Tables

A table is a grid of records you can read, sort, and filter. It is the working view of a research database: the full set of patents or products laid out at once, with the mappings between them close at hand, so the records that matter can come to the surface.

Each row is a single record, and each table lists one kind: rows are either patents or products, never both at once.

The point of a table is to narrow. You start with everything and cut, with filters and sorting, until only the rows worth opening remain. Everything below is in service of that one move.

A table at a glance#

Here is a Patents table mid-research. Each row is one patent. The first columns carry the patent's own fields; every product under review adds a column of mapping scores, colored by risk. The color does the first pass for you.

One look tells the story. Two patents match the Aurora column outright, Toyota's and QuantumScape's; a few more score high, and the rest sit low enough to wait. That coloring is the whole point: it turns thousands of scores into something you can scan in seconds.

Rows and columns#

Each part of the grid means something specific. Every row is one record, a patent or a product, never a mix. Columns come in three kinds:

• The identifier column names the record and is always present.
• Attribute columns carry the record's attributes, system and custom alike.
• Mapping columns show how the record scores against each record on the other side.

Identifier column#

The left-most column of a table is reserved for the identifier. It stays pinned in place as you scroll the other columns sideways, and it is the one column you can never hide. For patents the identifier is the publication number; for products, the name.

Attribute columns#

Attribute columns show a record's attributes: the system fields Patalyze fills in from the source, and the custom fields you add to extend the record yourself. On a patents table that means titles, applicants, dates, classifications, and status next to your own reviewer or priority columns; a products table does the same with websites, categories, manufacturers, and the rest. Show the ones you need, hide the others. When the field you want does not exist yet, the plus button at the end of the columns is where you create it.

Mapping columns#

Mapping columns are the reason the table exists. Each one stands for a record on the other side: on a Patents table, every product you are checking against adds a column. Where a patent and a product have been compared, the cell at their intersection holds the mapping between them.

A patent has many claims, but the cell leads with the strongest match: the claim that scores highest against the product, shown as a chip with its claim number and score. Any other notable claims sit beside it, with the remainder collapsed into a count. So a glance down the column tells you which patents come closest to reading on your product. Click a cell to open the full mapping behind it, claim by claim.

The color is the score's risk band. Every cell falls into one of four bands, from critical down to low, so the dangerous matches stand out from the safe ones at a glance. The mappings page defines each band and the percentage range behind it.

The cell reads the same from either side. A Products table puts your products in the rows and patents in the columns, but a critical match is critical whichever way you came at it.

Filtering#

Filtering is how you narrow the field. Pick a column, choose an operator, and the rows that fail the test drop away. Every option carries a count, so you can see how many rows a choice keeps before you commit. Add a filter from the toolbar, or open any column's header menu to filter by that column directly.

The move that matters is filtering a mapping column to the critical and high bands. Thousands of rows collapse to the few patents whose claims actually threaten your product, and those are the ones worth opening.

Layer a second filter on top to sharpen the shortlist: a single applicant, say, or in-force patents only. Once the list is right, export it to CSV or Excel; the rows and columns travel with it.

Sorting#

Where a filter removes rows, sorting reorders the ones that remain. Open a column's header menu and sort ascending or descending. A small arrow on the header marks the active direction, and you can clear it just as quickly.

Sort a mapping column from high to low and the closest matches float to the top, before you have set a single filter.

Searching#

Search jumps straight to a record you already have in mind. Type a publication number, a title, or an applicant into the search box, and the table keeps only what matches the text.

A filter narrows by a rule; search narrows by free text. So when all you want is to pull up one known patent, search beats building a filter.

Visualizing a column as a chart#

Any column can become a chart without leaving the table. Open the column's header menu and choose "Visualize as chart". A preview appears, binned the way the column deserves: a status column as a breakdown, a date as a trend, an applicant as a ranking. The preview respects your filters, so it charts exactly the rows you have narrowed down to. Add it to a dashboard to keep it around.

Showing and hiding columns#

Not every column needs to be on screen at once. Hide one straight from its header menu with "Don't show on page", or open the display settings to manage them all: reorder columns, switch between a compact and an expanded row height, and add any column back when you need it again.