# Ad Hoc Data Foraging in a Life Sciences Community Ecosystem Using SoDa +
###### Abstract
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commonsresource indices help with the discovery and identification of interesting data sources and analysis tools that users need, the process is completely manual, sluggish, and limited. They are slow to update and to include new resources, and do not serve the unique needs that users may have. In particular, they do not actively find resources of interest that are not already indexed in the resource list. Linked open data (LOD), on the other hand, has emerged as a promising approach to provide interconnected, machine-readable datasets, but its effectiveness is often hampered by issues related to data quality and accessibility. While LOD emphasizes openness, the FAIR (Findable, Accessible, Interoperable, and Reusable) principles [8] extend this concept, revealing significant gaps in compliance among LOD resources [9]. Tools such as the FAIR-Checker [10] have been developed to evaluate and improve FAIRness in LOD; by utilizing standardized metrics and criteria, this tool enhances transparency and reliability in LOD practices. However, the widespread adoption of FAIR principles remains a challenge, hindering the full realization of LOD's potential in supporting scientific inquiry and data-driven research. It is interesting to note that LOD does not imply FAIR, or vice-versa [11], and both of these concepts are not supported by set standards and thus are very hard to achieve. The question that remains open is how users can find the most useful and relevant resources accessible via the open internet? In this paper, we introduce the concept of data foraging and sharing in a community resource ecosystem [12] that will be curated [13] and will evolve with time [14]. We believe that the ingredients required to construct such an ecosystem are in place and a careful integration of them is ultimately possible. We discuss the architecture and functionalities of the proposed system called _SoDa_ (stands for _Solo_ Data Forager). In SoDa, we integrate four basic subsystems--a resource recommender system, a data access protocol designer or a wrapper system, a query processing system with the help of a schema matcher to support interoperability, and a curation system for knowledge evolution (we invite readers to consult [15] for a formal exposure to the concept of wrappers, and [16] for a discussion on schema matchers. In the presentation to follow, we assume that readers are familiar with these standard concepts in database integration technology). We illustrate the functionality of SoDa using an example from life sciences research. We would like to emphasize that while there are several prominent biological data integration and workflow systems available (e.g., Galaxy [17], Taverna [18], Kepler [19], VisFlow, etc. ), they are largely limited in their capabilities, especially when integrating arbitrary databases and constructing workflows using them. They are also not capable of helping users find the data sources or tools needed to construct a computational pipeline. Some of them are very powerful and supportive since they restrict the resource type they support. For example, Taverna only supports web service compliant resources, while Galaxy largely supports databases that have pre-arranged cooperative arrangements with Galaxy. Such limitations hinder interesting data analysis and scientific expeditions using interesting resources not supported by these systems. For example, the gene-disease association database DisGeNet [20] is not supported by Galaxy or Taverna, nor can they help users discover this database or make them use it in any analysis pipeline. The issue we address in SoDa is as follows: with no prior knowledge or awareness, can a biologist find DisGeNET and use it in a workflow along with another database that potentially has schema disparity with it in a matter of minutes, all without writing a single line of code.