Pro­cess­ing, regard­less of the size of the col­lec­tion, has many com­mon fea­tures: In almost all cases, you sur­vey the boxes to see what is there, decide what to keep and how it will be orga­nized, arrange the boxes, cre­ate folder or box lists (inven­to­ries), and write descrip­tive infor­ma­tion. Sheer size does pose some chal­lenges, how­ever. Below are some of the strate­gies I have imple­mented for the ACLU pro­cess­ing project, which con­sists of approx­i­mately 2,400 lin­ear feet of records.

1. Repur­pose data. The infor­ma­tion I received from ACLU, both from inven­to­ries and from the box labels, was inputted into a spread­sheet and formed the basis of my col­lec­tion sur­vey. The sur­vey data, after some clean up, formed the basis of the inven­to­ries cre­ated by my stu­dent assis­tants. And those inven­to­ries are now being used to adjust the arrange­ment of the records. This allowed me to do less sur­vey work, know­ing that the inven­to­ries would pro­vide more infor­ma­tion, and increased my stu­dents’ speed from an aver­age of 1 foot an hour to 3–6 feet an hour for cre­at­ing inventories.

2. Flex­i­bil­ity with inven­tory detail. It is at least twice as fast to make an inven­tory at the box level, so when­ever access would be suf­fi­cient at the box level, or with a few sec­tions per box, we stopped there. This was most appar­ent with legal case files, which are found through­out the col­lec­tion. For each case, the records were in fold­ers by the type of doc­u­ment (i.e. tran­scripts or briefs). Rather than type this list of doc­u­ments for each case, we can sum­ma­rize that in the series descrip­tions and sim­ply make a list of cases. This saved sig­nif­i­cant time with­out sac­ri­fic­ing accessibility.

3. Work in iter­a­tions. While it may seem more effi­cient to look at each box only once, I found that repeated passes allowed me to spend just as much time as needed with each box. For the sur­vey, I first looked at each box briefly, and then ana­lyzed that infor­ma­tion to see if I could place the box within the arrange­ment. For the remain­ing boxes, I went through this process a few more times, spend­ing more time with the remain­ing boxes on each pass, until at the end of three months I knew where each box belonged in the orga­ni­za­tion. We also plan to make addi­tional passes through boxes likely to con­tain restricted records.

4. Find ways to manip­u­late data. What­ever means you use to cre­ate descrip­tive infor­ma­tion, you should find ways to ana­lyze and manip­u­late the data. In our case, we are using Microsoft Excel. The sort­ing and fil­ter­ing func­tion­al­i­ties have been crit­i­cal for under­stand­ing and re-ordering the sur­vey and inven­tory data, and other func­tions and for­mu­las have assisted in check­ing stu­dent work for accu­racy and data clean up. We have also devel­oped some sim­ple macros to allow us to cal­cu­late date restric­tions and pre­pare the data for EAD encod­ing, which allow the find­ing aids to be deliv­ered and searched online.

5. Pri­or­i­tize time. Since the pri­mary goal of pro­cess­ing is to improve acces­si­bil­ity, the vast major­ity of our time is being spent on gain­ing intel­lec­tual con­trol over the records: cre­at­ing inven­to­ries, descrip­tion, and review­ing mate­ri­als for restric­tions. Most of the phys­i­cal work asso­ci­ated with pro­cess­ing, such as replac­ing boxes and fold­ers, will not be done at all since the exist­ing hous­ing is suf­fi­cient, except for the replace­ment of dam­aged boxes. This is also the first col­lec­tion I have processed where we are wait­ing until the end of the project to phys­i­cally arrange the boxes. With the data from the com­pleted inven­to­ries, I can adjust the arrange­ment, and only then will any­thing be moved so we only have to move the boxes once.