availability of automatic language translation tools Reaching people across geographical, cultural and linguistic boundaries requires translation. For example, a large proportion of basic information on the web is not accessible to Arab speakers. Sharing and leveraging open data will be limited if there are not tools that enable translation. Beyond the direct and obvious linguistic translation, this may include cultural differences, such as what units are used on data.

more coherent data standards For disparate data sets to be able to “talk to each other”, to be used in the same analysis, and be used to drive new discovery, they must be combinable. That requires standardization. Data standards have traditionally been very difficult to implement because people are always coming up with new data-types. Open, flexible standards are essential to enable truly Vibrant data.

degree which UI design enables participation by diverse groups As basic performance capabilities - computing power, networking, even the power of analytics tools - increase, the world will see a shift in emphasis from simple performance to a better design of that performance to fit the needs of real people. UI design is an important element in making the power of technology fit with the ways of learning, the language, the visual skills and other characteristics of real people.

proportion of the population that is functionally data literate Refers to the ability of people who understand enough about data and analysis to derive real value from it. Finding patterns and meaning in data will be simplified with the development of new analysis and visualization tools. The proportion of people who are “data literate” will drive the rate of development of tools that make it easier for people without a lot of specialized training to analyze data for meaning.

degree to which underlying technologies and data are invisible Some may want to explore all that is possible with a given tool, while others may want to just use the basics. Design plays a key role in enabling novices to immediately understand the use of a given technology or data set, while enabling deeper explorations over time. By artfully hiding or exposing details and functionality, designers will enable more people to share and use data in ways that suit them.

ability to easily manipulate data granularity Tools that enable the manipulation of data granularity enable people with different skills and interests to look at common data sets in their own way. Sometimes, it is important to dig into the details. Sometimes, it is more appropriate to just have a “bird's eye view”. The more our data analysis tools can accommodate both ways of looking (and those in between) the more likely that more people will find value in them.

ease to users of managing personal data access permissions Another issue refers to the importance of putting flexible tools for assigning data access permissions in the hands of people, not large institutions (reference “ability to control data access permissions”). These tools must involve a minimum of effort and management overhead on the part of individuals and be largely automated, otherwise they will be too complicated to be useful.

level of clarity, simplicity, and utility of data created by sensors Many sensors today gather data in ways that are either proprietary or idiosyncratic. We need new methods for sensor data to be made more easily accessible and understandable from the very moment it is first created. This may be through improvements of devices themselves or through methods that automatically format and make available data by way of post-processing.

degree of platform openness (copy and modify) Openness here is defined as free to copy and change. Open source has been a major enabler for many organizations to collaborate, share and leverage expertise. It enables innovation and local cultural relevancy people adapt tools and technologies to local needs. Similarly- by allowing the open sharing of data, and (appropriate) modification of information such as meta-tags, the utility of a database can be improved tremendously.

legal/policy framework for personal digital rights management People will not be willing to openly share their personal data unless they have assurances that their privacy will be protected. Current privacy agreements - implemented by corporations and institutions - do little to assure people of the protection of their privacy. Legal and policy frameworks that return control over privacy to individuals, along with technology tools to help individuals manage those protections, will be vital for data vibrancy.

legal framework for accessing/ sharing copyright protected data Tight legal restrictions limit peoples ability to work with and build on the data of others. Too often, such restrictions favor powerful enterprises, who “lock down” access. Without any restrictions, however, people may not be willing to share personal data for fear of violations of privacy. Legal frameworks require a balance between openness and individual protections, without those protections becoming a tool for abuse by powerful interests.

proportion of data from large institutions that is accessible While data is much more easily shared, laws, institutional power, access to technology and other resources can create barriers to openness and transparency. Even in highly democratic societies, large firms and institutions have the means to gather information about individuals (for advertising, or surveillance). Real data vibrancy will only occur when this one-sided approach to data gathering and possession gives way to much broader circulation of data.

reputation system that engenders trust among participants People who remotely collaborate need tools to assess the trustworthiness of others they share data with. Reputation systems have been developing online, and many firms are working on generalized reputation scores that apply across domains. But beyond simple scores, people will need other tools, including assurances about recourse in the event that trust is breached, in order to feel safe sharing information broadly.

concentration of data and access to data in few corporations Large, consumer-facing companies guard consumer data they collect. On the one hand, it means that corporations might protect those data from abuse. On the other hand, this hoarding of data reduces the chances for people to discover unexpected new meaning and value.

tools to anonymize sensitive data Tight legal restrictions limit peoples’ ability to work with and build on the data of others. Too often, such restrictions favor powerful enterprises, who “lock down” access. Without any restrictions, however, people may not be willing to share personal data for fear of violations of privacy. Legal frameworks require a balance between openness and individual protections, without those protections becoming a tool for abuse by powerful interests.

ease of adding to / modifying metadata Metadata is information about data - descriptions of context, characterizations, labels, all ways that help people know what a data set or element is, and how it might be used. Metadata is a key component to make data sets more compatible and useful across boundaries. Therefore, we need open systems that allow metadata to be modified appropriately.

ability to control data access permissions As data access becomes more open, people will need the means of setting personal data permissions. Current data permissions systems (e.g., those provided by online services or corporations with regards to personal data) are not nearly flexible or powerful enough, and generally favor the corporation as “owner” of the data. This will obviously have to change for people to willingly share and circulate their data in a more open way.

availability of suitable sensors Most smart phones have many sensors on them - GPS, accelerometers, cameras, microphones, etc. A more vibrant ecology of data creation will depend new types of affordable mobile sensors to collect data in new ways - for instance, after the 2011 earthquake in Japan, small mobile radiation sensors deployed by citizens were critical to mapping radiation plumes around the Fukushima power plant.

reduction in cost of computation Since the late 1960s computing performance has continuously doubled in power every 18 months, while the cost per unit of computing has dropped precipitously. This is a factor that will continue to fuel the growth of open and vibrant data exchange, as more and more people can ultimately afford to access computing power - and thus, digital technology.

reduction in cost of networking and storage Network access in more remote - and usually poorer - parts of the world remains an acute issue. As with the cost of computing, digital storage technologies continue to decline in price and increase in power. Solid state storage devices promise to provide a more robust option for small devices, while new, open standards for servers have created a proliferation of storage “in the cloud”.

computational power of small devices Since the late 1960s computing performance has continuously doubled in power every 18 months, while the cost per unit of computing has dropped precipitously. This is a factor that will continue to fuel the growth of open and vibrant data exchange, as more and more small devices become increasingly powerful computers. Right now, an average smartphone has more computing power within it than was used in the entire Apollo moon landing.

proportion of population with access to information infrastructure For people to openly exchange data and build on each others' insights, a very basic ingredient is simply access to technology and digital data. “Cloud” based storage, smart phones, wireless networking technologies and many other factors have made this a reality for an increasing number of people, but remote and poorer regions of the world still lack that basic access. As access increases, so does vibrancy.