Profiles Research Networking Software Harvard Catalyst

Professional Networking and Expertise Mining for Research Collaboration

Profiles Research Networking Software is an NIH-funded open source tool to speed the process of finding researchers with specific areas of expertise for collaboration and professional networking. Profiles RNS imports and analyzes "white pages" information, publications, and other data sources to create and maintain a complete searchable library of web-based electronic CV's. Built-in network analysis and data visualization tools allow administrators to generate research portfolios of their institution, discover connections between parts of their organization, and understand what factors influence collaboration.

Profiles RNS self-populates a database of publication history, research interests and professional relationships for each investigator in an organization. Integrated visualization and search tools make Profiles RNS easy to use, and its customizable look-and-feel allow Profiles RNS to be integrated into an existing website or set up as a stand-alone site. Profiles RNS data is also accessible through an API to power other applications.

Professional Networks

Profiles RNS pioneered the concept of "passive" and "active" networking, which not only enables the website to be a useful and exciting tool on day one, but also allows users to expand its content with information about social networks that only they know.

  • Passive networks are automatically created based on current or past co-authorship history, organizational relationships and geographic proximity. It extends these networks by discovering new connections, such as identifying "similar people" who share related keywords. Offering these additional suggestions, Profiles RNS can lead you to unexpected opportunities for collaboration and new sources of expertise.
  • Users can manually create active networks by identifying advisor, mentor and collaborator relationships with colleagues. Profiles RNS will soon support the OpenSocial standard, which will let researchers use the same types of plug-in collaboration gadgets found on LinkedIn and Google within their active networks.

More Than Simple Search Results

Profiles RNS provides much more useful information than typical directory listings or ordinary literature searches. Algorithms analyze publication data to define a researcher's professional interests with a set of prioritized keywords.

The factors used to rank and weight the significance of a specific keyword as a useful descriptor of a researcher include:

  • The researcher's position in the author list of a publication
  • The importance of a keyword as a publication topic
  • The date of a specific publication
  • The overall commonness of a keyword in the literature
  • The impact of a publication using citation information

The Profiles RNS Author Disambiguation Engine

Profiles RNS uses sophisticated multi-factorial matching algorithms to build a publication history automatically for each researcher in an institution. This "Disambiguation Engine" self-populates the individual researcher overviews in Profiles RNS, and identifies the specific keywords that characterize each researcher.

Using identity information from a managed data source such as a Human Resources database, the Disambiguation Engine extracts citations from PubMed and assigns publications to specific individuals. The Disambiguation Engine uses a number of factors to build each publication history, including:

  • Name permutations (e.g., first name vs first initial)
  • Email address
  • Institution affiliations
  • Known co-authors
  • Journal titles and subject areas
  • Known relevant keywords

Users (or their proxies) can add any missing publications by doing a PubMed search from within Profiles RNS or manually entering publications that do not exist in PubMed. The Disambiguation Engine learns from these changes to improve the results of the next literature analysis and update.

Profiles RNS creates a "career snapshot" that combines directory information, user-contributed content, and publications that are extracted from PubMed by the Profiles RNS Disambiguation Engine. On the right side-bar, Profiles RNS automatically identifies networks of related people and concepts ("passive" networking). On the left, users can create "active networks" with specific colleagues.

User Managed Content and Privacy Controls

Each researcher at an institution has control over her or his information. While contact details and other directory information are managed through the original source system at the institution, each user can select which sections of their overview page is displayed or hidden. In addition to editing their publication lists, users can add a photograph, short narrative summary, and awards to their profiles.

To make managing researcher information easier, Profiles RNS allows proxies to be designated for each user. Proxy access is configurable, controlling the ability to edit or show/hide specific categories of information.

Federated Search and Standards-Based APIs

Profiles RNS uses standards-based web service APIs that can communicate with other computer systems through XML and RDF using Linked Open Data (LOD). This enables sites using Profiles RNS to participate multi-institution networks, such as Direct2Experts, VIVOSearch, and CTSASearch.

Extending Functionality Through an Ontology

Profiles RNS is an ontology-based application, meaning users with administrative privileges can extend the types of data that are supported by simply describing the new entities and their relationships. For example, by stating that a person can "teach" a "course", a new content section for teaching will be added to users' profiles. By default, Profiles RNS uses the VIVO ontology. VIVO is an NIH funded project that created an RDF-based standard for sharing information about researchers. In addition to this "data" ontology, Profiles RNS also has a "presentation" ontology, which allows customization of the layout of the website and defines security rules that determine who can access what data.

Transform Profiles RNS into a Platform

Install the optional Open Research Networking Gadgets (ORNG) extension to plug in free third party or custom applications tailored to your institution. ORNG is based on Open Social standards and leverages the VIVO ontology in Profiles RNS. Build your own custom add-ons using HTML and JavaScript. Or install available add-ons from the ORNG.info App Library.

Profiles Research Networking Software was developed under the supervision of Griffin M Weber, MD, PhD, with support from Grant Number 1 UL1 RR025758-01 to Harvard Catalyst, The Harvard Clinical and Translational Science Center from the National Center for Research Resources and support from Harvard University and its affiliated academic healthcare centers.