(This blog post was crossposted over at the Transparency and Accountability Technology Project.)

Global Integrity focuses an increasingly significant amount of its time on technology-related initiatives – building, using, and supporting other organizations that are on the Indaba fieldwork platform is one obvious example. As we’ve continued to grow into a technology-focused organization (while certainly not abandoning the research and fieldwork that got us here), we’ve been forced to pick up on a range of jargon that tends to be embraced within the technology community but is, shall we saw, somewhat less obvious in its meaning to the broader public, including to most transparency and accountability (T&A) non-governmental organizations (NGOs).

Besides offering ripe opportunities for hilarious “lost in translation” moments where neither camp can understand the other, the jargon barrier has real implications for T&A NGOs…and for the technologists seeking to work with them. Re-read the first two paragraphs of this post: I’ve already gratuitously sprinkled around a fair amount of jargon (“NGO,” “transparency and accountability,” “platform”). Importantly for T&A NGOs, it becomes increasingly difficult to make informed decisions as to which technology merits an investment and which is worth ignoring if you can’t follow the conversation.

In the spirit of breaking down the jargon barrier, I offer T&A NGOs the following Top Three Tech Jargon You Need to Know…and why they are worth knowing.

#1: The Cloud. You have probably heard people talk about “the cloud,” “working in the cloud,” or “cloud-based computing.” The cloud refers to the hosting of your data, files, and/or software applications by a third-party’s computers that are not your own.

A real-life example of the cloud in action: Global Integrity maintains not a single computer server of its own. Our website is hosted by a third-party hosting company. Our shared internal work files are stored and accessed by staff via Basecamp, a third-party project management portal. Our Indaba fieldwork platform is hosted by Amazon Web Services, a massive farm of virtual computer servers used my millions of companies and organizations to run their software and websites without having to store that information on their own servers. Our email, calendars, and contacts are hosted by Google Apps, an increasingly popular cloud-based email platform based on Gmail.

Why the cloud is good: Like many cloud services, all of the services and software mentioned above can be accessed via any web browser on the planet. Our developers can upload new code to Indaba, I can check my email, and my colleagues can edit a shared document from any Internet café on the planet, literally. There are no software applications to install on anyone’s computer, and transitioning to new computer hardware across the organization becomes as simple as porting your web browser bookmarks from one hard drive to another.

Storing documents and running applications from the cloud offers major conveniences and also major cost savings. Global Integrity has never employed an “IT guy.” Why would we need one? We can all use a web browser, and so we can all manage the systems we use on a daily basis. That represents non-trivial savings, especially at scale. The quick math: its costs us roughly US$700 per month to pay for all of the above services (plus several other cloud services I didn’t mention). Try finding an IT guy willing to work for US$700 per month.

Why the cloud might not be good for you: Cloud-based services typically lock your data and applications into an environment from which it is often not easy to extricate them. Google Apps, for example, has loads of tools for importing your data from Microsoft Outlook. Getting that same data out years later when you want to migrate back to Outlook? Not as easy. Basecamp is notorious for failing to offer its clients a tool for exporting their files out of the platform.

These barriers give rise to even more jargon: “walled gardens.” If I can’t get my stuff out, and/or it’s difficult for my Basecamp information to talk to other applications (why is there no synching of Basecamp calendars with Google Apps calendars [shakes fist at sky]?!), that’s not a good thing. But walled gardens are great for the platform provider in terms of locking in paying clients, which explains why accusations of being a “walled garden” are often tossed about the tech community as an insult.

#2: The social graph. The social graph refers to the mapping of relationships between individuals, and in the social media age refers to the increasingly massive amount of data being accumulated and analyzed as Internet users connect themselves to others via platforms such as Facebook. Those billions of Facebook Likes, re-Tweets, and Shares are constantly being aggregated by all sorts of computers and algorithms searching for clues about your personality, interests, possible political affiliation…you name it.

Why the social graph is good: If you want to understand what’s going to motivate me to sign your petition or take off of work to picket Parliament on behalf of your cause, the social graph is a good place to start. This is why so much advocacy and organizing is increasingly going online. Nowhere else can organizers and the organizations behind them tap such a rich set of data to help identify what their users and community really care about. And if you know what your community really cares about, you can begin to craft some really powerful messaging to spur them to action.

Why the social graph might not be good for you: Privacy is a major concern when it comes to the social graph. Not a week goes by without another alleged breach of privacy on one of the many popular social networks. T&A NGOs seeking to leverage social media and the social graph towards their outreach and advocacy efforts need to be keenly aware of the privacy issues involved.

#3: Machine-readable data. Cue scary image from The Matrix. But this term really should matter for all T&A NGOs. Machine-readable data refers to the idea that a computer program should be able to distinguish between the country of “Georgia” listed on my spreadsheet with the US state of “Georgia” listed on yours. Or to understand that “Argentina” in one organization’s database is the same as “argentina” in another or “AR” in a third. Embracing machine-readable data using common formats also opens the door to another much-used buzzword: “mashing up” data (which refers to combining multiple data sets with each other, often on a map, to reveal powerful trends and insights).

Why machine-readable data is good: For a terrific case in point, witness the pain and suffering being incurred by NGOs pushing for greater aid transparency from aid donors by encouraging them to all use the same machine-readable labels and formats for their respective data. Trying to herd the IT guys from multiple government bureaucracies towards a common agreement on shared standards is a task I do not relish! But it’s crucially important if we want to have data at our fingertips that tell us instantly how much money the World Bank is spending on health versus education in a given province in Argentina. That can be powerful stuff.

Why machine-readable data might not be good for you: Turning existing data and information that is locked away in non-standardized and/or non-machine readable formats (e.g. PDF reports) into machine-readable formats can be a hellish brute force experience. It can be a rabbit hole from which you never emerge, or at least without your sanity. NGOs need to be cautious about evaluating the potential return on investment when it comes to embracing machine-readable data, especially in the context of transforming existing information into machine-readable formats.

So they next time you have this jargon thrown at you, here are some questions to ask:

• Do I have control over my information in the cloud? Can I easily bring it back down to Earth whenever I want to? Or is it locked away?

• Is it appropriate (and legal) for me to access my community’s information on the social graph? Will they be annoyed/angry with me for doing so?

• Do we really have 500 person-hours to invest in turning our organizations’ twenty years of hard copy annual reports into machine-readable data? Is it worth the effort?

Sound off in the Comments with your own ideas for tech jargon that T&A NGOs need to know.

– Nathaniel Heller