Are We Legislating Away Our Scientific Future? The Database Debate

The ambiguity of the present copyright laws governing the protection of databases creates a situation where database owners, unsure of how IP laws safeguard their information, overprotect their data with oppressive licenses and technological mechanisms (condoned by the DMCA) that impede interoperation. Databases are fundamental to scientific research, yet the lack of interoperability between databases and limited access inhibits this research. The US Congress, spurred by the European Database Directive, and heavily lobbied by the commercial database industry, is presently considering ways to legislate database protections; most of the present suggestions for legislation will be detrimental to scientific progress. The author agrees that new legislation is necessary, but not to provide extra-copyright protections, as database owners would like, but to create an environment wherein data is easily accessible to academic research and interoperability is encouraged; yet simultaneously providing database owners with incentives to produce new databases. One possibility would be to introduce standardized compulsory licensing of databases to academics following an embargo period where databases could be sold at free-market prices (to recoup costs). Databases would be given some sort of intellectual property protection both during and after this embargo in return for a limiting of technical safeguards and conforming to interoperability standards

The Equational Approach to CF2 Semantics

We introduce a family of new equational semantics for argumentation networks which can handle odd and even loops in a uniform manner. We offer one version of equational semantics which is equivalent to CF2 semantics, and a better version which gives the same results as traditional Dung semantics for even loops but can still handle odd loops.Comment: 36 pages, version dated 15 February 201

Bayesianism without Learning

According to the standard definition, a Bayesian agent is one who forms his posterior belief by conditioning his prior belief on what he has learned, that is, on facts of which he has become certain. Here it is shown that Bayesianism can be described without assuming that the agent acquires any certain information; an agent is Bayesian if his prior, when conditioned on his posterior belief, agrees with the latter. This condition is shown to characterize Bayesian models.Bayesian updating, prior and posterior

Ordered amorphous spin system

A solid is typically deemed amorphous when there are no Bragg peaks in its diffraction pattern. We discuss a two dimensional configuration of Ising spins with an autocorrelation function which vanishes at all nonzero distances, so that its scattering pattern is flat. This configuration is a ground state of a Hamiltonian with deterministic, translationally-invariant and finite range interactions. Despite ostensibly being amorphous, this configuration has perfect underlying order. The finite temperature behavior of this model exhibits ordering transitions at successively larger length scales.Comment: 5 pages, 3 figures. Discussion added on finite temperature behavior; supplemental material adde

Reactive preferential structures and nonmonotonic consequence

We introduce information bearing systems (IBRS) as an abstraction of many logical systems. We define a general semantics for IBRS, and show that IBRS generalize in a natural way preferential semantics and solve open representation problems