˲ ˲ The system can help complete forms such as the PC member invitation form and the paper submission form by suggesting likely colleagues based on past collaboration history.

For these reasons, EasyChair and EDAS are an immense contribution to the academic community. According to its Web page, EasyChair hosted over 3,300 conferences in 2010. Because of its optimizations for multiconferences and multitrack conferences, it is mandated for conferences and workshops that participate in the Federated Logic Conference (FLoC), a huge multicon-ference that attracts approximately 1,000 paper submissions.

Data Privacy concerns

Accidental or deliberate disclosure. A privacy concern with cloud-comput-ing-based conference management systems such as EDAS and EasyChair arises because the system administrators are custodians of a huge quantity of data about the submission and reviewing behavior of thousands of researchers, aggregated across multiple conferences. This data could be deliberately or accidentally disclosed, with unwelcome consequences.

˲ ˲ Reviewer anonymity could be compromised, as well as the confidentiality of PC discussions.

˲ ˲ The acceptance success records could be identified, for individual researchers and groups, over a period of years; and

˲ ˲ The aggregated reviewing profile (fair/unfair, thorough/scant, harsh/un-discerning, prompt/late, and so forth) of researchers could be disclosed.

The data could be abused by hiring or promotions committees, funding and award committees, and more generally by researchers choosing collaborators and associates. The mere existence of the data makes the system administrators vulnerable to bribery, coercion, and/or cracking attempts. If the administrators are also researchers, the data potentially puts them in situations of conflict of interest.

The problem of data privacy in general is of course well known, but cloud computing magnifies it. Conference data is an example in our backyard. When conference organizers had to install the software from scratch, there was still a risk of breach of con-

the acceptance
success records
could be identified,
for individual
researchers and
groups, over
a period of years.

fidentiality, but the data was just about one conference. Cloud computing solutions allow data to be aggregated across thousands of conferences over decades, presenting tremendous opportunities for abuse if the data gets into the wrong hands.

Beneficial data mining. In addition to the abuses of conference review data described here, there are some uses that might be considered beneficial. The data could be used to help detect or prevent fraud or other kinds of unwanted behavior, for example, by identifying:

˲ ˲Researchers who systematically unfairly accept each other’s papers, or rivals who systematically reject each other’s papers, or reviewers who reject a paper and later submit to another conference a paper with similar ideas; and

˲ ˲ Undesirable submission patterns and behaviors by individual researchers (such as parallel or serial submissions of the same paper; repeated paper withdrawals after acceptance; and recurring content changes between submitted version and final version).

The data could also be used to understand and improve the way conferences are administered. ACM, for example, could use the data to construct quality metrics for its conferences, enabling it to profile the kinds of authors who submit, how much “new blood” is entering the community, and how that changes over different editions of the conference. This could help identify conferences that are emerging as dominant, or others that have outlived their usefulness.

The decisions about who is allowed
to mine the data, and for what purpos-
es, are difficult. Policies should be de-
cided transparently and by consensus,
rather than being left solely to the de
facto data custodians.

Ways forward

Policies and legislation. An obvious first step is to articulate clear policies that circumscribe the ways in which the data is used. For example, a simple policy might be that the data gathered during the administration of a conference should be used only for the management of that particular conference. Adherence to this policy would imply that the data is deleted after the conference, which is not done in the case of Easychair (I don’t know if it is done for EDAS). Other policies might allow wider uses of the data. Debate within different academic communities can be expected to yield consensus about which practices are to be allowed in a discipline, and which ones not. For example, some communities may welcome plagiarism detection based on previously reviewed submissions, while others may consider it useless for their subject, or simply unnecessary.

Since its inception in 2002 and up to the time of writing, EasyChair has appeared not to have any privacy policy, or any statement about the purposes and possible uses of the data it stores. There is no privacy policy linked from its main page, and a search for “privacy policy” (or similar terms) restricted to the domain “ easychair.org” does not yield any results. I have been told that new users are presented with a privacy statement at the time of first signing up to Easychair. I did not create a new account to test this; regardless, the privacy statement is not linked from anywhere or later findable via search. EDAS does have an easily accessed privacy policy, which (while not watertight) appears to comply with the “use only for this conference” principle.

Another direction would be to try to find alternative custodians for the data—custodians that are not themselves also researchers participating actively in conferences. The ACM or IEEE might be considered suitable, although they contribute to decisions about publications and appointments of staff and fellows. Professional data custodians such as Google might also be considered. It may be difficult to find an ideal custodian, especially if cost factors are taken into account.