Although the terms “sector” and “industry” are often used interchangeably to describe a group of enterprises that “operate in the same segment of the economy or share a similar business type,” they do actually have slightly different meanings. Here, we also adopt the terminology used in the stock market in referring to a sector as the broader classification. In addition, the terms “domain” and “field,” used in Chapter 6, are most often used to designate an area of professional specialization.
Currently, enterprises or organizations that own or control data resources do not participate in data innovation. In fact, because of the usual barriers to entry, it may not be possible or realistic for them in the sectors to join in making data innovations. As Kevin Kelly wrote in his book Out of Control: The New Biology of Machines, Social Systems, and the Economic World, we might apply “bee thinking” as well in referring to the data industry, and crowdsource projects using a “mini-plant” groups consisting of 8 to 12 persons, so as to realize such a “distributed, decentralized, collaborative, and adaptive” “co-evolution.” Transboundary (or trans-sectoral) cooperation, therefore, can be consider as an important means of discussing possible future direction for data services like the issues of fostering SMEs and entrepreneurship development. We know all the scenarios in this chapter will prove beneficial to transboundary cooperation.