normative monogamy. One only has to look at the fluidity and nuance in the reality of lived existence to see different kinds of relationships. There is the notion of bringing other relationship models into the light for greater legitimacy under the umbrella that would include monogamies and non-monagamies. Any individual may have an almost endless stream of potential demographic self-identifications to make in the categories of Race, Ethnicity, Religion, Gender, Sexuality, Relationship Model, and other categories. Each category has a plurality and range of possible answers and it would be considered discriminatory and inappropriately normative to privilege any specific identification.

Emotional Mastery 
There may be a belief that polyamorous individuals have a silver bullet and do not experience jealousy and other challenging emotions often occur in relationships. This is not at all the case. The polyamory community has not mastered jealousy, but it is often true that individuals are in trying on an ongoing basis to master communication with the self and others. Individuals in polyamorous relationships may have more experience, permission, and tools at their disposal for recognizing, acknowledging, and managing jealousy and other emotions that arise in human relationships - poly people may be more skilled at dealing with the situation.

Core 21c Skillset: Data Literacy

A core 21st century skillset is data literacy, meaning the ability to recognize, understand, and manipulate various forms of data. One way is through visualization, using visual techniques to both represent data, and also as an inquiry tool for finding patterns.

Some of the basics of data visualization are being able to distinguish between ordinal (qualitative) and quantitative data, and selecting corresponding plotting techniques. For example, a bar chart may be best for displaying simple quantitative and ordinal values, a scatterplot for multiple quantitative data values, and a shape-based plot chart for multiple ordinal values.

Beyond the basics, the next step is mastering more sophisticated visualization techniques. Some of these build on information visualization pioneer Edward Tufte’s work and include using small multiples (plotting several similar charts to highlight differences in one variable), bullet charts, sparklines, horizon charts, and adding a dynamic element to visualizations.

Quantified-self Experimentation Platforms

In the burgeoning Quantified Self (QS) movement, one recent trend is the emergence of tools explicitly for the conduct of QS experiments, either individually or in groups. These tools offer the rapid design and launch of experiments, and usually some degree of automated operation, data analysis, and recruitment.

On the mobile platform, there is PACO, the Personal Analytics Companion for the design and operation of private or shared personal science experiments. Another tool is studycure, an online platform that allows users to create and run interactive experiments using simple if/then logic to help users design experiments.

Community self-experimentation networks also exist, such the health collaboration community Genomera where professional researchers, non-profit groups, and individuals run studies examining a range of issues such as sleep quality, vitamin deficiency, microbiomic profiling, empathy-building, and how the memory works.