Originally posted here on the IBM Social Spotlight Blog.

Many Domino customers are looking for ways to maximize their Domino investment, but are facing business and organizational challenges such as:

  • How to generate insights from large amounts of Domino application data in the organization
  • How to share the learnings with everyone in the organization, make knowledge easily accessible in team conversations, and leverage the insights to drive better business outcomes
  • How to access valuable information, including intellectual property, experts, etc., from Domino data that was previously unknown

We are introducing an experimental solution to expand the value of Domino data using cognitive technology and a conversational collaboration tool, allowing you to:

  • Identify insights from Domino data using IBM Watson Explorer
  • Query and share insights in your conversations on IBM Watson Workspace
  • This article is a case study by the IBM development team in Japan to help address your business challenges by integrating IBM Watson Explorer (WEX) and IBM Watson Workspace (WW).

    Benefits of Watson Explorer and Watson Workspace integration for Domino data

    IBM Watson Explorer provides a simple way to mine and explore all your unstructured data using cognitive exploration, powerful text analytics, and machine-learning capabilities.

    IBM Watson Workspace provides digital team conversation and collaboration spaces, understands business conversations, and helps you quickly take action and make decisions.

    Domino data is usually structured or semi-structured, making IBM Watson Explorer’s facet analysis a natural fit for your Domino data. We will demonstrate how IBM Watson Explorer’s facet analysis works in Watson Workspace. We will also demonstrate how Watson Assistant can be used with IBM Watson Explorer to learn the business dialects and specific language used in your Domino-based business processes, guiding you through interactions.

    We will show how this solution helps you:

    • Find new insights that were not identified before, especially if your Domino data contains both structured and unstructured text data
    • Unleash untapped knowledge from your Domino data for critical business conversations and decision making, right when users need it the most

    If your organization has data assets on Domino, this solution has the power to change the way you work across multiple industries and use cases:

    • R&D: extract insights from data-rich, historical discussions and identify innovation opportunities in your existing designs and architectural materials
    • IT dev/ops: find similar events in the past, identify the key players involved, and access runbooks quickly under strict SLAs
    • Call centers: Locate relevant information from past client interactions and provide the most effective response to customers
    • Factory maintenance: Quickly identify relevant FAQ and instructions directly from the field engineer’s notes, identifying the right people to resolve the issue
    • Watson Workspace conversations help you respond with agility and speed when faced with important customer needs and business challenges.

    Solution overview

    This is an experimental solution that integrates Watson Workspace and Watson Explorer for enterprise data. Domino databases are the primary target for this solution as demonstrate below, but other enterprise data can also be integrated as shown in Figure A below.

    Figure A

    In summary, these are the main benefits of this experimental solution:

      Zero-coding, easy to configure Watson Workspace application

    • Some variations in query patterns to Watson Explorer are provided — chat bot, slash command (*) and natural language (Watson Assistant)
    • Advanced Watson Explorer search and facet analysis by Watson Workspace’s Action Fulfillment feature (*). Watson Explorer facets are exposed through the Watson Workspace application as choices without explicit coding to the facets
    • Watson Assistant integration – automated entity additions and updates that are enriched from Domino data by Watson Explorer

    The solution allows you to leverage enterprise data in Watson Workspace with Watson Explorer. The enterprise data is first imported or crawled in Watson Explorer. Domino is already supported by Watson Explorer’s crawler. Data analysts familiar with your business processes and data structure can set up Watson Explorer datasets and collections appropriately. Domino fields are mapped to facets. Once the collection and facets are set up, you can add our application to Watson Workspace by configuring settings in a simple configuration file. You may also configure Watson Assistant to use natural language queries. For more details on Watson Assistant support for Watson Workspace, please see the topic of IBM Watson Work Services.

    Note: * These are Watson Workspace BETA features as of August 2018.

    Example — Retail store VOC

    In order to demonstrate the solution, we have selected a sample dataset of Voice of Customer with 800 records that are typically found in Domino databases (Figure-B). By using a full-text search in a Notes client, you may find some documents easily by specifying keywords. You may also find documents by various views.

    Figure B

    With Watson Explorer, you can generate more insights from existing Domino data beyond a full-text search.

    For example, using a similar document search, you can find relevant documents that are related to your natural language question (Figure C). You can open the Domino document directly from the link in the conversation.

    Figure C

    You may notice that your question in Watson Workspace is underlined, highlighting insights available from Watson Explorer. When you click the underlined statement, you will see choices of facets that you may want to explore (Figure D). For instance, if you choose “Client Location,” then you will find the location that is most relevant to your question (Figure E). Watson Explorer shows you the results in an order based on their relevance and correlation to the query.

    Figure D

    Figure E

    The use of cognitive capabilities isn’t limited to better indexing. Domino data can be enriched with cognitive models. For example, the sentiment of Domino records is understood by Watson Explorer. Furthermore, you may query with your business dialects as Watson Explorer enriches your Domino data for Watson Assistant integration. As a result, you will be able to ask something like the example below for sentiment analysis in regard to a specific cohort (Figure F).

    Figure F

    These examples are just a glimpse of what this solution can do for you Domino data. You will find that the benefits of integrating cognitive technologies with your Domino assets are many, many more.

    The future

    We will continue to evolve this solution so you can unleash new insights from your Domino data using cognitive technology integrated into a conversational collaboration space. In addition, consider moving your Domino workflow and applications to the IBM Cloud with IBM Domino Applications on Cloud (DAC) to further enhance the value of your Domino investment. With DAC, you are able to:

    • Determine which Domino assets need to be migrated to cloud and kept in use for extended value
    • Integrate easier with Watson Workspace as a cloud service

    You may also apply this solution to your Domino assets in on-premise servers without moving data to cloud by some additional solutions like IBM Secure Gateway.

    The IBM Watson Explorer and IBM Watson Workspace integration can help improve the return on your investment in Domino by turning your structured / unstructured data into new insights.

    In this case study, we used Watson Explorer as an example integration with IBM’s cognitive technology. You may choose Watson Discovery as well for a similar integration, depending on your business requirements.

    Feel free to contact the ICS Lab in Japan (ICSJPLAB@jp.ibm.com) for more details or if you are interested in setting up a proof of concept with us.

    Hidekuni Ueda
    Manager, IBM Collaboration Solutions Development

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