SPARC Roadmap

The overall vision and the main goals of the SPARC Portal are to provide a resource for the global scientific community to explore and leverage the scientific output of the SPARC program.

Explore and Discover SPARC Output

Vision: The SPARC Portal permits visitors to explore and discover SPARC output.

Examples: Where suitable, the SPARC Portal makes use of dedicated viewers to inspect data without downloading it (e.g., MBF viewers for microscopy images). Its robust search functionality and linking facilitate the discovery of related datasets and research. The anatomical maps offer powerful exploration and discovery of the Autonomic Nervous System (ANS). Finally, proper usability, visitor guidance, and documentation ensure that visitors can well appreciate the site content.

Information and Insight about/into the ANS and its Physiological Role

Vision: The SPARC Portal provides a user-friendly mechanism to explore how the Autonomic Nervous System (ANS) is structured, how organs are innervated, and how neuronal signalling propagates within the ANS and organs. This is achieved through consolidated and highly curated maps and computational models. The maps serve to visualize anatomical and functional relationships within the ANS. They can be used to discover portal content and to combine content for further analysis (e.g., measurement data as input of a computational model/analysis, computational models that can be coupled, data that serves to validate/constrain a model).

Example: A user can select a specific branch of a particular nerve in the ANS. The SPARC Portal should provide information about the organs that are innervated by this specific branch of the nervous system and how these organs might respond when this branch of the nerve is stimulated. Where available, relevant simulation models that could predict this behavior are displayed.

Finding of related/associated Data, Computational Models, Analysis Functionality, and Anatomical Models

Vision: The SPARC Portal provides access to a large amount of measurement data, computational models, data processing functionality, viewers, and resources. Through curation and mapping, it is possible to find related/associated data, computational models, analysis functionality, and anatomical models. Functional maps can be used to identify models and data that can be coupled, or to provide information about limitations of computational models, by highlighting which functional dependencies are not considered.

Example: When a user has selected a histological nerve cross-section image, the user should be offered the possibility of viewing it with a dedicated microscopy viewer, of segmenting it using a machine-learning tool for nerve-cross section segmentation on o²S²PARC, or of converting it into a computational model suitable for neural interface simulations.

Facilitate Collaboration between SPARC Researchers

Vision: A key strength of the online SPARC DRC infrastructure lies in facilitating collaborative work. The SPARC Portal supports this through its current functionality (e.g., events, news, access to public datasets, and listing of projects and key stakeholders) and upcoming planned functionality such as: 1) discussion forums, 2) ability to request access to embargoed SPARC datasets, 3) enabling joint elaboration of computational models, and 4) helping to bridge the gap between experimental data collection and computational modeling.

Example: Through the SPARC Portal, users login and initiate discussions about available resources within the SPARC ecosystem. They can rank datasets and simulation models, and reach out to the dataset owners to initiate a collaborative effort. Users might be able to submit announcements of events which will be listed and distributed to users who signed up to be continually informed.

FAIRness and TRUSTworthiness in Data/Model Publication (Metadata annotation & querying)

Vision: The FAIR principles stand for Findable, Accessible, Interoperable, and Re-usable. SPARC is committed to ensuring FAIRness and trustworthiness. For that purpose, the SPARC DRC maintains standards and harmonizes these with related standardization efforts. Furthermore, SPARC DRC provides an infrastructure that facilitates and encourages adherence to FAIRness. Currently, the SPARC Portal largely ensures FAIRness, mainly through the curation process, the publication process, mapping, and the design of the simulation framework.

Examples: Some planned features to expand the FAIRness of SPARC data and resources include tracking the provenance and change history of (derived) data and models, support for quality assurance and trustworthiness in o²S²PARC (credibility assessment, verification & validation, functionality to promote the Ten Simple Rules), and an expanded integration knowledge management system powering search functionality.

SPARC Communication and Community Building

Vision: The SPARC Portal serves as a gateway for SPARC communication, both internal and external as well as community building.

Examples: The SPARC Portal acts as a center to disseminate information about the SPARC program (documentation, success stories), SPARC-relevant events (meetings, webinars), and SPARC-related news, as well as a platform for forum-based discussions. The portal also provides links to related initiatives and resources beyond SPARC, and the DRC supports compatibility with selected initiatives and resources. The portal also facilitates communication related to its content (e.g., forum, discussion boards, messaging).

Larger Vision: The above goals address SPARC-related activities, but the members of the DRC are passionate about supporting research endeavors beyond SPARC, particularly in ensuring data quality and research collaboration. Thus, the DRC also aims to:

  1. Ensure FAIRness (e.g., through standards and curation, as well as quality assurance measures) and particularly also reproducible and extendable computational modeling and analysis.
  2. Provide an integrated picture that exposes relationships between different physiological functions, neural maps, measurement data, and computational models.
  3. Enable large-scale collaborative research.
  4. Facilitate running analyses on the available data and models and to share analyses and the resulting derived data.
  5. Permit sharing of established workflows created by experts.

Roadmap: Short Term (2021)

Functionality planned for roll out in the second half of 2021

  • Harmonized and extended documentation
    • Extensive documentation of the DRC resources
  • Community building
  • Search and supporting infrastructure
    • Find datasets based on metadata (given values for properties of: Samples, Subjects, Researchers, Protocols, Awards, and Dataset metadata, find all matching datasets)
    • Complex queries across data objects are supported (e.g., All samples collected using a particular protocol, or all images related to subjects from a particular strain across all of the SPARC efforts)
  • Facilitation of collaborative work
    • Ability for the platform to identify users to facilitate messaging, commenting, and other functionality
    • Ability to rate datasets based on quality and order datasets on the SPARC Portal based on this ranking
    • Ability to sign up for programmatic notification about datasets from the SPARC Portal
  • Requesting access to embargoed SPARC datasets through the portal
  • Launch data-specific functionality directly from the portal
    • Ability to launch a specified workflow/viewer on o²S²PARC
  • Integrated viewers in the web portal
    • Common web formats
  • Composing coupled computational models through the maps
    • Functionally connected models (and data) can be selected on the maps and (provided the meta-data indicates compatibility) combined into a coupled mode for simulation on o²S²PARC
  • Maps and scaffolds
  • Login functionality
  • Inclusion of non-SPARC data
    • Workflow for non-SPARC investigators to submit data to the portal
  • Tracking of provenance and change history for data and models
    • Robust concept will be defined for frequently evolving items such as computational model code and derived data

Continuously ongoing activities will include

  • User support (e.g., via SPARC Portal Feedback form)
  • Community building
    • Success stories, PI video interviews
    • Webinars, fireside chats, SPARC Art contest
    • Other events
  • Search and supporting infrastructure
    • Meta-data annotation will be extended to the individual file level e.g., describing the type and content of individual files such as experimental group, subject ID, sample, sex, species, etc.
    • Meta-data will also include content describing data files, e.g., “voltage trace from a patch-clamp experiment”
  • Bridge the gap between experimental data collection and computational modeling
    • New functionality will be added, such as machine learning capabilities and closed-loop control
  • Tracking of provenance and change history for data and models

Longer Term (beyond 2021)

  • Compatibility with other research initiatives
    • Harmonization with research produced by other initiatives will be achieved with an increasing number of repositories and standards
  • Search and supporting infrastructure
    • In the SPARC Portal, users will be able to combine map-based and graph/ontologies-driven searches
    • Given a particular entry on the portal (e.g., dataset, image, etc.), users will have the ability to search the broader community by linking out to SciCrunch, PubMed, or other indexing services
  • Facilitation of collaborative work
    • Messaging and forum functionality will be provided for users to discuss different portal entries (e.g., datasets, files, models, etc.)
    • Specialist users will be able to review datasets
  • Bridge the gap between experimental data collection and computational modeling
  • An exchange platform dedicated to experimentalists reaching out for modeler feedback and vice versa
  • Teaching
    • Adapt the portal to support visualizations and interactions that are valuable for teaching
    • Support the creation of online teaching classes