LaTiS: Interoperability via a Universal Functional Data Model

Datasets with disparate data formats and varied structural organizationrequire that scientific data users spend an inordinate amount of timemanipulating data instead of focusing on their area of expertise - thescience.Numerous data models have been developed and used in various scientificcommunities to ease the burden of data access and integration. However,these data representations tend to be domain specific, makinginteroperability across disciplines challenging.We present an alternative approach towards modeling datasets thattakes a step closer to the mathematical structure of the dataset,emphasizing the functional relationships that are inherent in mostscientific data. As a result, these Functional data structures enable amore representative abstraction of the actual dataset than traditional datamodels, facilitating higher level reasoning that is more closely relatedto the problem domain. (For example, a "time series of spectra" asopposed to multidimensional arrays.)Since any dataset can be represented in this common mathematical form,data access and integration difficulties can be greatly reduced. Themathematical nature of the model also lends itself to an algebra thatcan be used to manipulate datasets, further bringing disparate datasetsinto alignment and simplifying analysis tasks.LaTiS (https://github.com/dlindhol/LaTiS) is an Open Sourceimplementation of this Functional Data Model. In addition to the modelitself, the LaTiS software framework provides a pluggable architecture forWriters that expose existing datasets via the model interface,Operations that manipulate datasets in terms of the model, and Writersthat output a modeled dataset in a variety of forms. LaTiS has enabledus to easily provide access to datasets in their native form andtransform them in real time to improve usability. With the LaTiS serviceinterface, a data provider can also stand up a server to provideuniform access to their data.