Citation: Du, Y. R. (2014, August 18). [Review of the book Data journalism: Mapping the future, by J. Mair & R. L. Keeble (eds)]. Journalism & Mass Communication Quarterly, 91(3), 599-600.
With vast amounts of data now openly accessible online, and the new infographic technologies available to visualize data, news media are increasingly making use of these valuable mines of data to source and produce their stories. Data journalism – the use of numerical data in the production and distribution of news – is an emerging subarea in our field but so far little has been written about it. Scholarly narratives on data journalism are still rare, not to mention published books devoted to this subject. The January 2014 release of Data Journalism: Mapping the future is a welcome addition to this nascent body of literature, after the seminal Data Journalism Handbook (2012).
Defining “data journalism” is not an easy task, given its confusion, or overlap at least, with “online journalism,” “digital journalism,” “computer-assisted-reporting (CAP),” “investigative journalism” and so on. The book sets out with its first section, “What precisely is data journalism,” to track the philosophical and conceptual foundation for data journalism as a stand-alone subject area. This collection of essays from four academics and industry experts certainly answers more questions than it raises. One may walk away with a “bio-like” understanding of the data journalism identity: Data journalism evolved from “precision journalism (which Phil Meyer has advocated since 1970s),” and is a development of CAP in the online context; it combines reporting with programming of data; its features may include interactivity, statistics, a multi-modular approach, and audience participation. Despite this wealth of information, the book asks questions that remain unanswered: Is it realistic to expect journalists to be programmers? Should all reporters be required to be data literate? Is data journalism good for the general public audience or for the elite audience only?
As mentioned in the book, the notion of journo-coder, programmer-journalist, hacker-journalist, or journo-programmer is still novel and the terminology is as yet undecided. When reporting meets programming, the many myths this marriage has generated are always debatable but that does not stop data journalism from growing. Section 2 of the book is particularly informative (and most valuable of all, in my opinion) with the tips on developing and updating data journalism skills given by media-industry specialists such as Jacqui Taylor, Daniel Ionescu, and Pupul Chatterjee. From here one gets a big picture of the state of data journalism in practice – how data are accessed, obtained; how they are processed and presented using ever-updating tools such as Excel, Tabula, Tableau, Import.io, Google Charts, D3, infogr.am, Datawrapper, Many Eyes, Easel.ly, etc.
A great strength of this book is its recency. Not only does it introduce the most updated technologies needed for data journalism (like the aforementioned), but it also includes some very recent news events as examples to illustrate their implications for data journalism, such as the Snowden leaks, and the offshore banking leaks involving the secret British Virgin Islands-based businesses of the rich and famous around the world. Both of these happened just last year. Considering the turn-around cycle for publishing a book, this recency is quite impressive.
Of course, this recency may have come with a price. It seems the price for it, with this book, is paid in sporadic typos, reference errors, and inconsistent writing styles from chapter to chapter. Putting together for a book chapters authored by individuals from different backgrounds is not always easy, but it is possible and doable. There is one single chapter that is based on original research data with a methodology section, which reads more like a journal article than a book chapter. Some chapter contributors seem unfamiliar with scholarly writing, as references are missing where necessary. The chapter on China appears rather conspicuous – it is the only chapter that speaks in the context of an individual country; some claims, especially those made in the conclusion section, are unsubstantiated, without any references cited.
One may get lost while reading Section 3 of the book, which is labeled “The broader issues – locally, nationally, and internationally.” This section lacks a cohesive and logical structure in itself and with the book as a whole. It includes a wide variety of topics, ranging from sensor journalism to data visualization, from the role of a data journalist in holding the powerful accountable to using D3 to bring data alive, and so forth. As it is hard to make sense of its organizing logic (or no logic at all?), at times, readers are kept wondering, “Where are we?” The “The advent of the statistician journalist” chapter looks rather out of place in this section. The last section seems a more appropriate host for it, with its chapter addressing the dual roles of a data journalist.
It is also a bit disappointing that a couple of chapters, although otherwise very well written, are not really data-journalism specific, but rather of journalism in general. Topics such as accuracy in numbers and keeping an eye on government need to make sound connections to data journalism in order to be placed in this particular publication.
Most chapter contributors are UK-based so this book has a heavy UK context that requires some basic background knowledge to comprehend it. However, the information conveyed in the context is otherwise of universal reference value. Its UK context should not hinder it from being considered, overall, as an appreciated addition to the limited literature on data journalism.