Data Critique
The dataset chosen organizes a collection of maritime events that occurred along New Jersey’s coastline. The data is broken down into 36 key categories of information for each recorded shipwreck, spanning 4721 different ships lost between the years 1705 to 2013.
How was this dataset generated?
The dataset is a comprehensive collection spanning the years of 1705 to 2013, which was generated through historical records, encyclopedias, and the internet. The data was generated by New Jersey Maritime Museum, and the database was generated by Fusion Tables, an experimental tool developed by Google. Sources that were scanned and stored online are scraped using keywords and toggle search words in order to generate a comprehensive data collection. The data collected is categorized by name of the ship, owner, date of shipwreck, area found, and vessel type.
What are the original sources?
There are a variety of sources that were used to generate the database of maritime events that occured on the New Jersey Coast. These sources include newspaper archives, ship’s logs, diaries, US Life-Saving Services annual reports, shipwreck books, periodicals and many websites on the internet. Of these sources, the newspaper archives, ship’s logs, diaries, USLSS (which became the US Coast Guard after a merger) annual reports, and periodicals are original sources. Some of the newspaper archives utilized were the New Times Archive, NewspaperArchive, National Archives - UK, and the Press of AC Archives. There are also many primary sources from the ships and the crew, including ship’s logs, directories, and assorted narratives from crew members like Admiral Dupont, a civil war admiral, and Joseph Tidwell, a survivor from the USS Jacob Jones wreck. Periodicals from 1705 to 2013 and annual USLSS and USCG reports are also original sources that were used to generate the database. Many of these original sources have been preserved over time through digital records.
What information, events, or phenomena can your dataset illuminate?
A clear spike in shipwrecks began in about 1860, peaked in 1886, and began to decline in the 1890s. This period encompasses the Civil War and the tumultuous times after it. Thus, our data set can not only illuminate the unsettled nature of that time period, but also leads to other questions: were societal pressures impacting the safety of ships on the east coast of the United States? Did any unique factors result in increased shipwrecks during this time period? What might those unique factors have been? By delving deeper into the reasons the ships sank, cargo and personnel these ships were carrying, and metadata about the historical events of the time, it is possible to gain a deeper insight into the factors causing an uptick in shipwrecks between 1860 and 1890.
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Of the 36 key categories of information from the dataset, another aspect that is worth noting is the popularity of different vessel types throughout the time interval. The purpose of maritime transportation has greatly changed since the early 18th century, which can reveal a lot about not only the political landscape of the country, but also the nature of ship usage. Additionally, it leads to other questions like how have vessel types changed with technological advancements? Does the frequency of wrecks that we see for certain types paint a bigger picture of the nature of ship usage during the time? By identifying the use case for each wreckage and understanding the context behind the event, we can better understand the environmental factors in play at the time.
What information is left out? What can the data set not reveal?
Since many of the listed shipwrecks have never been actually found, it follows that there are missing data points within the latitudinal and longitudinal location categories for some entries. In addition, the data set contains little relevant information pertaining to the crew or passengers aboard the ship, so it is difficult to make conclusions about the ships’ personnel and the purposes of their voyages. This gap in our data also means we cannot paint a full humanistic picture for each wreck in terms of if it could have been avoided and if other factors such as sailing experience and nautical knowledge or lack thereof played a factor in a ship’s demise. Any assumptions made about the motives for each ship must be gleaned from other categories such as the ship’s cargo, vessel type, and departure port.
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The data also leaves out significant gaps when reporting the number of passengers on board and in fewer cases the size of the ship’s crew. Furthermore, it is hard to tell if lives were lost for ships that have been lost and were not reported as being found, as the data does not assume all lives were lost. For outputs related to ship value and cargo data, the data is missing information for many of the shipwrecks. More importantly, the data does not provide if the value is adjusted or is the real value at the date of loss. The data cannot reveal the extent of these shipwrecks’ economic impact.
What are the ideological effects?
Our dataset is our only source, and so there isn’t a particularly striking narrative behind it. Since it is just a raw collection of data sourced from historical archives, there seems to be little to no favoritism or prejudice in the numbers. However, there could have been some bias in the way that the data was compiled. According to the New Jersey Maritime Museum (the organization that created this database), whenever information was inconsistent between different sources, the “most frequent or most logical choice was used.” Frequency is impartial, but the decision as to what event is “the most logical” can be up for interpretation. We should also consider which shipwrecks were tracked in the first place. Smaller, private ships (especially those from long ago) were probably more likely to be lost to time, or whose absence would go unreported.